Helwig Hauser

Helwig Hauser graduated from Vienna University of Technology, Austria, in 1995 with the degree of a ''Dipl.-Ing.'' (~MSc) in computer science. In 1998, after research on flow visualization, he received the degree of a ''Dr.techn.'' (~PhD) from the same university (see below for a link to the thesis).
He worked as a teaching assistant, then as an assistant professor at the Institute of Computer Graphics [1] at Vienna University of Technology from 1994 until 2000. Afterwards, Helwig Hauser joined the newly founded VRVis Research Center [2], also in Vienna, Austria, as a key researcher in visualization. In 2003, he became the scientific director of VRVis [2].
In 2004, Helwig Hauser was entitled a ''Privatdozent'' at the Vienna University of Technology after his successful Habilitation (see below for a link to the thesis). Also in 2004, he won the IEEE Visualization 2004 Contest (together with H. Doleisch and Ph. Muigg), based on an interactive visual analysis of hurricane Isabel with SimVis [3]. In 2006, he was awarded with the prestigous Heinz Zemanek Award [4] for this work.
Since 2007, Helwig Hauser is professor at the University of Bergen, Norway, where he is leading the research group on visualization [5]. During the first four years, the group grew to a size of 15 researchers, working on projects in medical visualization, the visualization of geological data and models, flow visualization, the visualization of biological data, marine data visualization, and others. Since then, the group is continously contributing to the field (see, for example, the publications of the Bergen VisGroup).
In May 2013, at the Eurographics conference in Girona, Spain, Helwig Hauser - together with his colleagues I. Viola et al. - received the Dirk Bartz Prize for Visual Computing in Medicine (Eurographics Medical Prize) for research on high-quality 3D visualization of in-situ ultrasonography [6].
Helwig Hauser's interests are diverse in visualization and related fields, including interactive visual analysis, illustrative visualization, and the combination of scientific and information visualization, as well as many other related topics. Helwig Hauser is also particularly interested in the application of visualization to the fields of medicine, geoscience, climatology, biology, engineering, and others.

Related links (theses of Helwig Hauser):

  Habilitation of Helwig Hauser, entitled ”Generalizing Focus+Context Visualization” (PDF, 152 pages, dated Dec., 2003), together with the related supplement (PDF, 100 pages, dated Dec., 2003)

  Dissertation (PhD thesis) of Helwig Löffelmann, entitled ”Visualizing Local Properties and Characteristic Structures of Dynamical Systems” (PDF, 130 pages, dated Nov., 1998 – note that H. Hauser was named H. Löffelmann before his marriage in 1999)


Related links (cited from the short biography above):

[1] Home page of the Institute of Computer Graphics and Algorithms at the Vienna University of Technology in Austria

[2] Home page of the VRVis Research Center in Vienna, Austria

[3] Home page of the IEEE Visualization 2004 Contest at the IEEE CS and our entry

[4] Home page of the Heinz Zemanek Award, given every two years to one outstanding research work in CS or a related field, Hall of Fame

[5] Home page of the visualization group at the Dept. of Informatics, Univ. of Bergen, Norway

[6] Home page of the Dirk Bartz Prize, given every second year for outstanding CG contributions to medicine, 2014 Hall of Fame

 

Lecturing

VisFoundations (INF250) course about the foundations of data-oriented visual computing (end of Bachelor, beginning of Master).

Computer Graphics (INF251) course about computer graphics which is designed for the end of the UiB Bachelor study program in computer science and which acts as a preliminary for the UiB Master study program on visualization.

Visualization (INF252) course about visualization which is central to the UiB Master study program on visualization.

Project in Visualization (INF219)programming project in visualization, embedded within the UiB Master study program on visualization.

Selected publs. 2007-2015 (filtered listall)

Interactive Visual Analysis of Large Simulation Ensembles by Kr. Matković, D. Gračanin, M. Jelović, H. Hauser. Proc. Winter Simulation Conference 2015: 517-528, 2015

The State-of-the-Art of Set Visualizationby B. Alsallakh, L. Micallef, W. Aigner, H. Hauser, S. Miksch, P. Rodgers. Computer Graphics Forum, 2015

Expressive Seeding of Multiple Stream Surfaces for Interactive Flow Exploration by A. Brambilla & H. Hauser. Computers & Graphics 47: 123-134, 2015

Interactive Visual Steering of Hierarchical Simulation Ensembles by R. Splechtna, Kr. Matković, D. Gračanin, M. Jelović, H. Hauser. Proc. IEEE VAST:89-96

Interactively Illustrating Polymerization using Three-level Model Fusion by I. Kolesár, J. Parulek, I. Viola, St. Bruckner, A.-Kr. Stavrum, H. Hauser. BMC Bioinformatics 15:345-360, 2014

Attribute Signatures: Dynamic Visual Summaries for Analyzing Multivariate Geographical Databy Ç. Turkay, A. Slingsby, H. Hauser, J. Wood, J. Dykes. IEEE Trans. Vis. & Computer Graphics 20(12):2033-2042, 2014

Characterizing Cancer Subtypes Using Dual Analysis in Caleydo StratomeX by Ç. Turkay, A. Lex, M. Streit, H. Pfister, H. Hauser. IEEE Computer Graphics & Applications 34(2):38-47, 2014

Visual Methods for Analyzing Probabilistic Classification Data by B. Alsallakh, A. Hanbury, H. Hauser, S. Miksch, A. Rauber. IEEE Trans. Vis. & Computer Graphics20(12):1703-1712, 2014

Visual Analytics for Complex Engineering Systems: Hybrid Visual Steering of Simulation Ensembles by Kr. Matković, D. Gracanin, R. Splechtna, M. Jelović, B. Stehno, H. Hauser, W. Purgathofer. IEEE Trans. Vis. & Computer Graphics 20(12):1803-1812, 2014

Interactive Visual Analysis of Heterogeneous Cohort Study Data by P. Angelelli, St. Oeltze, Ç. Turkay, J. Haász, E. Hodneland, A. Lundervold, A. J. Lundervold, B. Preim, H. Hauser. IEEE CG & Appls. 34(5):70-82, 2014

Radial Sets: Interactive Visual Analysis of Large Overlapping Sets by B. Alsallakh, W. Aigner, S. Miksch, and H. Hauser. IEEE Trans. Vis. & Computer Graphics19(12):2496-2505, 2013

Hypothesis Generation by Interactive Visual Exploration of Heterogeneous Medical Databy Ç. Turkay, A. Lundervold, A. J. Lundervold, and H. Hauser.Lecture Notes in Computer Science 7947:1-12, 2013 (often cited)

High-Quality 3D Visualization of In-Situ Ultrasonography by I. Viola, Å. Birkeland, V. Šoltészová, L. Helljesen, H. Hauser, Sp. Kotopoulis, K. Nylund, D. M. Ulvang, O. Kr. Øye, Tr. Hausken, O. H. Gilja. Dirk Bartz Prize of Eurographics 2013, pp. 1-4, 2013

Geological Storytelling by E. Lidal, M. Natali, D. Patel, H. Hauser, I. Viola. Computers & Graphics 37(5):445-459, 2013

Visualization and Visual Analysis of Multifaceted Scientific Data: A Survey by J. Kehrer and H. Hauser.IEEE Trans. Vis. & Computer Graphics 19(3):495-513, 2013 (often cited)

Representative Factor Generation for the Interactive Visual Analysis of High-Dimensional Data by Ç. Turkay, A. Lundervold, A. J. Lundervold, and H. Hauser. IEEE Trans. Vis. & Computer Graphics 18(12):2621-2630, 2012

Interactive Visual Exploration and Analysis of Multivariate Simulation Data by H. Doleisch and H. Hauser. Computing in Science Engineering 14(2):70-77, 2012

Scientific Storytelling Using Visualization by Kw.-L. Ma, I. Liao, J. Frazier, H. Hauser, and H.-N. Kostis. IEEE Computer Graphics and Applications 32(1):12-19, 2012

Straightening Tubular Flow for Side-by-Side Visualization by P. Angelelli and H. Hauser. IEEE Trans. Vis. & Computer Graphics 17(12):2063-2070, 2011

Brushing Dimensions – A Dual Visual Analysis Model for High-dimensional Data by Ç. Turkay, P. Filzmoser, and H. Hauser. Computer Graphics Forum29(3):813-822, 2011

Energy-scale Aware Feature Extraction for Flow Visualization by A. Pobitzer, M. Tutkun, Ø. Andreassen, R. Fuchs, R. Peikert, and H. Hauser. Computer Graphics Forum30(3):771-780, 2011

Interactive Visual Analysis of Temporal Cluster Structures by Ç. Turkay, J. Parulek, N. Reuter, and H. Hauser. Computer Graphics Forum 30(3):711-720, 2011

Curve Density Estimates by O. D. Lampe and H. Hauser.Computer Graphics Forum 30(3):633-642, 2011

The State of the Art in Topology-based Visualization of Unsteady Flow by A. Pobitzer, R. Peikert, R. Fuchs, B. Schindler, A. Kuhn, H. Theisel, Kr. Matković, and H. Hauser. Computer Graphics Forum30(6):1789-1811, 2011

Interactive Visual Analysis of Contrast-enhanced Ultrasound Data based on Small Neighborhood Statistics by P. Angelelli, K. Nylund, O. H. Gilja, and H. Hauser. Computers & Graphics 35(2):218-226, 2011

Interactive Visual Analysis of Heterogeneous Scientific Data across an Interface by J. Kehrer, Ph. Muigg, H. Doleisch, and H. Hauser. IEEE Trans. Vis. & Computer Graphics 17(7):934-946, 2011

Interactive Visual Analysis of Multiple Simulation Runs using the Simulation Model View: Understanding and Tuning of an Electronic Unit Injector by Kr. Matković, D. Gračanin, M. Jelović, A. Ammer, A. Lež, and H. Hauser. IEEE Trans. Vis. & Computer Graphics16(6):1449-1457, 2010

Brushing Moments in Interactive Visual Analysisby J. Kehrer, P. Filzmoser, and H. Hauser. Computer Graphics Forum 29(3):813-822, 2010

Toward a Lagrangian Vector Field Topologyby R. Fuchs, J. Kemmler, B. Schindler, J. Waser, F. Sadlo, H. Hauser, and R. Peikert. Computer Graphics Forum29(3):1163-1172, 2010

On the Way Towards Topology-Based Visualization of Unsteady Flow – the State of the Art by Ar. Pobitzer, R. Peikert, R. Fuchs, B. Schindler, A. Kuhn, H. Theisel, Kr. Matković, and H. Hauser. Eurographics 2010 State-of-the-Art Proceedings, pp. 137-154, 2010

Curve-Centric Volume Reformation for Comparative Visualization by O. Daae Lampe, C. Correa, Kw.-L. Ma, and H. Hauser. IEEE Trans. Vis. & Computer Graphics 15(6):1235-1242, 2009

Knowledge-Assisted Visualization of Seismic Databy D. Patel, Ø. Sture, H. Hauser, Chr. Giertsen, and E. Gröller.Computers & Graphics 33(5):585-596, 2009

Visualization of Multi-Variate Scientific Databy R. Fuchs and H. Hauser. Computer Graphics Forum28(6):1670-1690, 2009 (often cited)

Sonography of the Small Intestine by K. Nylund, Sv. Ødegaard, Tr. Hausken, G. Folvik, G. A. Lied, I. Viola, H. Hauser, and O. H. Gilja. World Journal of Gastroenterology15(11):1319-1330, 2009 (often cited)

Interactive Visual Analysis of Complex Scientific Data as Families of Data Surfaces by Kr. Matković, D. Gračanin, B. Klarin, H. Hauser. IEEE Trans. Vis. & Computer Graphics 15(6):1351-1358, 2009

Path Line Attributes – an Information Visualization Approach to Analyzing the Dynamic Behavior of 3D Time-Dependent Flow Fieldsby K. Shi, H. Theisel, H. Hauser, T. Weinkauf, Kr. Matković, H.-Chr. Hege, and H.-P. Seidel. In Topology-based Methods in Visualization II, Springer, 75-88, 2009 (often cited)

Hypothesis Generation in Climate Research with Interactive Visual Data Exploration by J. Kehrer, Fl. Ladstädter, Ph. Muigg, H. Doleisch, A. Steiner, H. Hauser.IEEE Trans. Vis. & Computer Graphics 14(6):1579-1586, 2008

Interactive Visual Steering – Rapid Visual Prototyping of a Common Rail Injection Systemby Kr. Matković, D. Gračanin, M. Jelović, H. Hauser. IEEE Trans. on Vis. and Computer Graphics 14(6):1699-1706, 2008

Interactive Visual Analysis of Set-Typed Databy W. Freiler, Kr. Matković, H. Hauser. IEEE Transactions on Visualization and Computer Graphics 14(6):1340-1347, 2008

A Four-level Focus+Context Approach to Interactive Visual Analysis of Temporal Features in Large Scientific Data by Ph. Muigg, J. Kehrer, St. Oeltze, H. Piringer, H. Doleisch, B. Preim, H. Hauser.Computer Graphics Forum 27(3):775-782, 2008 (often cited)

Parallel Vectors Criteria for Unsteady Flow Vortices by R. Fuchs, R. Peikert, H. Hauser, F. Sadlo, Ph. Muigg. IEEE Transactions on Visualization and Computer Graphics 14(3):615-626, 2008

Two-Level Approach to Efficient Visualization of Protein Dynamics by O. Daae Lampe, I. Viola, N. Reuter, H. Hauser. IEEE Transactions on Visualization and Computer Graphics, 13(6):1616-1623, 2007 (often cited)

Interactive Visual Analysis of Perfusion Databy St. Oeltze, H. Doleisch, H. Hauser, Ph. Muigg, and B. Preim.IEEE Transactions on Visualization and Computer Graphics, 13(6):1392-1399, 2007 (often cited)

Scalable Hybrid Unstructured and Structured Grid Raycasting by Ph. Muigg, M. Hadwiger, H. Doleisch, and H. Hauser. IEEE Transactions on Visualization and Computer Graphics, 13(6):1592-1599, 2007 (often cited)

Visualization of Multi-variate Scientific Databy R. Bürger and H. Hauser. Eurographics 2007 State-of-the-Art Proceedings, pp. 117-134, 2007 (often cited)

Integrating Local Feature Detectors in the Interactive Visual Analysis of Flow Simulation Data by R. Bürger, Ph. Muigg, M. Ilčík, H. Doleisch, and H. Hauser. EuroVis 2007 Proc., pp. 171-178, 2007

Story Telling for Presentation in Volume Visualization by M. Wohlfart and H. Hauser. EuroVis 2007 Proc., pp. 91-98, 2007 (often cited)

Topology-Based Flow Visualization, The State of the Art by R. Laramee, H. Hauser, L. Zhao, and Fr. Post. In Topology-based Methods in Visualization, Springer, pp. 1-20, 2007 (cited >100*)

Publications

2024

    [PDF] [DOI] [Bibtex]
    @article{splechtna2024interactive,
    title={Interactive design-of-experiments: optimizing a cooling system},
    author={Splechtna, Rainer and Behravan, Majid and Jelovic, Mario and Gracanin, Denis and Hauser, Helwig and Matkovic, Kre{\v{s}}imir},
    journal={IEEE Transactions on Visualization and Computer Graphics},
    year={2024},
    publisher={IEEE},
    doi = {10.1109/TVCG.2024.3456356},
    url = {https://doi.org/10.1109/TVCG.2024.3456356},
    images = {images/splechtna2024cooling.png},
    thumbnails = {images/splechtna2024cooling.png},
    pdf = {pdfs/splechtna2024cooling.pdf},
    abstract = {The optimization of cooling systems is important in many cases, for example for cabin and battery cooling in electric cars. Such an optimization is governed by multiple, conflicting objectives and it is performed across a multi-dimensional parameter space.The extent of the parameter space, the complexity of the non-linear model of the system,as well as the time needed per simulation run and factors that are not modeled in the simulation necessitate an iterative, semi-automatic approach. We present an interactive visual optimization approach, where the user works with a p-h diagram to steer an iterative, guided optimization process. A deep learning (DL) model provides estimates for parameters, given a target characterization of the system, while numerical simulation is used to compute system characteristics for an ensemble of parameter sets. Since the DL model only serves as an approximation of the inverse of the cooling system and since target characteristics can be chosen according to different, competing objectives, an iterative optimization process is realized, developing multiple sets of intermediate solutions, which are visually related to each other.The standard p-h diagram, integrated interactively in this approach, is complemented by a dual, also interactive visual representation of additional expressive measures representing the system characteristics. We show how the known four-points semantic of the p-h diagram meaningfully transfers to the dual data representation.When evaluating this approach in the automotive domain, we found that our solution helped with the overall comprehension of the cooling system and that it lead to a faster convergence during optimization.}
    }

2022

    [PDF] [DOI] [Bibtex]
    @ARTICLE {Garrison2022PhysioSTAR,
    author = "Laura A. Garrison and Ivan Kolesar and Ivan Viola and Helwig Hauser and Stefan Bruckner",
    title = "Trends & Opportunities in Visualization for Physiology: A Multiscale Overview",
    journal = "Computer Graphics Forum",
    year = "2022",
    volume = "41",
    number = "3",
    publisher = "The Eurographics Association and John Wiley & Sons Ltd.",
    pages = "609-643",
    doi = "10.1111/cgf.14575",
    abstract = "Combining elements of biology, chemistry, physics, and medicine, the science of human physiology is complex and multifaceted. In this report, we offer a broad and multiscale perspective on key developments and challenges in visualization for physiology. Our literature search process combined standard methods with a state-of-the-art visual analysis search tool to identify surveys and representative individual approaches for physiology. Our resulting taxonomy sorts literature on two levels. The first level categorizes literature according to organizational complexity and ranges from molecule to organ. A second level identifies any of three high-level visualization tasks within a given work: exploration, analysis, and communication. The findings of this report may be used by visualization researchers to understand the overarching trends, challenges, and opportunities in visualization for physiology and to provide a foundation for discussion and future research directions in this area. ",
    images = "images/garrison-STAR-taxonomy.png",
    thumbnails = "images/garrison-STAR-thumb.png",
    pdf = "pdfs/Garrison_STAR_cameraready.pdf",
    publisher = "The Eurographics Association and John Wiley \& Sons Ltd.",
    project = "VIDI"
    }

2021

    [PDF] [DOI] [Bibtex]
    @article{brushingComparison,
    author={Fan, Chaoran and Hauser, Helwig},
    journal={IEEE Computer Graphics and Applications},
    title={On sketch-based selections from scatterplots using KDE, compared to Mahalanobis and CNN brushing},
    year={2021},
    volume={},
    number={},
    pages={1-13},
    doi={10.1109/MCG.2021.3097889},
    abstract = {"Fast and accurate brushing is crucial in visual data exploration and sketch-based solutions are successful methods. In this paper, we detail a solution, based on kernel density estimation (KDE), which computes a data subset selection in a scatterplot from a simple click-and-drag interaction. We explain, how this technique relates to two alternative approaches, i.e., Mahalanobis brushing and CNN brushing. To study this relation, we conducted two user studies and present both a quantitative three-fold comparison as well as additional details about the prevalence of all possible cases in that each technique succeeds/fails. With this, we also provide a comparison between empirical modeling and implicit modeling by deep learning in terms of accuracy, efficiency, generality and interpretability."},
    pdf = "pdfs/Fan-2021-brushingComparison.pdf",
    images = "images/Fan-2021-brushingComparison.png",
    thumbnails = "images/Fan-2021-brushingComparison.png",
    }
    [PDF] [DOI] [YT] [Bibtex]
    @ARTICLE {Garrison-2021-DimLift,
    author = {Garrison, Laura and M\"{u}ller, Juliane and Schreiber, Stefanie and Oeltze-Jafra, Steffen and Hauser, Helwig and Bruckner, Stefan},
    title = {DimLift: Interactive Hierarchical Data Exploration through Dimensional Bundling},
    journal={IEEE Transactions on Visualization and Computer Graphics},
    year = {2021},
    abstract = {The identification of interesting patterns and relationships is essential to exploratory data analysis. This becomes increasingly difficult in high dimensional datasets. While dimensionality reduction techniques can be utilized to reduce the analysis space, these may unintentionally bury key dimensions within a larger grouping and obfuscate meaningful patterns. With this work we introduce DimLift, a novel visual analysis method for creating and interacting with dimensional bundles. Generated through an iterative dimensionality reduction or user-driven approach, dimensional bundles are expressive groups of dimensions that contribute similarly to the variance of a dataset. Interactive exploration and reconstruction methods via a layered parallel coordinates plot allow users to lift interesting and subtle relationships to the surface, even in complex scenarios of missing and mixed data types. We exemplify the power of this technique in an expert case study on clinical cohort data alongside two additional case examples from nutrition and ecology.},
    volume = {27},
    number = {6},
    pages = {2908--2922},
    pdf = {pdfs/garrison-2021-dimlift.pdf},
    images = {images/garrison_dimlift.jpg},
    thumbnails = {images/garrison_dimlift_thumb.jpg},
    youtube = {https://youtu.be/JSZuhnDyugA},
    doi = {10.1109/TVCG.2021.3057519},
    git = {https://github.com/lauragarrison87/DimLift},
    project = {VIDI},
    }
    [PDF] [DOI] [Bibtex]
    @ARTICLE {Mueller-2021-IDA,
    author = {M\"{u}ller, Juliane and Garrison, Laura and Ulbrich, Philipp and Schreiber, Stefanie and Bruckner, Stefan and Hauser, Helwig and Oeltze-Jafra, Steffen},
    title = {Integrated Dual Analysis of Quantitative and Qualitative High-Dimensional Data},
    journal={IEEE Transactions on Visualization and Computer Graphics},
    year = {2021},
    abstract = {The Dual Analysis framework is a powerful enabling technology for the exploration of high dimensional quantitative data by treating data dimensions as first-class objects that can be explored in tandem with data values. In this work, we extend the Dual Analysis framework through the joint treatment of quantitative (numerical) and qualitative (categorical) dimensions. Computing common measures for all dimensions allows us to visualize both quantitative and qualitative dimensions in the same view. This enables a natural joint treatment of mixed data during interactive visual exploration and analysis. Several measures of variation for nominal qualitative data can also be applied to ordinal qualitative and quantitative data. For example, instead of measuring variability from a mean or median, other measures assess inter-data variation or average variation from a mode. In this work, we demonstrate how these measures can be integrated into the Dual Analysis framework to explore and generate hypotheses about high-dimensional mixed data. A medical case study using clinical routine data of patients suffering from Cerebral Small Vessel Disease (CSVD), conducted with a senior neurologist and a medical student, shows that a joint Dual Analysis approach for quantitative and qualitative data can rapidly lead to new insights based on which new hypotheses may be generated.},
    volume = {27},
    number = {6},
    pages = {2953--2966},
    pdf = {pdfs/Mueller_2020_IDA.pdf},
    images = {images/Mueller_2020_IDA.jpg},
    thumbnails = {images/Mueller_2020_IDA.png},
    doi = {10.1109/TVCG.2021.3056424},
    git = {https://github.com/JulianeMu/IntegratedDualAnalysisAproach_MDA},
    project = {VIDI},
    }
    [PDF] [DOI] [Bibtex]
    @ARTICLE{Palenik-2020-IsoTrotter,
    author={P\'{a}lenik, Juraj and Spengler, Thomas and Hauser, Helwig},
    journal={IEEE Transactions on Visualization and Computer Graphics},
    title={{IsoTrotter: Visually Guided Emprical Modelling of Atmospheric Convection}},
    abstract={Empirical models, fitted to data from observations, are often used in natural sciences to describe physical behaviour and support discoveries. However, with more complex models, the regression of parameters quickly becomes insufficient, requiring a visual parameter space analysis to understand and optimize the models. In this work, we present a design study for building a model describing atmospheric convection. We present a mixed-initiative approach to visually guided modelling, integrating an interactive visual parameter space analysis with partial automatic parameter optimization. Our approach includes a new, semi-automatic technique called IsoTrotting, where we optimize the procedure by navigating along isocontours of the model. We evaluate the model with unique observational data of atmospheric convection based on flight trajectories of paragliders.},
    year={2021},
    volume={27},
    number={2},
    pages={775-784},
    doi={10.1109/TVCG.2020.3030389},
    pdf={pdfs/2020-10-20-Palenik-IsoTrotter.pdf},
    images={images/IsoTrotter2020.png},
    thumbnails={images/IsoTrotter2020.png}
    }

2020

    [PDF] [DOI] [Bibtex]
    @article{sketchingQuery,
    author={Fan, Chaoran and Matkovic, Kresimir and Hauser, Helwig},
    journal={IEEE Transactions on Visualization and Computer Graphics},
    title={Sketch-based fast and accurate querying of time series using parameter-sharing LSTM networks},
    year={2020},
    volume={},
    number={},
    pages={1-12},
    doi={10.1109/TVCG.2020.3002950},
    abstract = {"Sketching is one common approach to query time series data for patterns of interest. Most existing solutions for matching the data with the interaction are based on an empirically modeled similarity function between the user's sketch and the time series data with limited efficiency and accuracy. In this paper, we introduce a machine learning based solution for fast and accurate querying of time series data based on a swift sketching interaction. We build on existing LSTM technology (long short-term memory) to encode both the sketch and the time series data in a network with shared parameters. We use data from a user study to let the network learn a proper similarity function. We focus our approach on perceived similarities and achieve that the learned model also includes a user-side aspect. To the best of our knowledge, this is the first data-driven solution for querying time series data in visual analytics. Besides evaluating the accuracy and efficiency directly in a quantitative way, we also compare our solution to the recently published Qetch algorithm as well as the commonly used dynamic time warping (DTW) algorithm.."},
    pdf = "pdfs/Fan-2020-sketchingQuery.pdf",
    images = "images/Fan-2020-sketchingQuery.png",
    thumbnails = "images/Fan-2020-sketchingQuery.png",
    }
    [PDF] [DOI] [Bibtex]
    @ARTICLE{Palenik-2019-Splatting,
    author={J. P\'{a}lenik and J. By\v{s}ka and S. Bruckner and H. Hauser},
    journal={IEEE Transactions on Visualization and Computer Graphics},
    title={Scale-Space Splatting: Reforming Spacetime for Cross-Scale Exploration of Integral Measures in Molecular Dynamics},
    year={2020},
    volume={26},
    number={1},
    pages={643--653},
    keywords={Data visualization;Computational modeling;Time series analysis;Atmospheric measurements;Particle measurements;Analytical models;Kernel;Scale space;time-series;scientific simulation;multi-scale analysis;space-time cube;molecular dynamics},
    doi={10.1109/TVCG.2019.2934258},
    ISSN={1077-2626},
    month={},
    pdf = "pdfs/scale-space-splatting.pdf",
    images = "images/scale-space-teaser.png",
    thumbnails = "images/scale-space-teaser-thumb.png",
    abstract = "Understanding large amounts of spatiotemporal data from particle-based simulations, such as molecular dynamics, often relies on the computation and analysis of aggregate measures. These, however, by virtue of aggregation, hide structural information about the space/time localization of the studied phenomena. This leads to degenerate cases where the measures fail to capture distinct behaviour. In order to drill into these aggregate values, we propose a multi-scale visual exploration technique. Our novel representation, based on partial domain aggregation, enables the construction of a continuous scale-space for discrete datasets and the simultaneous exploration of scales in both space and time. We link these two scale-spaces in a scale-space space-time cube and model linked views as orthogonal slices through this cube, thus enabling the rapid identification of spatio-temporal patterns at multiple scales. To demonstrate the effectiveness of our approach, we showcase an advanced exploration of a protein-ligand simulation.",
    }

2019

    [PDF] [Bibtex]
    @article{fan2019personalized,
    title={Personalized Sketch-Based Brushing in Scatterplots},
    author={Chaoran Fan and Helwig Hauser},
    journal={IEEE Computer Graphics and Applications},
    volume={39},
    number={4},
    pages={28--39},
    year={2019},
    publisher={IEEE},
    pdf="pdfs/personalizedBrush.pdf",
    images="images/personalizedBrush.png",
    thumbnails = "images/personalizedBrush.png",
    abstract="Brushing is at the heart of most modern visual analytics solutions and effective and efficient brushing is crucial for successful interactive data exploration and analysis. As the user plays a central role in brushing, several data-driven brushing tools have been designed that are based on predicting the user’s brushing goal. All of these general brushing models learn the users’ average brushing preference, which is not optimal for every single user. In this paper, we propose an innovative framework that offers the user opportunities to improve the brushing technique while using it. We realized this framework with a CNN-based brushing technique and the result shows that with additional data from a particular user, the model can be refined (better performance in terms of accuracy), eventually converging to a personalized model based on a moderate amount of retraining."
    }
    [PDF] [DOI] [Bibtex]
    @INPROCEEDINGS {Fan-2019-KDE,
    author = "Chaoran Fan and Helwig Hauser",
    title = "On KDE-based brushing in scatterplots and how it compares to CNN-based brushing",
    booktitle = "Proceedings of MLVis: Machine Learning Methods in Visualisation for Big Data",
    year = "2019",
    publisher = "Eurographics Association",
    abstract = "In this paper, we investigate to which degree the human should be involved into the model design and how good the empirical model can be with more careful design. To find out, we extended our previously published Mahalanobis brush (the best current empirical model in terms of accuracy for brushing points in a scatterplot) by further incorporating the data distribution information that is captured by the kernel density estimation (KDE). Based on this work, we then include a short discussion between the empirical model, designed in detail by an expert and the deep learning-based model that is learned from user data directly",
    pdf = "pdfs/On-KDE-based-brushing-in-scatterplotsand-how-it-compares-to-CNN-based-brushing.pdf",
    images = "images/pic-2.png",
    thumbnails = "images/pic-2.png",
    doi = "10.2312/mlvis.20191157",
    }

2018

    [PDF] [Bibtex]
    @INPROCEEDINGS {hauser2018foundations,
    author = "Hauser, Helwig and Rheingans, Penny and Scheuermann, Gerik",
    title = "Foundations of Data Visualization (Dagstuhl Seminar 18041)",
    booktitle = "Dagstuhl Reports",
    year = "2018",
    volume = "8",
    organization = "Schloss Dagstuhl-Leibniz-Zentrum fuer Informatik",
    abstract = "This report documents the program and the outcomes of Dagstuhl Seminar 18041 “Foundations
    of Data Visualization”. It includes a discussion of the motivation and overall organization, an
    abstract from each of the participants, and a report about each of the working groups.",
    pdf = "pdfs/foundations.pdf",
    thumbnails = "images/foundations.png",
    number = "1"
    }
    [PDF] [Bibtex]
    @MISC {Smit18MMIV,
    author = "N. N. Smit and S. Bruckner and H. Hauser and I. Haldorsen and A. Lundervold and A. S. Lundervold and E. Hodneland and L. Oltedal and K. Specht and E. R. Gruner",
    title = "Research Agenda of the Mohn Medical Imaging and Visualization Centre in Bergen, Norway",
    howpublished = "Poster presented at the EG VCBM workshop 2018",
    month = "September",
    year = "2018",
    abstract = "The Mohn Medical Imaging and Visualization Centre (MMIV) was recently established in collaboration between the University of Bergen, Norway, and the Haukeland University Hospital in Bergen with generous financial support from the Bergen Research Foundation (BFS) to conduct cross-disciplinary research related to state-of-the-art medical imaging, including preclinical and clinical high-field MRI, CT and hybrid PET/CT/MR.The overall goal of the Centre is to research new methods in quantitative imaging and interactive visualization to predict changes in health and disease across spatial and temporal scales. This encompasses research in feature detection, feature extraction, and feature prediction, as well as on methods and techniques for the interactive visualization of spatial and abstract data related to and derived from these features.With special emphasis on the natural and medical sciences, the long-term goal of the Centre is to consolidate excellence in the interplay between medical imaging (physics, chemistry, radiography, radiology), and visualization (computer science and mathematics) and develop novel and refined imaging methods that may ultimately improve patient care. In this poster, we describe the overall research agenda of MMIV and describe the four core projects in the centre.",
    pdf = "pdfs/smit2018posterabstract.pdf",
    images = "images/MMIVPoster.png",
    thumbnails = "images/MMIVPoster.png",
    location = "Granada, Spain",
    project = "VIDI"
    }
    [PDF] [DOI] [Bibtex]
    @ARTICLE {cnn-brush,
    author = "Fan, Chaoran and Hauser, Helwig",
    title = "{Fast and Accurate CNN-based Brushing in Scatterplots}",
    journal = "Computer Graphics Forum (Eurovis 2018)",
    year = "2018",
    abstract = "Brushing plays a central role in most modern visual analytics solutions and effective and efficient techniques for data selection are key to establishing a successful human-computer dialogue. With this paper, we address the need for brushing techniques that are both fast, enabling a fluid interaction in visual data exploration and analysis, and also accurate, i.e., enabling the user to effectively select specific data subsets, even when their geometric delimination is non-trivial. We present a new solution for a near-perfect sketch-based brushing technique, where we exploit a convolutional neural network (CNN) for estimating the intended data selection from a fast and simple click-and-drag interaction and from the data distribution in the visualization. Our key contributions include a drastically reduced error rate-now below 3%, i.e., less than half of the so far best accuracy- and an extension to a larger variety of selected data subsets, going beyond previous limitations due to linear estimation models.",
    pdf = "pdfs/eurovis18.pdf",
    images = "images/cnn.png",
    thumbnails = "images/cnn.png",
    publisher = "The Eurographics Association and John Wiley and Sons Ltd.",
    issn = "1467-8659",
    doi = "10.1111/cgf.13405"
    }

2017

    [PDF] [Bibtex]
    @ARTICLE {matkovic2017quantitative,
    author = "Matkovi{\'c}, Kre{\v{s}}imir and Abraham, Hrvoje and Jelovi{\'c}, Mario and Hauser, Helwig",
    title = "Quantitative externalization of visual data analysis results using local regression models",
    journal = "International Cross-Domain Conference for Machine Learning and Knowledge Extraction",
    year = "2017",
    pages = "199-218",
    abstract = "Both interactive visualization and computational analysis
    methods are useful for data studies and an integration of both approaches
    is promising to successfully combine the benefits of both methodologies.
    In interactive data exploration and analysis workflows, we need successful
    means to quantitatively externalize results from data studies, amounting
    to a particular challenge for the usually qualitative visual data analysis.
    In this paper, we propose a hybrid approach in order to quantitatively
    externalize valuable findings from interactive visual data exploration and
    analysis, based on local linear regression models. The models are built on
    user-selected subsets of the data, and we provide a way of keeping track
    of these models and comparing them. As an additional benefit, we also
    provide the user with the numeric model coefficients. Once the models are
    available, they can be used in subsequent steps of the workflow. A modelbased
    optimization can then be performed, for example, or more complex
    models can be reconstructed using an inversion of the local models. We
    study two datasets to exemplify the proposed approach, a meteorological
    data set for illustration purposes and a simulation ensemble from the
    automotive industry as an actual case study.",
    pdf = "pdfs/Matkovic2017.pdf",
    thumbnails = "images/matkovic_10.png"
    }
    [PDF] [Bibtex]
    @ARTICLE {Furmanova2017Ligand,
    author = "Furmanov{\'a}, Katar{\'\i}na and Jare{\v{s}}ov{\'a}, Miroslava and By{\v{s}}ka, Jan and Jur{\v{c}}{\'i}k, Adam and Parulek, J{\'u}lius and Hauser, Helwig and Kozl{\'i}kov{\'a}, Barbora",
    title = "Interactive exploration of ligand transportation through protein tunnels",
    journal = "BMC Bioinformatics",
    year = "2017",
    volume = "18(Suppl 2)",
    number = "22",
    month = "feb",
    abstract = "Background: Protein structures and their interaction with ligands have been in the focus of biochemistry andstructural biology research for decades. The transportation of ligand into the protein active site is often complexprocess, driven by geometric and physico-chemical properties, which renders the ligand path full of jitter andimpasses. This prevents understanding of the ligand transportation and reasoning behind its behavior along the path.Results: To address the needs of the domain experts we design an explorative visualization solution based on amulti-scale simplification model. It helps to navigate the user to the most interesting parts of the ligand trajectory byexploring different attributes of the ligand and its movement, such as its distance to the active site, changes of aminoacids lining the ligand, or ligand “stuckness�. The process is supported by three linked views – 3D representation of thesimplified trajectory, scatterplot matrix, and bar charts with line representation of ligand-lining amino acids.Conclusions: The usage of our tool is demonstrated on molecular dynamics simulations provided by the domainexperts. The tool was tested by the domain experts from protein engineering and the results confirm that it helps tonavigate the user to the most interesting parts of the ligand trajectory and to understand the ligand behavior",
    pdf = "pdfs/Furmanova2017.pdf",
    images = "images/Furmanova2016Interactive.png",
    thumbnails = "images/Furmanova2016Interactive.png",
    note = "https://doi.org/10.1186/s12859-016-1448-0"
    }
    [PDF] [DOI] [Bibtex]
    @INPROCEEDINGS {newMahalanobisBrush,
    author = "Fan, Chaoran and Hauser, Helwig",
    title = "{User-study Based Optimization of Fast and Accurate Mahalanobis Brushing in Scatterplots}",
    booktitle = "Vision, Modeling & Visualization",
    year = "2017",
    editor = "Matthias Hullin and Reinhard Klein and Thomas Schultz and Angela Yao",
    publisher = "The Eurographics Association",
    abstract = "Brushing is at the heart of most modern visual analytics solutions with coordinated, multiple views and effective brushing is crucial for swift and efficient processes in data exploration and analysis. Given a certain data subset that the user wishes to brush in a data visualization, traditional brushes are usually either accurate (like the lasso) or fast (e.g., a simple geometry like a rectangle or circle). In this paper, we now present a new, fast and accurate brushing technique for scatterplots, based on the Mahalanobis brush, which we have extended and then optimized using data from a user study. We explain the principal, sketchbased model of our new brushing technique (based on a simple click-and-drag interaction), the details of the user study and the related parameter optimization, as well as a quantitative evaluation, considering efficiency, accuracy, and also a comparison with the original Mahalanobis brush.",
    pdf = "pdfs/vmv-final.pdf",
    images = "images/Mahalanobis.png",
    thumbnails = "images/Mahalanobis.png",
    isbn = "978-3-03868-049-9",
    doi = "10.2312/vmv.20171262"
    }
    [PDF] [Bibtex]
    @ARTICLE {Kocincova2017SS,
    author = "Kocincov{\'a}, Lucia and Jare{\v{s}}ov{\'a}, Miroslava and By{\v{s}}ka, Jan and Parulek, J{\'u}lius and Hauser, Helwig and Kozl{\'i}kov{\'a}, Barbora",
    title = "Comparative visualization of protein secondary structures",
    journal = "BMC Bioinformatics",
    year = "2017",
    volume = "18(Suppl 2)",
    number = "23",
    month = "feb",
    abstract = "Background: Protein function is determined by many factors, namely by its constitution, spatial arrangement, anddynamic behavior. Studying these factors helps the biochemists and biologists to better understand the proteinbehavior and to design proteins with modified properties. One of the most common approaches to these studies is tocompare the protein structure with other molecules and to reveal similarities and differences in their polypeptidechains.Results: We support the comparison process by proposing a new visualization technique that bridges the gapbetween traditionally used 1D and 3D representations. By introducing the information about mutual positions ofprotein chains into the 1D sequential representation the users are able to observe the spatial differences between theproteins without any occlusion commonly present in 3D view. Our representation is designed to serve namely forcomparison of multiple proteins or a set of time steps of molecular dynamics simulation.Conclusions: The novel representation is demonstrated on two usage scenarios. The first scenario aims to compare aset of proteins from the family of cytochromes P450 where the position of the secondary structures has a significantimpact on the substrate channeling. The second scenario focuses on the protein flexibility when by comparing a setof time steps our representation helps to reveal the most dynamically changing parts of the protein chain.",
    pdf = "pdfs/Kocincova2017.pdf",
    images = "images/Lucia2016Comparative.png",
    thumbnails = "images/Lucia2016Comparative.png",
    note = "https://doi.org/10.1186/s12859-016-1449-z"
    }
    [PDF] [Bibtex]
    @INPROCEEDINGS {vad_viktor-2017-WVE,
    author = "Viktor Vad and Jan By\v{s}ka and Adam Jur\v{c}\'{i}k and Ivan Viola and Meister Eduard Gr{\"o}ller and Helwig Hauser and Sergio M. Margues and Ji\v{r}\'{i} Damborsk\'{y} and Barbora Kozl\'{i}kov\'{a}",
    title = "Watergate: Visual Exploration of Water Trajectories in Protein Dynamics",
    booktitle = "Eurographics Workshop on Visual Computing for Biology and Medicine 2017",
    year = "2017",
    pages = "33--42",
    abstract = "The function of proteins is tightly related to their interactions with other molecules. The study of such interactions often requires to track the molecules that enter or exit specific regions of the proteins. This is investigated with molecular dynamics simulations, producing the trajectories of thousands of water molecules during hundreds of thousands of time steps. To ease the exploration of such rich spatio-temporal data, we propose a novel workflow for the analysis and visualization of large sets of water-molecule trajectories. Our solution consists of a set of visualization techniques, which help biochemists to classify, cluster, and filter the trajectories and to explore the properties and behavior of selected subsets in detail. Initially, we use an interactive histogram and a time-line visualization to give an overview of all water trajectories and select the interesting ones for further investigation. Further, we depict clusters of trajectories in a novel 2D representation illustrating the flows of water molecules. These views are interactively linked with a 3D representation where we show individual paths, including their simplification, as well as extracted statistical information displayed by isosurfaces. The proposed solution has been designed in tight collaboration with experts to support specific tasks in their scientific workflows. They also conducted several case studies to evaluate the usability and effectiveness of our new solution with respect to their research scenarios. These confirmed that our proposed solution helps in analyzing water trajectories and in extracting the essential information out of the large amount of input data.",
    pdf = "pdfs/Vad_Victor2017.pdf",
    images = "images/Watergate.png",
    thumbnails = "images/Watergate.png",
    proceedings = "In Proceedings of Eurographics Workshop on Visual Computing for Biology and Medicine",
    location = "September, 2017 Bremen, Germany",
    url = "https://www.cg.tuwien.ac.at/research/publications/2017/vad_viktor-2017-WVE/"
    }
    [PDF] [DOI] [Bibtex]
    @ARTICLE {Turkay2017VIS,
    author = "C. Turkay and E. Kaya and S. Balcisoy and H. Hauser",
    title = "Designing Progressive and Interactive Analytics Processes for High-Dimensional Data Analysis",
    journal = "IEEE Transactions on Visualization and Computer Graphics",
    year = "2017",
    volume = "PP",
    number = "99",
    pages = "1-1",
    month = "jan",
    abstract = "In interactive data analysis processes, the dialogue between the human and the computer is the enabling mechanism that can lead to actionable observations about the phenomena being investigated. It is of paramount importance that this dialogue is not interrupted by slow computational mechanisms that do not consider any known temporal human-computer interaction characteristics that prioritize the perceptual and cognitive capabilities of the users. In cases where the analysis involves an integrated computational method, for instance to reduce the dimensionality of the data or to perform clustering, such non-optimal processes are often likely. To remedy this, progressive computations, where results are iteratively improved, are getting increasing interest in visual analytics. In this paper, we present techniques and design considerations to incorporate progressive methods within interactive analysis processes that involve high-dimensional data. We define methodologies to facilitate processes that adhere to the perceptual characteristics of users and describe how online algorithms can be incorporated within these. A set of design recommendations and according methods to support analysts in accomplishing high-dimensional data analysis tasks are then presented. Our arguments and decisions here are informed by observations gathered over a series of analysis sessions with analysts from finance. We document observations and recommendations from this study and present evidence on how our approach contribute to the efficiency and productivity of interactive visual analysis sessions involving high-dimensional data.",
    pdf = "pdfs/Turkay2017VIS.pdf",
    images = "images/Turkay-2017-VIS.png",
    thumbnails = "images/Turkay-2017-VIS.png",
    doi = "10.1109/TVCG.2016.2598470",
    issn = "1077-2626"
    }
    [PDF] [DOI] [YT] [Bibtex]
    @ARTICLE {Kolesar-2017-FCC,
    author = "Ivan Kolesar and Stefan Bruckner and Ivan Viola and Helwig Hauser",
    title = "A Fractional Cartesian Composition Model for Semi-spatial Comparative Visualization Design",
    journal = "IEEE Transactions on Visualization and Computer Graphics",
    year = "2017",
    volume = "23",
    number = "1",
    pages = "851--860",
    month = "jan",
    abstract = "The study of spatial data ensembles leads to substantial visualization  challenges in a variety of applications. In this paper, we present  a model for comparative visualization that supports the design of  according ensemble visualization solutions by partial automation.  We focus on applications, where the user is interested in preserving  selected spatial data characteristics of the data as much as possible—even  when many ensemble members should be jointly studied using comparative  visualization. In our model, we separate the design challenge into  a minimal set of user-specified parameters and an optimization component  for the automatic configuration of the remaining design variables.  We provide an illustrated formal description of our model and exemplify  our approach in the context of several application examples from  different domains in order to demonstrate its generality within the  class of comparative visualization problems for spatial data ensembles.",
    pdf = "pdfs/Kolesar-2017-FCC.pdf",
    images = "images/Kolesar-2017-FCC.jpg",
    thumbnails = "images/Kolesar-2017-FCC.png",
    youtube = "https://www.youtube.com/watch?v=_zk67fmryok",
    doi = "10.1109/TVCG.2016.2598870",
    event = "IEEE SciVis 2016",
    keywords = "visualization models, integrating spatial and non-spatial data visualization, design methodologies",
    location = "Baltimore, USA",
    project = "physioillustration"
    }

2016

    [Bibtex]
    @MISC {moller2016winter,
    author = "Moller, Torsten and Brambilla, Andrea and Hotz, Ingrid and Gordon, Kindlmann and Schulz, Hans Jorg and Hauser, Helwig and Brodtkorb, Andre",
    title = "Geilo Winter School in eScience on Scientific Visualization",
    year = "2016",
    thumbnails = "images/winter.png",
    note = "https://www.cs.ubc.ca/~tmm/talks.html",
    journal = "Geilo Winter School of eSience"
    }
    [PDF] [Bibtex]
    @ARTICLE {preim2016visual,
    author = "Preim, Bernhard and Klemm, Paul and Hauser, Helwig and Hegenscheid, Katrin and Oeltze, Steffen and Toennies, Klaus and V{\"o}lzke, Henry",
    title = "Visual analytics of image-centric cohort studies in epidemiology",
    journal = "Visualization in Medicine and Life Sciences III, Springer",
    year = "2016",
    pages = "221-248",
    abstract = "Epidemiology characterizes the influence of causes to disease and health conditions of defined populations. Cohort studies are population-based studies involving usually large numbers of randomly selected individuals and comprising numerous attributes, ranging from self-reported interview data to results from various medical examinations, e.g., blood and urine samples. Since recently, medical imaging has been used as an additional instrument to assess risk factors and potential prognostic information. In this chapter, we discuss such studies and how the evaluation may benefit from visual analytics. Cluster analysis to define groups, reliable image analysis of organs in medical imaging data and shape space exploration to characterize anatomical shapes are among the visual analytics tools that may enable epidemiologists to fully exploit the potential of their huge and complex data. To gain acceptance, visual analytics tools need to complement more classical epidemiologic tools, primarily hypothesis-driven statistical analysis.",
    pdf = "pdfs/Preim2016_Centric.pdf",
    thumbnails = "images/Preim2016_Centric_1.png"
    }
    [PDF] [Bibtex]
    @ARTICLE {brambilla2016comparative,
    author = "Brambilla, Andrea and Angelelli, Paolo and Andreassen, yvind and Hauser, Helwig",
    title = "Comparative visualization of multiple time surfaces by planar surface reformation",
    journal = "Pacific Visualization Symposium (PacificVis), 2016 IEEE",
    year = "2016",
    pages = "88--95",
    abstract = "Comparing time surfaces at different integration time points, or
    from different seeding areas, can provide valuable insight into
    transport phenomena of fluid flows. Such a comparative study is
    challenging due to the often convoluted shapes of these surfaces.
    We propose a new approach for comparative flow visualization
    based on time surfaces, which exploits the idea of embedding the
    surfaces in a carefully designed, reformed 2D visualization space.
    Such an embedding enables new opportunities for comparative flow
    visualization. We present three different strategies for comparative
    flow visualization that take advantage of the reformation. By reforming the time surfaces, we not only mitigate occlusion issues,
    but we can devote also the third dimension of the visualization
    space to the comparative aspects of the visualization. Our approach
    is effective in a variety of flow study cases. The direct comparison
    of individual time surfaces reveals small scale differences and fine
    details about the fluid’s motion. The concurrent study of multiple
    surface families enables the identification and the comparison of
    the most prominent motion patterns. This work was developed in
    close collaboration with an expert in fluid dynamics, who assessed
    the potential usefulness of this approach in his field.",
    pdf = "pdfs/bambarilla.pdf",
    thumbnails = "images/bambarilla_1.png"
    }
    [PDF] [Bibtex]
    @ARTICLE {radovs2016towards,
    author = "Rado{\v{s}}, Sanjin and Splechtna, Rainer and Matkovi{\'c}, K and Juras, M and Gr{\"o}ller, Eduard and Hauser, Helwig",
    title = "Towards quantitative visual analytics with structured brushing and linked statistics",
    journal = "Computer Graphics Forum",
    year = "2016",
    volume = "35",
    number = "3",
    pages = "251--260",
    abstract = "Until now a lot of visual analytics predominantly delivers qualitative results—based, for example, on a continuous color map or a detailed spatial encoding. Important target applications, however, such as medical diagnosis and decision making, clearly benefit from quantitative analysis results. In this paper we propose several specific extensions to the well-established concept oflinking&brushing in order to make the analysis results more quantitative. We structure the brushing space in order to improvethe reproducibility of the brushing operation, e.g., by introducing the percentile grid. We also enhance the linked visualization with overlaid descriptive statistics to enable a more quantitative reading of the resulting focus+context visualization. Addition-ally, we introduce two novel brushing techniques: the percentile brush and the Mahalanob is brush. Both use the underlying data to support statistically meaningful interactions with the data. We illustrate the use of the new techniques in the context of two case studies, one based on meteorological data and the other one focused on data from the automotive industry where we evaluate a shaft design in the context of mechanical power transmission in cars.",
    pdf = "pdfs/Rado-_et_al-2016-Computer_Graphics_Forum.pdf",
    thumbnails = "images/Rado-_et_al-2016-Computer_Graphics_Forum_1.png"
    }
    [PDF] [DOI] [YT] [Bibtex]
    @INPROCEEDINGS {Stoppel-2016-GIR,
    author = "Sergej Stoppel and Erlend Hodneland and Helwig Hauser and Stefan Bruckner",
    title = "Graxels: Information Rich Primitives for the Visualization of Time-Dependent Spatial Data",
    booktitle = "Proceedings of VCBM 2016",
    year = "2016",
    pages = "183--192",
    month = "sep",
    abstract = "Time-dependent volumetric data has important applications in areas  as diverse as medicine, climatology, and engineering. However, the  simultaneous quantitative assessment of spatial and temporal features  is very challenging. Common visualization techniques show either  the whole volume in one time step (for example using direct volume  rendering) or let the user select a region of interest (ROI) for  which a collection of time-intensity curves is shown. In this paper,  we propose a novel approach that dynamically embeds quantitative  detail views in a spatial layout. Inspired by the concept of small  multiples, we introduce a new primitive graxel (graph pixel). Graxels  are view dependent primitives of time-intensity graphs, generated  on-the-fly by aggregating per-ray information over time and image  regions. Our method enables the detailed feature-aligned visual analysis  of time-dependent volume data and allows interactive refinement and  filtering. Temporal behaviors like frequency relations, aperiodic  or periodic oscillations and their spatial context are easily perceived  with our method. We demonstrate the power of our approach using examples  from medicine and the natural sciences.",
    pdf = "pdfs/Stoppel-2016-GIR.pdf",
    images = "images/Stoppel-2016-GIR.jpg",
    thumbnails = "images/Stoppel-2016-GIR.png",
    youtube = "https://www.youtube.com/watch?v=UsClj3ytd0Y",
    doi = "10.2312/vcbm.20161286",
    event = "VCBM 2016",
    keywords = "time-dependent data, volume data, small multiples",
    location = "Bergen, Norway"
    }
    [Bibtex]
    @INPROCEEDINGS {Kolesar2016VCBM,
    author = "Ivan Kolesar and Jan By\v{s}ka and Julius Parulek and Helwig Hauser and Barbora Kozl\'{i}kov\'{a}",
    title = "Unfolding and Interactive Exploration of Protein Tunnels andtheir Dynamics",
    booktitle = "Eurographics Workshop on Visual Computing for Biology and Medicine",
    year = "2016",
    pages = "1--10",
    month = "sep",
    abstract = "The presence of tunnels in protein structures substantially influences their reactivity with other molecules. Therefore, studying their properties and changes over time has been in the scope of biochemists for decades. In this paper we introduce a novel approach for comparative visualization and exploration of ensembles of tunnels. Our goal is to overcome occlusion problems present in traditional tunnel representations while providing users a quick way to navigate through the input dataset to identify potentially interesting tunnels. First, we unfold the input tunnels to a 2D representation enabling to observe the mutual position of amino acids forming the tunnel surface and the amount of surface they influence. These 2D images are subsequently described by image moments commonly used in image processing. This way we are able to detect similarities and outliers in the dataset, which are visualized as clusters in a scatterplot graph. The same coloring scheme is used in the linked bar chart enabling to detect the position of the cluster members over time. These views provide a way to select a subset of potentially interesting tunnels that can be further explored in detail using the 2D unfolded view and also traditional 3D representation. The usability of our approach is demonstrated on case studies conducted by the domain experts.",
    images = "images/Kolesar-2016-VCBM.png",
    thumbnails = "images/Kolesar-2016-VCBM-thumbnail.jpg",
    proceedings = "Proceedings of Eurographics Workshop on Visual Computing in Biology and Medicine",
    keywords = "unfolding, storytelling, game visualization",
    location = "Bergen, Norway",
    project = "physioillustration"
    }

2015

    [PDF] [Bibtex]
    @INPROCEEDINGS {PBVRVis2015026,
    author = "Matkovic, K and Gracanin, D and Jelovi{\'{c}}, M and Hauser, H",
    title = "Interactive Visual Analysis of Large Simulation Ensembles",
    booktitle = "Proceedings of Winter Simulation Conference (WSC 2015, to appear)",
    year = "2015",
    abstract = "Recent advancements in simulation and computing make it possible to compute large simulation ensembles. A simulation ensemble consists of multiple simulation runs of the same model with different values of control parameters. In order to cope with ensemble data, a modern analysis methodology is necessary. In this paper, we present our experience with simulation ensemble exploration and steering by means of interactive visual analysis. We describe our long-term collaboration with fuel injection experts from the automotive industry. We present how interactive visual analysis can be used to gain a deep understanding in the ensemble data, and how it can be used, in a combination with automatic methods, to steer the ensemble creation, even for very complex systems. Very positive feedback from domain experts motivated us, a team of visualization and simulation experts, to present this research to the simulation community.",
    pdf = "pdfs/matkovic_2015_winter_simConf.pdf",
    images = "images/IVA_matkovic.png",
    thumbnails = "images/IVA_matkovic.png"
    }
    [PDF] [DOI] [Bibtex]
    @ARTICLE {alsallakh2015state,
    author = "Alsallakh, Bilal and Micallef, Luana and Aigner, Wolfgang and Hauser, Helwig and Miksch, Silvia and Rodgers, Peter",
    title = "The State-of-the-Art of Set Visualization",
    journal = "Computer Graphics Forum",
    year = "2015",
    abstract = "Sets comprise a generic data model that has been used in a variety of data analysis problems. Such problems involve analysing and visualizing set relations between multiple sets defined over the same collection of elements. However, visualizing sets is a non-trivial problem due to the large number of possible relations between them. We provide a systematic overview of state-of-the-art techniques for visualizing different kinds of set relations. We classify these techniques into six main categories according to the visual representations they use and the tasks they support. We compare the categories to provide guidance for choosing an appropriate technique for a given problem. Finally, we identify challenges in this area that need further research and propose possible directions to address these challenges. Further resources on set visualization are available at http://www.setviz.net.",
    pdf = "pdfs/Alsallakh_et_al-2016-Computer_Graphics_Forum.pdf",
    images = "images/ThumbNailIMG-SetVisSTAR.png",
    thumbnails = "images/ThumbNailIMG-SetVisSTAR.png",
    organization = "Wiley Online Library",
    booktitle = "Computer Graphics Forum",
    doi = "10.1111/cgf.12722"
    }
    [PDF] [Bibtex]
    @MISC {Hauser2015IRIS,
    author = "Helwig Hauser",
    title = "Medical Visualization Research at the VisGroup @ UiB.no/ii",
    howpublished = "Invited talk at IRIS",
    month = "November",
    year = "2015",
    abstract = "Established about eight years ago, the Visualization Research Group is the youngest of six research groups at the Department of Informatics, UiB, focusing on application-oriented basic research in visualization. Medicine and related disciplines (such as biomedicine, biology, etc.) stand for a growing number of grand visualization challenges and the vivid interdisciplinary MedViz network in Bergen gives ample opportunities for internationally recognized visualization research. In this talk, an overview of the visualization research group [1] is given, together with a short review of selected research projects in medical visualization.",
    pdf = "pdfs/2015-11-25-HH-IRIS.pdf",
    images = "images/ThumbNailIRIS.jpg",
    thumbnails = "images/ThumbNailIRIS.jpg",
    day = "25",
    location = "Bergen, Norway"
    }
    [DOI] [Bibtex]
    @ARTICLE {Brambilla15Expressive,
    author = "Andrea Brambilla and Helwig Hauser",
    title = "Expressive Seeding of Multiple Stream Surfaces for Interactive Flow Exploration",
    journal = "Computers \& Graphics",
    year = "2015",
    volume = "47",
    pages = "123--134",
    abstract = "Integral surfaces, such as stream and path surfaces, are highly effective in the context of the exploration and the analysis of the long-term behavior of three-dimensional flows. However, specifying the seeding curves that lead to an expressive set of integral surfaces is a challenging and cumbersome task. In this paper, we propose an algorithm for automatically seeding multiple stream surfaces around a user-specified location of interest. The process is guided by a streamline similarity measure. Within the resulting integral surfaces, adjacent streamlines are as similar as possible to each other. In addition, we aim at conveying different aspects of the flow behavior with each surface. This is achieved by maximizing the dissimilarity between streamlines from different stream surfaces. The capabilities of our technique are demonstrated on a number of application cases. We provide a qualitative comparison with two state-of-the-art approaches. We report from our detailed exchange with a domain expert concerning the expressiveness and usefulness of our approach. A thorough analysis of the few parameters involved is provided. ",
    images = "images/Brambilla15Expressive01.png, images/Brambilla15Expressive02.png",
    thumbnails = "images/Brambilla15Expressive01_thumb.png, images/Brambilla15Expressive02_thumb.png",
    publisher = "Elsevier",
    doi = "http://dx.doi.org/10.1016/j.cag.2015.01.002",
    url = "http://www.sciencedirect.com/science/article/pii/S0097849315000035",
    keywords = "Flow visualization; Stream surface selection; Visibility management"
    }
    [PDF] [DOI] [Bibtex]
    @INPROCEEDINGS {splechtna2015interactive,
    author = "Splechtna, Rainer and Matkovic, Kresimir and Gracanin, Denis and Jelovic, Mario and Hauser, Helwig",
    title = "Interactive visual steering of hierarchical simulation ensembles",
    booktitle = "Visual Analytics Science and Technology (VAST), 2015 IEEE Conference on",
    year = "2015",
    pages = "89--96",
    organization = "IEEE",
    abstract = "Multi-level simulation models, i.e., models where different components are simulated using sub-models of varying levels of complexity, belong to the current state-of-the-art in simulation. The existing analysis practice for multi-level simulation results is to manually compare results from different levels of complexity, amounting to a very tedious and error-prone, trial-and-error exploration process. In this paper, we introduce hierarchical visual steering, a new approach to the exploration and design of complex systems. Hierarchical visual steering makes it possible to explore and analyze hierarchical simulation ensembles at different levels of complexity. At each level, we deal with a dynamic simulation ensemble - the ensemble grows during the exploration process. There is at least one such ensemble per simulation level, resulting in a collection of dynamic ensembles, analyzed simultaneously. The key challenge is to map the multi-dimensional parameter space of one ensemble to the multi-dimensional parameter space of another ensemble (from another level). In order to support the interactive visual analysis of such complex data we propose a novel approach to interactive and semi-automatic parameter space segmentation and comparison. The approach combines a novel interaction technique and automatic, computational methods - clustering, concave hull computation, and concave polygon overlapping - to support the analysts in the cross-ensemble parameter space mapping. In addition to the novel parameter space segmentation we also deploy coordinated multiple views with standard plots. We describe the abstract analysis tasks, identified during a case study, i.e., the design of a variable valve actuation system of a car engine. The study is conducted in cooperation with experts from the automotive industry. Very positive feedback indicates the usefulness and efficiency of the newly proposed approach.",
    pdf = "pdfs/Splechtna_2015.pdf",
    images = "images/ThumbNailIMG-HierSteering.png",
    thumbnails = "images/ThumbNailIMG-HierSteering.png",
    doi = "10.1109/VAST.2015.7347635"
    }
    [PDF] [Bibtex]
    @MISC {Hauser2015Austria,
    author = "Helwig Hauser",
    title = "Integrating Spatial \& Non-spatial Data in Visualization",
    howpublished = "Invited talk",
    month = "October",
    year = "2015",
    abstract = "New opportunities in data science, such as the consideration of cohort study data, require new approaches to the appropriate design of an effective visualization. We need to capitalize on successful solutions from previous research, of course, but we should also explore new strategies that challenge our already established mindset in visualization. In this talk, I address the specific challenge of integrating spatial and non-spatial data in visualization, in particular, when the spatial aspect of the data is of great importance to the user---this could relate to the morphological information in a 3D medical scan or the geometrical aspects of flow features in a CFD simulation. In data visualizaiton, the actual mapping step---from data to a visual form---is certainly crucial and we should strive to optimally exploit the great opportunities that we have in designing this step. In data-intensive sciences, the study objects of interest are increasingly often represented by extensive and rich datasets (aka. big data)---while traditionally the focus of visualization was on individual, static datasets, we now face dynamic data, representing entire ensembles of study entities, etc. Visualization gets a lot harder, when facing such new 'big data' challenges---both on the designer sider as well as also on the user side. At the same time, however, also the potential for impact is increasing, which amounts to a fantastic motivation for new basic research in visualization.",
    pdf = "pdfs/2015-10-14-HHauser-InvTalk.pdf",
    images = "images/ThumbPicHHAustria2015.png",
    thumbnails = "images/ThumbPicHHAustria2015.png",
    location = "Vienna, Austria"
    }
    [PDF] [Bibtex]
    @MISC {Hauser2015VIS,
    author = "Helwig Hauser",
    title = "From Anatomy to Physiology in Medical Visualization",
    howpublished = "Tutorial talk at IEEE VIS 2015",
    month = "October",
    year = "2015",
    abstract = "Generally, medical visualization assists the diagnosis of diseases as well as the treatment of patients. Capturing the patients anatomy, which to a large degree is in the focus of traditional MedViz, certainly is one important key to the success of medical visualization. At least equally important, if not even more, is the consideration of physiology, entailing the complex of function (or malfunction) of the patient. Modern imaging modalities extend beyond the simple depiction of static anatomical snapshots to capturing temporal processes as well as to covering multiple scales of physiology eventually linking molecular biology to medicine. The visualization of human physiology complements other techniques, for example lab tests for quantifying certain physiological functions. We deem ourselves at the beginning of an interesting extension of MedViz research to increasingly capture physiology in addition to anatomy.",
    pdf = "pdfs/2015-10-25-VIS2015-TutTalkHH-print2up.pdf",
    images = "images/ThumbnailVisTut.png",
    thumbnails = "images/ThumbnailVisTut.png",
    day = "25",
    location = "Chicago, Illinois, USA"
    }
    [PDF] [Bibtex]
    @MISC {Hauser2015SUBSEA,
    author = "Helwig Hauser",
    title = "Big Data - visualization and visual analytics",
    howpublished = "Invited talk at the NCE Subsea Forum",
    month = "March",
    year = "2015",
    pdf = "pdfs/2015-03-19-NCE-BigDataVA-print2up.pdf",
    images = "images/ThumbnailBigData.jpg",
    thumbnails = "images/ThumbnailBigData.jpg",
    day = "19",
    location = "Bergen, Norway"
    }

2014

    [PDF] [Bibtex]
    @MISC {Hauser2014BigData,
    author = "Helwig Hauser",
    title = "Big Data - a threat or an opportunity for our modern society?",
    howpublished = "Invited talk at the Alumni Event of the University of Bergen, Norway",
    month = "May",
    year = "2014",
    abstract = "Invited talk at the Alumni Event of the University of Bergen, Norway",
    pdf = "pdfs/2014-05-10-UiB-Alumni-BigDataTalkHH-print2up.pdf",
    images = "images/2014-05-10-UiB-Alumni-BigDataTalkHH-print2up_Image_0003.jpg",
    thumbnails = "images/2014-05-10-UiB-Alumni-BigDataTalkHH-print2up_Image_0003.jpg",
    location = "Bergen, Norway"
    }
    [Bibtex]
    @ARTICLE {alsallakh2014visual,
    author = "Alsallakh, Bilal and Hanbury, Allan and Hauser, Helwig and Miksch, Silvia and Rauber, Andreas",
    title = "Visual methods for analyzing probabilistic classification data",
    journal = "Visualization and Computer Graphics, IEEE Transactions on",
    year = "2014",
    volume = "20",
    number = "12",
    pages = "1703--1712",
    abstract = "Multi-class classifiers often compute scores for the classification samples describing probabilities to belong to different classes. In order to improve the performance of such classifiers, machine learning experts need to analyze classification results for a large number of labeled samples to find possible reasons for incorrect classification. Confusion matrices are widely used for this purpose. However, they provide no information about classification scores and features computed for the samples. We propose a set of integrated visual methods for analyzing the performance of probabilistic classifiers. Our methods provide insight into different aspects of the classification results for a large number of samples. One visualization emphasizes at which probabilities these samples were classified and how these probabilities correlate with classification error in terms of false positives and false negatives. Another view emphasizes the features of these samples and ranks them by their separation power between selected true and false classifications. We demonstrate the insight gained using our technique in a benchmarking classification dataset, and show how it enables improving classification performance by interactively defining and evaluating post-classification rules.",
    images = "images/alsallakh2014visual3.jpg, images/alsallakh2014visual1.jpg, images/alsallakh2014visual2.jpg",
    thumbnails = "images/alsallakh2014visual3.jpg",
    publisher = "IEEE"
    }
    [PDF] [DOI] [Bibtex]
    @MISC {Hauser2014SIBGRAPI,
    author = "Helwig Hauser",
    title = "Interactive Visual Exploration and Analysis of Multi-Faceted Scientific Data",
    howpublished = "Invited talk at SIBGRAPI Conference on Graphics, Patterns and Images in Rio de Janeiro, Brazil",
    month = "August",
    year = "2014",
    abstract = "Invited talk at SIBGRAPI Conference on Graphics, Patterns and Images in Rio de Janeiro, Brazil",
    pdf = "pdfs/2014-08-30-Rio-SIBGRAPI-invited-talk-print-new-new-2up.pdf",
    images = "images/2014-08-30-Rio-SIBGRAPI-invited-talk-print-new-new-2up_Image_0003.jpg, images/2014-08-30-Rio-SIBGRAPI-invited-talk--print-new-new-2up_Image_0001.jpg, images/2014-08-30-Rio-SIBGRAPI-invited-talk-print-new-new-2up_Image_0001(2).jpg, images/2014-08-30-Rio-SIBGRAPI-invited-talk-print-new-new-2up_Image_0001(3).jpg, images/2014-08-30-Rio-SIBGRAPI-invited-talk-print-new-new-2up_Image_0001(4).jpg",
    thumbnails = "images/2014-08-30-Rio-SIBGRAPI-invited-talk-print-new-new-2up_Image_0003.jpg",
    location = "Rio de Janeiro, Brazil",
    doi = "10.1007/978-1-4471-6497-5_15"
    }
    [DOI] [Bibtex]
    @INPROCEEDINGS {alsallakh2014visualizing,
    author = "Alsallakh, Bilal and Micallef, Luana and Aigner, Wolfgang and Hauser, Helwig and Miksch, Silvia and Rodgers, Peter",
    title = "Visualizing sets and set-typed data: State-of-the-art and future challenges",
    booktitle = "Eurographics conference on Visualization (EuroVis)--State of The Art Reports",
    year = "2014",
    pages = "1--21",
    abstract = "A variety of data analysis problems can be modelled by defining multiple sets over a collection of elements and analyzing the relations between these sets. Despite their simple concept, visualizing sets is a non-trivial problem due to the large number of possible relations between them. We provide a systematic overview of state-of-theart techniques for visualizing different kinds of set relations. We classify these techniques into 7 main categories according to the visual representations they use and the tasks they support. We compare the categories to provide guidance for choosing an appropriate technique for a given problem. Finally, we identify challenges in this area that need further research and propose possible directions to address with these challenges.",
    images = "images/img_Page_13_Image_0001.jpg",
    thumbnails = "images/img_Page_13_Image_0001.jpg",
    proceedings = "Eurographics conference on Visualization (EuroVis)--stars",
    doi = "dx.doi.org/10.2312/eurovisstar.20141170"
    }
    [Bibtex]
    @MISC {Kingman14Integrating,
    author = "Pina Kingman and Anne-Kristin Stavrum and Ivan Viola and Helwig Hauser",
    title = "Integrating 2D and 3D Animation to Comprehensively Communicate Biology",
    howpublished = "Poster presented at the VizBi conference 2014",
    month = "March",
    year = "2014",
    abstract = "As research in cellular and molecular biology advances, so does the need to educated both the science research community and the general public. The former must be aware of developments in associated fields, the latter must be able to take responsibility for their own well-being. In both cases, we have a willing and capable audience, ready to delve deeper into the biological sciences. To exploit this opportunity, we need to research new and advanced visual language techniques to further improve communication. We are therefore investigating novel visual communication techniques to advance knowledge translation methods, focusing on effectively communicating abstract functional aspects of biological systems. To this end, we are creating several short animations, each one exploring different design solutions. These design solutions incorporate 2D motion graphics, information visualization, 3D animation, and can be applied to any biological story. In addition to our short animations, this research will culminate in a short film describing NAD-dependent DNA Repair, intended for the general public and researchers interested in these molecular systems.",
    images = "images/Kingman13Integrating.png",
    thumbnails = "images/Kingman13Integrating_thumb.jpg",
    location = "Heidelberg, Germany",
    project = "physioillustration"
    }
    [PDF] [Bibtex]
    @MISC {Hauser2014USP,
    author = "Helwig Hauser",
    title = "About Visualization in Bergen and Interactive Visual Analysis",
    howpublished = "Invited talk at Institute of Computing and Mathematical Sciences, University of São Paolo, in São Carlos, Brazil",
    month = "August",
    year = "2014",
    abstract = "Invited talk at Institute of Computing and Mathematical Sciences, University of São Paolo, in São Carlos, Brazil",
    pdf = "pdfs/2014-08-26-SaoCarlos-USP-inv-talk-print2up.pdf",
    images = "images/2014-08-26-SaoCarlos-USP-invtalk-print2up_Image_0001.jpg, images/2014-08-26--SaoCarlos-USP-inv-talk-print2up_Image_0001(2).jpg, images/2014-08-26-SaoCarlos-USP-inv-talk-print2up_Image_0001(3).jpg, images/2014-08-26-SaoCarlos-USP-inv-talk-print2up_Image_0001(4).jpg, images/2014-08-26-SaoCarlos-USP-inv-talk-print2up_Image_0002.jpg, images/2014-08-26-SaoCarlos-USP-inv-talk-print2up_Image_0003.jpg, images/2014-08-26-SaoCarlos-USP-inv-talk-print2up_Image_0003(2).jpg, images/2014-08-26-SaoCarlos-USP-inv-talk-print2up_Image_0002(2).jpg, images/2014-08-26-SaoCarlos-USP-inv-talk-print2up_Image_0002(3).jpg",
    thumbnails = "images/2014-08-26-SaoCarlos-USP-invtalk-print2up_Image_0001.jpg",
    location = "São Carlos, Brazil"
    }
    [PDF] [Bibtex]
    @MISC {Hauser2014NCE,
    author = "Helwig Hauser",
    title = "About Visual Computing",
    howpublished = "Invited talk at the NCE Subsea Theme Meeting on Visual Computing in Bergen, Norway",
    month = "April",
    year = "2014",
    abstract = "Invited talk at the NCE Subsea Theme Meeting on Visual Computing in Bergen, Norway",
    pdf = "pdfs/2014-04-08-VisCompTalk-HH-print2up.pdf",
    images = "images/2014-04-08-VisCompTalk-HH-print2up_Image_0004.jpg, images/2014-04-08-VisCompTalk-HH-print2up_Image_0006.jpg, images/2014-04-08-VisCompTalk-HH-print2up_Image_0010.jpg, images/2014-04-08-VisCompTalk-HH-print2up_Image_0002.jpg",
    thumbnails = "images/2014-04-08-VisCompTalk-HH-print2up_Image_0010.jpg",
    location = "Bergen, Norway"
    }
    [DOI] [Bibtex]
    @INCOLLECTION {RobertLaramee2014HSH,
    author = "Robert Laramee and Hamish Carr and Min Chen and Helwig Hauser and Lars Linsen and Klaus Mueller and Vijay Natarajan and Harald Obermaier and Ronald Peikert and Eugene Zhang.",
    title = "Future Challenges and Unsolved Problems in Multi-field Visualization",
    booktitle = "Scientific Visualization: Uncertainty, Multifield, Biomedical, and  Scalable Visualization",
    publisher = "Springer",
    year = "2014",
    editor = "Min Chen and Hans Hagen and Charles D. Hansen and Christopher R.  Johnson and Arie E. Kaufman",
    series = "Mathematics and Visualization",
    chapter = "19",
    pages = "205-211",
    month = "sep",
    images = "images/no_thumb.png",
    thumbnails = "images/no_thumb.png",
    doi = "10.1007/978-1-4471-6497-5_19",
    keywords = "uncertainty, heuristics, problem solving",
    owner = "hausser",
    timestamp = "2015.02.06",
    isbn = "978-1-4471-6496-8",
    url = "http://www.springer.com/mathematics/computational+science+%26+engineering/book/978-1-4471-6496-8"
    }
    [PDF] [VID] [Bibtex]
    @INPROCEEDINGS {Kolesar-2014-IPT,
    author = "Ivan Kolesar and Julius Parulek and Ivan Viola and Stefan Bruckner and Anne-Kristin Stavrum and Helwig Hauser",
    title = "Illustrating Polymerization using Three-level Model Fusion",
    booktitle = "Proceedings of IEEE BioVis 2014",
    year = "2014",
    month = "aug",
    abstract = "Research in cell biology is steadily contributing new knowledge about  many different aspects of physiological processes like polymerization,  both with respect to the involved molecular structures as well as  their related function. Illustrations of the spatio-temporal development  of such processes are not only used in biomedical education, but  also can serve scientists as an additional platform for in-silico  experiments. In this paper, we contribute a new, three-level modeling  approach to illustrate physiological processes from the class of  polymerization at different time scales. We integrate physical and  empirical modeling, according to which approach suits the different  involved levels of detail best, and we additionally enable a simple  form of interactive steering while the process is illustrated. We  demonstrate the suitability of our approach in the context of several  polymerization processes and report from a first evaluation with  domain experts.",
    pdf = "pdfs/Kolesar-2014-IPT.pdf",
    vid = "vids/Kolesar14Polymers.mp4",
    images = "images/Kolesar-2014-IPT.jpg",
    thumbnails = "images/Kolesar-2014-IPT.png",
    keywords = "biochemical visualization, L-system modeling, multi-agent modeling, visualization of physiology, polymerization",
    owner = "bruckner",
    project = "physioillustration",
    timestamp = "2014.12.29"
    }
    [DOI] [Bibtex]
    @INCOLLECTION {turkay2014computationally,
    author = "Turkay, Cagatay and Jeanquartier, Fleur and Holzinger, Andreas and Hauser, Helwig",
    title = "On computationally-enhanced visual analysis of heterogeneous data and its application in biomedical informatics",
    booktitle = "Interactive Knowledge Discovery and Data Mining in Biomedical Informatics",
    publisher = "Springer",
    year = "2014",
    pages = "117--140",
    abstract = "With the advance of new data acquisition and generation technologies, the biomedical domain is becoming increasingly data-driven. Thus, understanding the information in large and complex data sets has been in the focus of several research fields such as statistics, data mining, machine learning, and visualization. While the first three fields predominantly rely on computational power, visualization relies mainly on human perceptual and cognitive capabilities for extracting information. Data visualization, similar to Human–Computer Interaction, attempts an appropriate interaction between human and data to interactively exploit data sets. Specifically within the analysis of complex data sets, visualization researchers have integrated computational methods to enhance the interactive processes. In this state-of-the-art report, we investigate how such an integration is carried out. We study the related literature with respect to the underlying analytical tasks and methods of integration. In addition, we focus on how such methods are applied to the biomedical domain and present a concise overview within our taxonomy. Finally, we discuss some open problems and future challenges.",
    images = "images/img_Page_12_Image_0001.jpg, images/img_Page_12_Image_0002.jpg, images/img_Page_12_Image_0003.jpg",
    thumbnails = "images/img_Page_12_Image_0001.jpg",
    doi = "10.1007/978-3-662-43968-5_7)"
    }
    [PDF] [Bibtex]
    @MISC {Hauser2014Dagstuhl,
    author = "Helwig Hauser",
    title = "Semi-abstract visualization of rich scientific data",
    howpublished = "Invited talk at the Dagstuhl 14231 Seminar on Scientific Visualization, Dagstuhl, Germany",
    month = "June",
    year = "2014",
    abstract = "Invited talk at the Dagstuhl 14231 Seminar on Scientific Visualization, Dagstuhl, Germany",
    pdf = "pdfs/2014-06-06-Dagstuhl-SemiAbstractSciVis-print2up.pdf",
    images = "images/2014-06-06-Dagstuhl-SemiAbstractSciVis-print2up_Image_0002(3).jpg, images/2014-06-06-Dagstuhl-SemiAbstractSciVis-print2up_Image_0002(2).jpg, images/2014-06-06-Dagstuhl-SemiAbstractSciVis-print2up_Image_0002.jpg, images/2014-06-06-Dagstuhl-SemiAbstractSciVis-print2up_Image_0008.jpg",
    thumbnails = "images/2014-06-06-Dagstuhl-SemiAbstractSciVis-print2up_Image_0002(3).jpg",
    location = "Dagstuhl, Germany"
    }
    [DOI] [Bibtex]
    @ARTICLE {turkay2014characterizing,
    author = "Turkay, Cagatay and Lex, Alexander and Streit, Marc and Pfister, Hanspeter and Hauser, Helwig",
    title = "Characterizing cancer subtypes using dual analysis in caleydo stratomex",
    journal = "Computer Graphics and Applications, IEEE",
    year = "2014",
    volume = "34",
    number = "2",
    pages = "38--47",
    abstract = "Dual analysis uses statistics to describe both the dimensions and rows of a high-dimensional dataset. Researchers have integrated it into StratomeX, a Caleydo view for cancer subtype analysis. In addition, significant-difference plots show the elements of a candidate subtype that differ significantly from other subtypes, thus letting analysts characterize subtypes. Analysts can also investigate how data samples relate to their assigned subtype and other groups. This approach lets them create well-defined subtypes based on statistical properties. Three case studies demonstrate the approach's utility, showing how it reproduced findings from a published subtype characterization.",
    images = "images/img_Page_08_Image_0001.jpg, images/img_Page_04_Image_0001.jpg",
    thumbnails = "images/img_Page_08_Image_0001.jpg",
    publisher = "IEEE",
    doi = "10.1109/MCG.2014.1"
    }
    [PDF] [DOI] [Bibtex]
    @INPROCEEDINGS {Angelelli-2014-LUP,
    author = "Paolo Angelelli and Sten Roar Snare and Siri Ann Nyrnes and Stefan Bruckner and Helwig Hauser and Lasse L{\o}vstakken",
    title = "Live Ultrasound-based Particle Visualization of Blood Flow in the Heart",
    booktitle = "Proceedings of SCCG 2014",
    year = "2014",
    pages = "42--49",
    month = "may",
    abstract = "We introduce an integrated method for the acquisition, processing  and visualization of live, in-vivo blood flow in the heart. The method  is based on ultrasound imaging, using a plane wave acquisition acquisition  protocol, which produces high frame rate ensemble data that are efficiently  processed to extract directional flow information not previously  available based on conventional Doppler imaging. These data are then  visualized using a tailored pathlet-based visualization approach,  to convey the slice-contained dynamic movement of the blood in the  heart. This is especially important when imaging patients with possible  congenital heart diseases, who typically exhibit complex flow patterns  that are challenging to interpret. With this approach, it now is  possible for the first time to achieve a real-time integration-based  visualization of 2D blood flow aspects based on ultrasonic imaging.  We demonstrate our solution in the context of selected cases of congenital  heart diseases in neonates, showing how our technique allows for  a more accurate and intuitive visualization of shunt flow and vortices.",
    pdf = "pdfs/Angelelli-2014-LUP.pdf",
    images = "images/Angelelli-2014-LUP.jpg",
    thumbnails = "images/Angelelli-2014-LUP.png",
    doi = "10.1145/2643188.2643200",
    keywords = "ultrasound medical visualization, real-time visualization, blood flow visualization",
    url = "http://dx.doi.org/10.1145/2643188.2643200"
    }
    [PDF] [Bibtex]
    @MISC {Hauser2014HiB,
    author = "Helwig Hauser",
    title = "Interactive Visual Analysis of Rich Scientific Data",
    howpublished = "Invited talk at the Bergen University College in Bergen, Norway",
    month = "November",
    year = "2014",
    abstract = "Invited talk at the Bergen University College in Bergen, Norway",
    pdf = "pdfs/2014-11-25-BergenHIB-InvitedTalk-print2up-web.pdf",
    images = "images/2014-11-25-BergenHIB-InvitedTalk-print2up-web_Image_0002.jpg, images/2014-11-25-BergenHIB-InvitedTalk-print2up-web_Image_0003.jpg, images/2014-11-25-BergenHIB-InvitedTalk-print2up-web_Image_0005.jpg, images/2014-11-25-BergenHIB-InvitedTalk-print2up-web_Image_0002(2).jpg, images/2014-11-25-BergenHIB-InvitedTalk-print2up-web_Image_0009.jpg, images/2014-11-25-BergenHIB-InvitedTalk-print2up-web_Image_0002(3).jpg, images/2014-11-25-BergenHIB-InvitedTalk-print2up-web_Image_0009(2).jpg, images/2014-11-25-BergenHIB-InvitedTalk-print2up-web_Image_0003(2).jpg, images/2014-11-25-BergenHIB-InvitedTalk-print2u--web_Image_0007.jpg, images/2014-11-25-BergenHIB-InvitedTalk-print2up-web_Image_0005(2).jpg",
    thumbnails = "images/2014-11-25-BergenHIB-InvitedTalk-print2up-web_Image_0002.jpg",
    location = "Bergen, Norway"
    }
    [PDF] [DOI] [YT] [Bibtex]
    @ARTICLE {Kolesar-2014-IIP,
    author = "Ivan Kolesar and Julius Parulek and Ivan Viola and Stefan Bruckner and Anne-Kristin Stavrum and Helwig Hauser",
    title = "Interactively Illustrating Polymerization using Three-level Model Fusion",
    journal = "BMC Bioinformatics",
    year = "2014",
    volume = "15",
    pages = "345",
    month = "oct",
    abstract = "Research in cell biology is steadily contributing new knowledge about  many aspects of physiological processes, both with respect to the  involved molecular structures as well as their related function.  Illustrations of the spatio-temporal development of such processes  are not only used in biomedical education, but also can serve scientists  as an additional platform for in-silico experiments. Results In this  paper, we contribute a new, three-level modeling approach to illustrate  physiological processes from the class of polymerization at different  time scales. We integrate physical and empirical modeling, according  to which approach best suits the different involved levels of detail,  and we additionally enable a form of interactive steering, while  the process is illustrated. We demonstrate the suitability of our  approach in the context of several polymerization processes and report  from a first evaluation with domain experts. Conclusion We conclude  that our approach provides a new, hybrid modeling approach for illustrating  the process of emergence in physiology, embedded in a densely filled  environment. Our approach of a complementary fusion of three systems  combines the strong points from the different modeling approaches  and is capable to bridge different spatial and temporal scales.",
    pdf = "pdfs/Kolesar-2014-IIP.pdf",
    images = "images/Kolesar-2014-IIP.jpg",
    thumbnails = "images/Kolesar-2014-IIP.png",
    youtube = "https://www.youtube.com/watch?v=iMl5nDicmhg",
    doi = "10.1186/1471-2105-15-345",
    keywords = "biochemical visualization, L-system modeling, multi-agent modeling, visualization of physiology, polymerization",
    owner = "bruckner",
    project = "physioillustration",
    timestamp = "2014.12.29",
    url = "http://www.ii.uib.no/vis/projects/physioillustration/research/interactive-molecular-illustration.html"
    }
    [Bibtex]
    @MISC {Kingman14PARP1,
    author = "Pina Kingman and Anne-Kristin Stavrum and Ivan Viola and Helwig Hauser",
    title = "PARP-1 Binds Damaged DNA",
    howpublished = "Poster presented at the VizBi conference 2014",
    month = "March",
    year = "2014",
    abstract = "This image is an excerpt from the animation entitled Negative charge and poly(ADP)-ribosylation: a scientific animation. The molecules where uploaded from the Protein Data Bank using the Embedded Python Molecular Viewer plug-in for Autodesk Maya (Johnson et al. 2001; Sanner et al. 1996). The scene was rendered using Maxon Cinema 4D and composited in Adobe Photoshop. Subsurface Scattering was chosen to give the molecules a translucent appearance. Two PARP-1 molecules are shown bound to damaged DNA (Coquelle and Glover 2012). This work has been carried out within the PhysioIllustration project (funded by NFR, project #218023).",
    images = "images/Kingman13PARP1.jpg",
    thumbnails = "images/Kingman13PARP1_thumb.jpg",
    location = "Heidelberg, Germany",
    project = "physioillustration"
    }
    [Bibtex]
    @ARTICLE {matkovic2014visual,
    author = "Matkovic, Kresimir and Gracanin, Denis and Splechtna, Rainer and Jelovic, Mario and Stehno, Benedikt and Hauser, Helwig and Purgathofer, Werner",
    title = "Visual analytics for complex engineering systems: Hybrid visual steering of simulation ensembles",
    journal = "Visualization and Computer Graphics, IEEE Transactions on",
    year = "2014",
    volume = "20",
    number = "12",
    pages = "1803--1812",
    abstract = "In this paper we propose a novel approach to hybrid visual steering of simulation ensembles. A simulation ensemble is a collection of simulation runs of the same simulation model using different sets of control parameters. Complex engineering systems have very large parameter spaces so a naïve sampling can result in prohibitively large simulation ensembles. Interactive steering of simulation ensembles provides the means to select relevant points in a multi-dimensional parameter space (design of experiment). Interactive steering efficiently reduces the number of simulation runs needed by coupling simulation and visualization and allowing a user to request new simulations on the fly. As system complexity grows, a pure interactive solution is not always sufficient. The new approach of hybrid steering combines interactive visual steering with automatic optimization. Hybrid steering allows a domain expert to interactively (in a visualization) select data points in an iterative manner, approximate the values in a continuous region of the simulation space (by regression) and automatically find the “best� points in this continuous region based on the specified constraints and objectives (by optimization). We argue that with the full spectrum of optimization options, the steering process can be improved substantially. We describe an integrated system consisting of a simulation, a visualization, and an optimization component. We also describe typical tasks and propose an interactive analysis workflow for complex engineering systems. We demonstrate our approach on a case study from automotive industry, the optimization of a hydraulic circuit in a high pressure common rail Diesel injection system.",
    images = "images/matkovic2014visual1.jpg, images/matkovic2014visual2.jpg",
    thumbnails = "images/matkovic2014visual1.jpg",
    publisher = "IEEE"
    }
    [DOI] [VID] [Bibtex]
    @ARTICLE {Angelelli14Interactive,
    author = "Paolo Angelelli and Steffen Oeltze and Cagatay Turkay and Judit Haasz and Erlend Hodneland and Arvid Lundervold and Astri Johansen Lundervold and Bernhard Preim and Helwig Hauser",
    title = "Interactive Visual Analysis of Heterogeneous Cohort Study Data",
    journal = "Computer Graphics and Applications, IEEE",
    year = "2014",
    volume = "PP",
    number = "99",
    pages = "1-1",
    abstract = "Cohort studies are used in medicine to enable the study of medical hypotheses in large samples. Often, a large amount of heterogeneous data is acquired from many subjects. The analysis is usually hypothesis-driven, i.e., a specific subset of such data is studied to confirm or reject specific hypotheses. In this paper, we demonstrate how we enable the interactive visual exploration and analysis of such data, helping with the generation of new hypotheses and contributing to the process of validating them. We propose a data-cube based model which allows to handle partially overlapping data subsets during the interactive visualization. This model enables the seamless integration of the heterogeneous data, as well as the linking of spatial and non-spatial views on these data. We implemented this model in an application prototype, and used it to analyze data acquired in the context of a cohort study on cognitive aging. In this paper we present a case-study analysis of selected aspects of brain connectivity by using a prototype implementation of the presented model, to demonstrate its potential and flexibility.",
    vid = "vids/angelelli14CohortExplorer.wmv",
    images = "images/angelelli14Cohort.png",
    thumbnails = "images/angelelli14Cohort.png",
    doi = "10.1109/MCG.2014.40",
    url = "http://dx.doi.org/10.1109/MCG.2014.40"
    }
    [DOI] [Bibtex]
    @ARTICLE {turkay2014attribute,
    author = "Turkay, Cagatay and Slingsby, Aidan and Hauser, Helwig and Wood, Jo and Dykes, Jason",
    title = "Attribute signatures: Dynamic visual summaries for analyzing multivariate geographical data",
    journal = "Visualization and Computer Graphics, IEEE Transactions on",
    year = "2014",
    volume = "20",
    number = "12",
    pages = "2033--2042",
    abstract = "The visual analysis of geographically referenced datasets with a large number of attributes is challenging due to the fact that the characteristics of the attributes are highly dependent upon the locations at which they are focussed, and the scale and time at which they are measured. Specialized interactive visual methods are required to help analysts in understanding the characteristics of the attributes when these multiple aspects are considered concurrently. Here, we develop attribute signatures-interactively crafted graphics that show the geographic variability of statistics of attributes through which the extent of dependency between the attributes and geography can be visually explored. We compute a number of statistical measures, which can also account for variations in time and scale, and use them as a basis for' our visualizations. We then employ different graphical configurations to show and compare both continuous and discrete variation of location and scale. Our methods allow variation in multiple statistical summaries of multiple attributes to be considered concurrently and geographically, as evidenced by examples in which the census geography of London and the wider UK are explored.",
    images = "images/img_Page_06_Image_0003.jpg, images/img_Page_01_Image_0002.jpg, images/img_Page_01_Image_0005.jpg, images/img_Page_07_Image_0003.jpg",
    thumbnails = "images/img_Page_06_Image_0003.jpg",
    publisher = "IEEE",
    doi = "10.1109/TVCG.2014.2346265"
    }

2013

    [DOI] [Bibtex]
    @ARTICLE {Lidal13Geological,
    author = "Endre M. Lidal and Mattia Natali and Daniel Patel and Helwig Hauser and Ivan Viola",
    title = "Geological storytelling",
    journal = "Computers \& Graphics",
    year = "2013",
    volume = "37",
    number = "5",
    pages = "445--459 ",
    abstract = "Developing structural geological models from exploratory subsea imaging is difficult and an ill-posed process. The structural geological processes that take place in the subsurface are both complex and time-dependent. We present Geological Storytelling, a novel graphical system for performing rapid and expressive geomodeling. Geologists can convey geological stories that externalize both their model and the reasoning process behind it through our simple, yet expressive sketch-based, flip-over canvases. This rapid modeling interface makes it easy to construct a large variety of geological stories, and our story tree concept facilitates easy management and the exploration of these alternatives. The stories are then animated and the geologists can examine and compare them to identify the most plausible models. Finally, the geological stories can be presented as illustrative animations of automatically synthesized 3D models, which efficiently communicate the complex geological evolution to non-experts and decision makers. Geological storytelling provides a complete pipeline from the ideas and knowledge in the mind of the geologist, through externalized artifacts specialized for discussion and knowledge dissemination among peer-experts, to automatically rendered illustrative 3D animations for communication to lay audience. We have developed geological storytelling in collaboration with domain experts that work with the modeling challenges on a daily basis. For evaluation, we have developed a geological storytelling prototype and presented it to experts and academics from the geosciences. In their feedback, they acknowledge that the rapid and expressive sketching of stories can make them explore more alternatives and that the 3D illustrative animations assist in communicating their models.",
    images = "images/Lidal13Geological01.jpg, images/Lidal13Geological02.png",
    thumbnails = "images/Lidal13Geological01.jpg, images/Lidal13Geological02.png",
    issn = "0097-8493",
    doi = "http://dx.doi.org/10.1016/j.cag.2013.01.010",
    url = "http://www.sciencedirect.com/science/article/pii/S0097849313000125",
    keywords = "Sketch-based modeling; Externalization of mental processes; Storytelling; 3D model synthesis; Animation; Alternatives exploration; Geology; Structural geological models",
    project = "geoillustrator"
    }
    [PDF] [Bibtex]
    @MISC {Hauser2013SouthCHI,
    author = "Helwig Hauser",
    title = "Integrating Interactive and Computational Analysis in Visualization",
    howpublished = "Keynote talk at SouthCHI 2013 in Maribor, Slovenia.",
    month = "June",
    year = "2013",
    abstract = "Keynote talk at SouthCHI 2013 in Maribor, Slovenia.",
    pdf = "pdfs/2013-07-02-Maribor-SouthCHI-Keynote-IVA-print2up.pdf",
    images = "images/2013-07-02-Maribor-SouthCHI-Keynote-IVA-print2up_Image_0001(6).jpg, images/2013-07-02-Maribor-SouthCHI-Keynote-IVA-print2up_Image_0001(5).jpg, images/2013-07-02-Maribor-SouthCHI-Keynote-IVA-print2up_Image_0001(4).jpg, images/2013-07-02-Maribor-SouthCHI-Keynote-IVA-print2up_Image_0001(3).jpg, images/2013-07-02-Maribor-SouthCHI-Keynote-IVA-print2up_Image_0001(2).jpg, images/2013-07-02-Maribor-SouthCHI-Keynote-IVA-print2up_Image_0001.jpg, images/2013-07-02-Maribor-SouthCHI-Keynote-IVA-print2up_Image_0003.jpg",
    thumbnails = "images/2013-07-02-Maribor-SouthCHI-Keynote-IVA-print2up_Image_0001(6).jpg"
    }
    [PDF] [DOI] [Bibtex]
    @INPROCEEDINGS {Brambilla13Integrated,
    author = "Andrea Brambilla and {\O }yvind Andreassen and Helwig Hauser",
    title = "Integrated Multi-aspect visualization of 3D Fluid Flows",
    booktitle = "Proc. of VMV 2013: Vision, Modeling \& Visualization",
    year = "2013",
    pages = "1--9",
    month = "Sept.",
    abstract = "The motion of a fluid is affected by several intertwined flow aspects. Analyzing one aspect at a time can only yield partial information about the flow behavior. More details can be revealed by studying their interactions. Our approach enables the investigation of these interactions by simultaneously visualizing meaningful flow aspects, such as swirling motion and shear strain. We adopt the notions of relevance and coherency. Relevance identifies locations where a certain flow aspect is deemed particularly important. The related piece of information is visualized by a specific visual entity, placed at the corresponding location. Coherency instead represents the homogeneity of a flow property in a local neighborhood. It is exploited in order to avoid visual redundancy and to reduce occlusion and cluttering. We have applied our approach to three CFD datasets, obtaining meaningful insights.",
    pdf = "pdfs/Brambilla13Integrated.pdf",
    images = "images/Brambilla13Integrated_00.png, images/Brambilla13Integrated_01.png",
    thumbnails = "images/Brambilla13Integrated_thumb00.png, images/Brambilla13Integrated_thumb01.png",
    proceedings = "Proc. of VMV 2013: Vision, Modeling \& Visualization",
    url = "http://diglib.eg.org/EG/DL/PE/VMV/VMV13/001-009.pdf",
    doi = "10.2312/PE.VMV.VMV13.001-009",
    location = "Lugano, Switzerland",
    pres = "pdfs/Brambilla13Integrated.pptx",
    extra = "extra/Brambilla13Integrated_extra.pdf"
    }
    [DOI] [Bibtex]
    @ARTICLE {Alsallakh13Radial,
    author = "B. Alsallakh and W. Aigner and S. Miksch and H. Hauser",
    title = "Radial Sets: Interactive Visual Analysis of Large Overlapping Sets",
    journal = "IEEE Transactions on Visualization and Computer Graphics",
    year = "2013",
    volume = "19",
    number = "12",
    pages = "2496-2505",
    abstract = "In many applications, data tables contain multi-valued attributes that often store the memberships of the table entities to multiple sets such as which languages a person masters, which skills an applicant documents, or which features a product comes with. With a growing number of entities, the resulting element-set membership matrix becomes very rich of information about how these sets overlap. Many analysis tasks targeted at set-typed data are concerned with these overlaps as salient features of such data. This paper presents Radial Sets, a novel visual technique to analyze set memberships for a large number of elements. Our technique uses frequency-based representations to enable quickly finding and analyzing different kinds of overlaps between the sets, and relating these overlaps to other attributes of the table entities. Furthermore, it enables various interactions to select elements of interest, find out if they are over-represented in specific sets or overlaps, and if they exhibit a different distribution for a specific attribute compared to the rest of the elements. These interactions allow formulating highly-expressive visual queries on the elements in terms of their set memberships and attribute values. As we demonstrate via two usage scenarios, Radial Sets enable revealing and analyzing a multitude of overlapping patterns between large sets, beyond the limits of state-of-the-art techniques.",
    images = "images/Alsallakh13Radial_3.jpg, images/Alsallakh13Radial_1.jpg, images/Alsallakh13Radial_2.jpg",
    thumbnails = "images/Alsallakh13Radial_3_thumb.png, images/Alsallakh13Radial_1_thumb.png, images/Alsallakh13Radial_2_thumb.png",
    url = "http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6634104",
    doi = "10.1109/TVCG.2013.184",
    issn = "1077-2626"
    }
    [PDF] [DOI] [Bibtex]
    @INPROCEEDINGS {Matkovic13Interactive,
    author = "Kresimir Matkovic and Mario Duras and Denis Gracanin and Rainer Splechtna and Benedikt Stehno and Helwig Hauser ",
    title = "Interactive Visual Analysis in the Concept Stage of a Hybrid-Vehicle Design",
    booktitle = "EuroVis Workshop on Visual Analytics",
    year = "2013",
    pages = "61--65",
    address = "Leipzig, Germany",
    publisher = "Eurographics Association",
    abstract = "The design of modern, hybrid vehicles is an active area of research. As the whole field is new, engineers need intuitive and powerful support tools. In this application paper, we illustrate an application of interactive visual analysis in the concept phase of a hybrid-vehicle design. We exploit coordinated multiple views to explore and analyze a simulation ensemble - a set of simulation runs of the same simulation model. Once we reduce the ensemble to a single run we use a detailed view, including an energy flow graph and a vehicle drive animation. Very positive feedback from domain experts and opportunities for additional improvements encourage further research.",
    pdf = "pdfs/Matkovic13Interactive.pdf",
    images = "images/Matkovic13Interactive_0.jpg, images/Matkovic13Interactive_1.jpg, images/Matkovic13Interactive_2.jpg, images/Matkovic13Interactive_3.jpg",
    thumbnails = "images/Matkovic13Interactive_0_thumb.jpg, images/Matkovic13Interactive_1.jpg, images/Matkovic13Interactive_2.jpg, images/Matkovic13Interactive_3.jpg",
    url = "http://diglib.eg.org/EG/DL/PE/EuroVAST/EuroVA13/061-065.pdf",
    doi = "10.2312/PE.EuroVAST.EuroVA13.061-065",
    isbn = "978-3-905674-55-2"
    }
    [DOI] [Bibtex]
    @INPROCEEDINGS {Glasser13VisualAnalysis,
    author = "Sylvia Glasser and Steffen Oeltze and Uta Preim and Atle Bj{\O }rnerud and Helwig Hauser and Bernhard Preim",
    title = "Visual analysis of longitudinal brain tumor perfusion",
    booktitle = "Proc. SPIE",
    year = "2013",
    volume = "8670",
    pages = "86700Z-86700Z-11",
    abstract = "In clinical research on diagnosis and evaluation of brain tumors, longitudinal perfusion MRI studies are acquired for tumor grading as well as to monitor and assess treatment response and patient prognosis. Within this work, we demonstrate how visual analysis techniques can be adapted to multidimensional datasets from such studies within a framework to support the computer-aided diagnosis of brain tumors. Our solution builds on two innovations: First, we introduce a pipeline yielding comparative, co-registered quantitative perfusion parameter maps over all time steps of the longitudinal study. Second, based on these time-dependent parameter maps, visual analysis methods were developed and adapted to reveal valuable insight into tumor progression, especially regarding the clinical research area of low grade glioma transformation into high grade gliomas. Our examination of four longitudinal brain studies demonstrates the suitability of the presented visual analysis methods and comprises new possibilities for the clinical researcher to characterize the development of low grade gliomas.",
    images = "images/Glasser13VisualAnalysis_0.jpg, images/Glasser13VisualAnalysis_1.jpg",
    thumbnails = "images/Glasser13VisualAnalysis_0.jpg, images/Glasser13VisualAnalysis_1.jpg",
    doi = "10.1117/12.2007878",
    url = "http://dx.doi.org/10.1117/12.2007878",
    project = "yggdrasil, medviz"
    }
    [PDF] [DOI] [Bibtex]
    @INPROCEEDINGS {Borgo13GlyphBased,
    author = "Rita Borgo and Johannes Kehrer and David H. S. Chung and Eamonn Maguire and Robert S. Laramee and Helwig Hauser and Matthew Ward and Min Chen ",
    title = "Glyph-based Visualization: Foundations, Design Guidelines, Techniques and Applications",
    booktitle = "EuroGraphics 2013 State-of-the-Art Reports (STARs)",
    year = "2013",
    pages = "39--63",
    address = "Girona, Spain",
    publisher = "Eurographics Association",
    abstract = "This state of the art report focuses on glyph-based visualization, a common form of visual design where a data set is depicted by a collection of visual objects referred to as glyphs. Its major strength is that patterns of multivariate data involving more than two attribute dimensions can often be more readily perceived in the context of a spatial relationship, whereas many techniques for spatial data such as direct volume rendering find difficult to depict with multivariate or multi-field data, and many techniques for non-spatial data such as parallel coordinates are less able to convey spatial relationships encoded in the data. This report fills several major gaps in the literature, drawing the link between the fundamental concepts in semiotics and the broad spectrum of glyph-based visualization, reviewing existing design guidelines and implementation techniques, and surveying the use of glyph-based visualization in many applications.",
    pdf = "pdfs/Borgo13GlyphBased.pdf",
    images = "images/Borgo13GlyphBased.jpg",
    thumbnails = "images/Borgo13GlyphBased.jpg",
    url = "http://diglib.eg.org/EG/DL/conf/EG2013/stars/039-063.pdf",
    issn = "1017-4656",
    doi = "10.2312/conf/EG2013/stars/039-063"
    }
    [PDF] [Bibtex]
    @MISC {Smestad13Advanced,
    author = "Geir Smestad and Paolo Angelelli and Helwig Hauser",
    title = "Advanced data fusion in 4-D color doppler volume visualization",
    howpublished = "Poster presented at the MedIm conference 2013",
    month = "October",
    year = "2013",
    pdf = "pdfs/Smestad13Advanced.pdf",
    images = "images/Smestad13Advanced.jpg",
    thumbnails = "images/Smestad13Advanced_thumb.jpg",
    location = "Troms{\O }",
    project = "bia"
    }
    [DOI] [Bibtex]
    @INPROCEEDINGS {Viola2013Dirk,
    author = "Ivan Viola and {\AA},smund Birkeland and Veronika \v{S},olt{\'e},szov{\'a}, and Linn Helljesen and Helwig Hauser and Spiros Kotopoulis and Kim Nylund and Dag M. Ulvang and Ola K. {\O }ye and Trygve Hausken and Odd H. Gilja",
    title = "High-Quality 3{D} Visualization of In-Situ Ultrasonography",
    booktitle = "EG 2013---Dirk Bartz Prize",
    year = "2013",
    pages = "1-4",
    abstract = "In recent years medical ultrasound has experienced a rapid development in the quality of real-time 3D ultrasound (US) imaging. The image quality of the 3D volume that was previously possible to achieve within the range of a few seconds, is now possible in a fraction of a second. This technological advance offers entirely new opportunities for the use of US in the clinic. In our project, we investigate how real-time 3D US can be combined with high-performance processing of today's graphics hardware to allow for high-quality 3D visualization and precise navigation during the examination. ",
    images = "images/2013-05-08-DirkBartzPrizeComb.jpg",
    thumbnails = "images/2013-05-08-DirkBartzPrizeComb.jpg",
    doi = "10.2312/conf/EG2013/med/001-004",
    url = "http://diglib.eg.org/EG/DL/conf/EG2013/med/001-004.pdf.abstract.pdf;internal\&action=action.digitallibrary.ShowPaperAbstract",
    project = "illustrasound,medviz,illvis"
    }
    [Bibtex]
    @MISC {Hauser13VisTutorial,
    author = "Steffen Oeltze and Johannes Kehrer and Helwig Hauser",
    title = "Interactive Visual Analysis of Scientific Data",
    howpublished = "Tutorial at the IEEE VisWeek 2013",
    month = "October",
    year = "2013",
    abstract = "In a growing number of application areas, a subject or phenomenon is investigated by means of multiple datasets being acquired over time (spatiotemporal), comprising several attributes per data point (multi-variate), stemming from different data sources (multi-modal) or multiple simulation runs (multi-run/ensemble) [KH13]. Interactive visual analysis (IVA) comprises concepts and techniques for a user-guided knowledge discovery in such complex data. Through a tight feedback loop of computation, visualization and user interaction, it provides new insight into the data and serves as a vehicle for hypotheses generation or validation. It is often implemented via a multiple coordinated view framework where each view is equipped with interactive drill-down operations for focusing on data features. Two classes of views are integrated: physical views, such as direct volume rendering, show information in the context of the spatiotemporal observation space while attribute views, such as scatter plots and parallel coordinates, show relationships between multiple data attributes. The user may drill-down the data by selecting interesting regions of the observation space or attribute ranges leading to a consistent highlighting of this selection in all other views (brushing-and-linking). Three patterns of explorative/analytical procedures may be accomplished by doing so. In a feature localization, the user searches for places in the 3D/4D observation space where certain attribute values are present. In a multi-variate analysis, relations between data attributes are investigated, e.g., by searching for correlations. In a local investigation, the user inspects the values of selected attributes with respect to certain spatiotemporal subsets of the observation space. In this tutorial, we discuss examples for successful applications of IVA to scientific data from various fields: climate research, medicine, epidemiology, and flow simulation / computation, in particular for automotive engineering. We base our discussions on a theoretical foundation of IVA which helps the tutorial attendees in transferring the subject matter to their own data and application area. In the course of the tutorial, the attendees will become acquainted with techniques from statistics and knowledge discovery, which proved to be particularly useful for a specific IVA application. The tutorial further comprises an overview of off-the-shelf IVA solutions, which may be be particularly interesting for visualization practitioners. It is concluded by a summary of the gained knowledge and a discussion of open problems in IVA of scientific data.",
    images = "images/",
    thumbnails = "images/iva_scientificdata_proposal_2013_Image.png",
    location = "Atlanta (GA), USA",
    pres = "pdfs/iva_scientificdata_proposal_2013.pdf"
    }
    [DOI] [Bibtex]
    @INCOLLECTION {Turkay13Hypothesis,
    author = "Cagatay Turkay and Arvid Lundervold and Astri Johansen Lundervold and Helwig Hauser",
    title = "Hypothesis Generation by Interactive Visual Exploration of Heterogeneous Medical Data",
    booktitle = "Human-Computer Interaction and Knowledge Discovery in Complex, Unstructured, Big Data",
    publisher = "Springer Berlin Heidelberg",
    year = "2013",
    editor = "Holzinger, Andreas and Pasi, Gabriella",
    volume = "7947",
    series = "Lecture Notes in Computer Science",
    pages = "1--12",
    images = "images/Turkay13Hypothesis_01.png",
    thumbnails = "images/Turkay13Hypothesis_01.png",
    isbn = "978-3-642-39145-3",
    doi = "10.1007/978-3-642-39146-0_1",
    url = "http://dx.doi.org/10.1007/978-3-642-39146-0_1",
    keywords = "interactive visual analysis; high dimensional medical data",
    pres = "pdfs/Turkay13Hypothesis.pdf"
    }
    [DOI] [Bibtex]
    @ARTICLE {Hauser13GuestEditors,
    author = "Helwig Hauser and Stephen Kobourov and Huamin Qu",
    title = "Guest Editors' Introduction: Special Section on the IEEE Pacific Visualization Symposium 2012",
    journal = "IEEE Transactions on Visualization and Computer Graphics",
    year = "2013",
    volume = "19",
    number = "6",
    pages = "898-899",
    images = "images/Gno_thumb.png",
    thumbnails = "images/no_thumb.png",
    issn = "1077-2626",
    url = "http://doi.ieeecomputersociety.org/10.1109/TVCG.2013.70",
    doi = "http://doi.ieeecomputersociety.org/10.1109/TVCG.2013.70",
    publisher = "IEEE Computer Society",
    address = "Los Alamitos, CA, USA"
    }
    [PDF] [Bibtex]
    @MISC {Hauser2013VISU,
    author = "Helwig Hauser",
    title = "Interactive Visual Analysis of Scientific Data",
    howpublished = "Keynote talk at VISU 2013 in Paris, France",
    month = "November",
    year = "2013",
    abstract = "Keynote talk at VISU 2013 in Paris, France",
    pdf = "pdfs/2013-11-06-Paris-Visu2013-SciDataIVA-print2up-web.pdf",
    images = "images/2013-11-06-Paris-Visu2013-SciDataIVA-print2up-web_Image_0003.jpg, images/2013-11-06-Paris-Visu2013-SciDataIVA-print2up-web_Image_0006.jpg, images/2013-11-06-Paris-Visu2013-SciDataIVA-print2up-web_Image_0002.jpg, images/2013-11-06-Paris-Visu2013-SciDataIVA-print2up-web_Image_0002(2).jpg, images/2013-11-06-Paris-Visu2013-SciDataIVA-print2up-web_Image_0010.jpg, images/2013-11-06-Paris-Visu2013-SciDataIVA-print2up-web_Image_0008.jpg, images/2013-11-06-Paris-Visu2013-SciDataIVA-print2up-web_Image_0009.jpg, images/2013-11-06-Paris-Visu2013-SciDataIVA-print2up-web_Image_0002(3).jpg, images/2013-11-06-Paris-Visu2013-SciDataIVA-print2up-web_Image_0002(4).jpg, images/2013-11-06-Paris-Visu2013-SciDataIVA-print2up-web_Image_0006(2).jpg",
    thumbnails = "images/2013-11-06-Paris-Visu2013-SciDataIVA-print2up-web_Image_0003.jpg",
    location = "Paris, France"
    }
    [PDF] [DOI] [Bibtex]
    @ARTICLE {Kehrer13VisualizationAnd,
    author = "Johannes Kehrer and Helwig Hauser",
    title = "Visualization and Visual Analysis of Multi-faceted Scientific Data: a Survey",
    journal = "IEEE Transactions on Visualization and Computer Graphics",
    year = "2013",
    volume = "19",
    number = "3",
    pages = "495-513",
    abstract = "Visualization and visual analysis play important roles in exploring, analyzing and presenting scientific data. In many disciplines, data and model scenarios are becoming multi-faceted: data are often spatio-temporal and multi-variate; they stem from different data sources (multi-modal data), from multiple simulation runs (multi-run/ensemble data), or from multi-physics simulations of interacting phenomena (multi-model data resulting from coupled simulation models). Also, data can be of different dimensionality or structured on various types of grids that need to be related or fused in the visualization. This heterogeneity of data characteristics presents new opportunities as well as technical challenges for visualization research. Visualization and interaction techniques are thus often combined with computational analysis. In this survey, we study existing methods for visualization and interactive visual analysis of multi-faceted scientific data. Based on a thorough literature review, a categorization of approaches is proposed. We cover a wide range of fields and discuss to which degree the different challenges are matched with existing solutions for visualization and visual analysis. This leads to conclusions with respect to promising research directions, for instance, to pursue new solutions for multi-run and multi-model data as well as techniques that support a multitude of facets.",
    pdf = "pdfs/Kehrer13VisualizationAnd.pdf",
    images = "images/Kehrer13VisualizationAnd01.png",
    thumbnails = "images/Kehrer13VisualizationAnd01_thumb.png",
    issn = "1077-2626",
    doi = "http://doi.ieeecomputersociety.org/10.1109/TVCG.2012.110",
    publisher = "IEEE Computer Society",
    address = "Los Alamitos, CA, USA"
    }
    [PDF] [Bibtex]
    @MISC {Hauser2013IHCI,
    author = "Helwig Hauser",
    title = "Integrating Interactive and Computational Analysis in Visual Analytics",
    howpublished = "Keynote talk at IHCI 2013 in Prague, Czech Republic.",
    month = "July",
    year = "2013",
    abstract = "Keynote talk at IHCI 2013 in Prague, Czech Republic.",
    pdf = "pdfs/2013-07-22-Prague-IHCI-Keynote-IVA-print2up.pdf",
    images = "images/2013-07-22-Prague-IHCI-Keynote-IVA-print2up_Image_0001(2).jpg, images/2013-07-22-Prague-IHCI-Keynote-IVA-print2up_Image_0001(3).jpg, images/2013-07-22-Prague--IHCI-Keynote-IVA-print2up_Image_0001(4).jpg, images/2013-07-22-Prague-IHCI-Keynote-IVA-print2up_Image_0001(5).jpg, images/2013-07-22-Prague-IHCI-Keynote-IVA-print2up_Image_0001(6).jpg, images/2013-07-22-Prague-IHCI-Keynote-IVA-print2up_Image_0003.jpg",
    thumbnails = "images/2013-07-22-Prague-IHCI-Keynote-IVA-print2up_Image_0001(2).jpg"
    }

2012

    [PDF] [DOI] [VID] [Bibtex]
    @ARTICLE {Turkay12Representative,
    author = "Cagatay Turkay and Arvid Lundervold and Astri Johansen Lundervold and Helwig Hauser",
    title = "Representative Factor Generation for the Interactive Visual Analysis of High-Dimensional Data",
    journal = "Visualization and Computer Graphics, IEEE Transactions on",
    year = "2012",
    volume = "18",
    number = "12",
    pages = "2621--2630",
    month = "December",
    abstract = "Datasets with a large number of dimensions per data item (hundreds or more) are challenging both for computational and visual analysis. Moreover, these dimensions have different characteristics and relations that result in sub-groups and/or hierarchies over the set of dimensions. Such structures lead to heterogeneity within the dimensions. Although the consideration of these structures is crucial for the analysis, most of the available analysis methods discard the heterogeneous relations among the dimensions. In this paper, we introduce the construction and utilization of representative factors for the interactive visual analysis of structures in high-dimensional datasets. First, we present a selection of methods to investigate the sub-groups in the dimension set and associate representative factors with those groups of dimensions. Second, we introduce how these factors are included in the interactive visual analysis cycle together with the original dimensions. We then provide the steps of an analytical procedure that iteratively analyzes the datasets through the use of representative factors. We discuss how our methods improve the reliability and interpretability of the analysis process by enabling more informed selections of computational tools. Finally, we demonstrate our techniques on the analysis of brain imaging study results that are performed over a large group of subjects.",
    pdf = "pdfs/Turkay12Representative.pdf",
    vid = "vids/Turkay12Representative.avi",
    images = "images/Turkay12Representative01.png, images/Turkay12Representative02.png",
    thumbnails = "images/Turkay12Representative01_thumb.png, images/Turkay12Representative02_thumb.png",
    event = "IEEE Information Visualization Conference 2012",
    location = "Seattle, WA, USA",
    doi = "10.1109/TVCG.2012.256",
    issn = "1077-2626"
    }
    [PDF] [DOI] [Bibtex]
    @INPROCEEDINGS {Lidal12Geological,
    author = "Endre M. Lidal and Helwig Hauser and Ivan Viola ",
    title = "Geological Storytelling - Graphically Exploring and Communicating Geological Sketches",
    booktitle = "Proceedings of Sketch-Based Interfaces and Modeling (SBIM 2012)",
    year = "2012",
    pages = "11--20",
    abstract = "Developing structural geological models from exploratory subsea imaging is difficult and an ill-posed process. Therefore, in practice several experts generate a larger number of geological interpretations. This leads to the situation that a number of geological sketches are prepared and examined for the next steps in the oil and gas exploration pipeline. In this paper, we present Geological Storytelling, a novel graphical approach for performing rapid and expressive geomodeling of a multitude of model variations. The solution builds on a flip-over metaphor for sketching the individual steps in a story that externalizes the mental steps the modeler performs when developing the model. The stories, through the discrete story steps, are then visualized in a Story Tree for easy access and management. This tree also provides the interface for individual story playback and examination, or comparative visualization of several stories. With our approach, the experts can rapidly sketch geological stories that both visualize the proposed model of today's geology and visualize how the expert derived this model. Presenting the model as a visual story helps the peers to evaluate the geological soundness of the model. We have developed geological storytelling in collaboration with domain experts that work with such challenges on a daily basis. Our focus of this work has been on models derived from single seismic slices. We have implemented a prototype of Geological Storytelling to demonstrate our concept and to get domain expert feedback.",
    pdf = "pdfs/Lidal12Geological.pdf",
    images = "images/Lidal12Geological01.png, images/Lidal12Geological02.png",
    thumbnails = "images/Lidal12Geological01_thumb.png, images/Lidal12Geological02_thumb.png",
    url = "http://diglib.eg.org/EG/DL/WS/SBM/SBM12/011-020.pdf",
    doi = "10.2312/SBM/SBM12/011-020",
    project = "geoillustrator"
    }
    [PDF] [VID] [Bibtex]
    @INPROCEEDINGS {Solteszova12Stylized,
    author = "Veronika \v{S}olt{\'e}szov{\'a} and Ruben Patel and Helwig Hauser and Ivanko Viola",
    title = "Stylized Volume Visualization of Streamed Sonar Data",
    booktitle = "Proceedings of Spring Conference on Computer Graphics (SCCG 2012)",
    year = "2012",
    pages = "13--20",
    month = "May",
    abstract = "Current visualization technology implemented in the software for 2D sonars used in marine research is limited to slicing whilst volume visualization is only possible as post processing. We designed and implemented a system which allows for instantaneous volume visualization of streamed scans from 2D sonars without prior resampling to a voxel grid. The volume is formed by a set of most recent scans which are being stored. We transform each scan using its associated transformations to the view-space and slice their bounding box by view-aligned planes. Each slicing plane is reconstructed from the underlying scans and directly used for slice-based volume rendering. We integrated a low frequency illumination model which enhances the depth perception of noisy acoustic measurements. While we visualize the 2D data and time as 3D volumes, the temporal dimension is not intuitively communicated. Therefore, we introduce a concept of temporal outlines. Our system is a result of an interdisciplinary collaboration between visualization and marine scientists. The application of our system was evaluated by independent domain experts who were not involved in the design process in order to determine real life applicability.",
    pdf = "pdfs/Solteszova12Stylized.pdf",
    vid = "vids/Solteszova12Stylized.mp4",
    images = "images/Solteszova12Stylized01.png, images/Solteszova12Stylized02.png, images/Solteszova12Stylized03.png",
    thumbnails = "images/Solteszova12Stylized01_thumb.png, images/Solteszova12Stylized02_thumb.png, images/Solteszova12Stylized03_thumb.png",
    note = "Second best paper and second best presentation awards",
    location = "Smolenice castle, Slovakia",
    project = "illustrasound,medviz,illvis"
    }
    [DOI] [Bibtex]
    @ARTICLE {Doleish12Interactive,
    author = "Helmut Doleisch and Helwig Hauser",
    title = "Interactive Visual Exploration and Analysis of Multivariate Simulation Data",
    journal = "Computing in Science Engineering",
    year = "2012",
    volume = "14",
    number = "2",
    pages = "70--77",
    month = "March-April",
    abstract = "The interactive visual exploration of large and complex simulation datasets has become an important methodology that improves data analysis for scientists and professional practitioners.",
    images = "images/Doleish12Interactive01.png, images/Doleish12Interactive02.png",
    thumbnails = "images/Doleish12Interactive01_thumb.png, images/Doleish12Interactive02_thumb.png",
    keywords = "complex simulation datasets;data analysis;important methodology; interactive visual exploration;multivariate simulation data;data analysis; data visualisation;geophysics computing;",
    doi = "10.1109/MCSE.2012.27",
    issn = "1521-9615",
    url = "http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6159200"
    }
    [PDF] [DOI] [Bibtex]
    @INPROCEEDINGS {Brambilla12Illustrative,
    author = "Andrea Brambilla and Robert Carnecky and Ronald Peikert and Ivan Viola and Helwig Hauser",
    title = "Illustrative Flow Visualization: State of the Art, Trends and Challenges",
    booktitle = "EuroGraphics 2012 State of the Art Reports (STARs)",
    year = "2012",
    pages = "75--94",
    abstract = "Flow visualization is a well established branch of scientific visualization and it currently represents an invaluable resource to many fields, like automotive design, meteorology and medical imaging. Thanks to the capabilities of modern hardware, flow datasets are increasing in size and complexity, and traditional flow visualization techniques need to be updated and improved in order to deal with the upcoming challenges. A fairly recent trend to enhance the expressiveness of scientific visualization is to produce depictions of physical phenomena taking inspiration from traditional handcrafted illustrations: this approach is known as illustrative visualization, and it is getting a foothold in flow visualization as well. In this state of the art report we give an overview of the existing illustrative techniques for flow visualization, we highlight which problems have been solved and which issues still need further investigation, and, finally, we provide remarks and insights on the current trends in illustrative flow visualization.",
    pdf = "pdfs/Brambilla12Illustrative.pdf",
    images = "images/Brambilla12Illustrative.png",
    thumbnails = "images/Brambilla12Illustrative_thumb.png",
    url = "http://diglib.eg.org/EG/DL/conf/EG2012/stars/075-094.pdf",
    doi = "10.2312/conf/EG2012/stars/075-094",
    location = "Cagliari, Italy",
    pres = "pdfs/Brambilla12Illustrative.pptx",
    project = "semseg"
    }
    [PDF] [DOI] [Bibtex]
    @INPROCEEDINGS {Pobitzer12Filtering,
    author = "Armin Pobitzer and Ronald Peikert and Raphael Fuchs and Holger Theisel and Helwig Hauser",
    title = "Filtering of FTLE for Visualizing Spatial Separation in Unsteady 3D Flow",
    booktitle = "Topological Methods in Data Analysis and Visualization II",
    year = "2012",
    editor = "R. Peikert and H. Hauser and H. Carr and R. Fuchs",
    pages = "237--253",
    publisher = "Springer",
    abstract = "Texture mapping is a common method for combining surface geometry with image data, with the resulting photorealistic 3D models being suitable not only for visualisation purposes but also for interpretation and spatial measurement, in many application fields, such as cultural heritage and the earth sciences. When acquiring images for creation of photorealistic models, it is usual to collect more data than is finally necessary for the texturing process. Images may be collected from multiple locations, sometimes with different cameras or lens configurations and large amounts of overlap may exist. Consequently, much redundancy may be present, requiring sorting to choose the most suitable images to texture the model triangles. This paper presents a framework for visualization and analysis of the geometric relations between triangles of the terrain model and covering image sets. The application provides decision support for selection of an image subset optimized for 3D model texturing purposes, for non-specialists. It aims to improve the communication of geometrical dependencies between model triangles and the available digital images, through the use of static and interactive information visualisation methods. The tool was used for computer-aided selection of image subsets optimized for texturing of 3D geological outcrop models. The resulting textured models were of high quality and with a minimum of missing texture, and the time spent in time-consuming reprocessing was reduced. Anecdotal evidence indicated that an increased user confidence in the final textured model quality and completeness makes the framework highly beneficial. ",
    pdf = "pdfs/Pobitzer12Filtering.pdf",
    images = "images/Pobitzer12Filtering01.png, images/Pobitzer12Filtering02.png",
    thumbnails = "images/Pobitzer12Filtering01_thumb.png, images/Pobitzer12Filtering02_thumb.png",
    doi = "http://dx.doi.org/10.1007/978-3-642-23175-9_16",
    url = "http://dx.doi.org/10.1007/978-3-642-23175-9_16",
    project = "semseg"
    }
    [PDF] [Bibtex]
    @MISC {Brambilla12Geilo,
    author = "Andrea Brambilla and Armin Pobitzer and Helwig Hauser",
    title = "Flow Visualization and the SemSeg project",
    howpublished = "Poster presented at the Sintef winter school 2012",
    month = "January",
    year = "2012",
    pdf = "pdfs/Brambilla12Geilo.pdf",
    images = "images/Brambilla12Geilo01.png",
    thumbnails = "images/Brambilla12Geilo01_thumb.png",
    location = "Geilo, Norway",
    url = "http://www.sintef.no/Projectweb/eVITA/Winter-Schools/2012/"
    }
    [PDF] [Bibtex]
    @INPROCEEDINGS {Turkay2012DualDNA,
    author = "Cagatay Turkay and Julius Parulek and Helwig Hauser",
    title = "Dual analysis of DNA microarrays",
    booktitle = "Proceedings of the 12th International Conference on Knowledge Management and Knowledge Technologies",
    year = "2012",
    series = "i-KNOW '12",
    pages = "26:1--26:8",
    abstract = "Microarray data represents the expression levels of genes for different samples and for different conditions. It has been a central topic in bioinformatics research for a long time already. Researchers try to discover groups of genes that are responsible for specific biological processes. Statistical analysis tools and visualizations have been widely used in the analysis of microarray data. Researchers try to build hypotheses on both the genes and the samples. Therefore, such analyses require the joint exploration of the genes and the samples. However, current methods in interactive visual analysis fail to provide the necessary mechanisms for this joint analysis. In this paper, we propose an interactive visual analysis framework that enables the dual analysis of the samples and the genes through the use of integrated statistical tools. We introduce a set of specialized views and a detailed analysis procedure to describe the utilization of our framework.",
    pdf = "pdfs/Turkay2012DualDNA.pdf",
    images = "images/Turkay2012DualDNA01.png, images/Turkay2012DualDNA02.png",
    thumbnails = "images/Turkay2012DualDNA01_thumb.png, images/Turkay2012DualDNA02_thumb.png",
    location = "Graz, Austria",
    articleno = "26",
    numpages = "8",
    keywords = "interactive visual analysis, microarray data, visual analytics"
    }
    [DOI] [Bibtex]
    @INPROCEEDINGS {Konyha12Interactive,
    author = "Zoltan Konyha and Alan Lez and Kresimir Matkovic and Mario Jelovic and Helwig Hauser",
    title = "Interactive visual analysis of families of curves using data aggregation and derivation",
    booktitle = "Proceedings of the 12th International Conference on Knowledge Management and Knowledge Technologies",
    year = "2012",
    series = "i-KNOW '12",
    pages = "24:1--24:8",
    address = "New York, NY, USA",
    publisher = "ACM",
    abstract = "Time-series data are regularly collected and analyzed in a wide range of domains. Multiple simulation runs or multiple measurements of the same physical quantity result in ensembles of curves which we call families of curves. The analysis of time-series data is extensively studied in mathematics, statistics, and visualization; but less research is focused on the analysis of families of curves. Interactive visual analysis in combination with a complex data model, which supports families of curves in addition to scalar parameters, represents a premium methodology for such an analysis. In this paper we describe the three levels of complexity of interactive visual analysis we identified during several case studies. The first two levels represent the current state of the art. The newly introduced third level makes extracting deeply hidden implicit information from complex data sets possible by adding data derivation and advanced interaction. We seamlessly integrate data derivation and advanced interaction into the visual exploration to facilitate an in-depth interactive visual analysis of families of curves. We illustrate the proposed approach with typical analysis patterns identified in two case studies from automotive industry.",
    images = "images/Konyha12Interactive01.png, images/Konyha12Interactive02.png",
    thumbnails = "images/Konyha12Interactive01_thumb.png, images/Konyha12Interactive02_thumb.png",
    isbn = "978-1-4503-1242-4",
    location = "Graz, Austria",
    articleno = "24",
    numpages = "8",
    url = "http://doi.acm.org/10.1145/2362456.2362487",
    doi = "10.1145/2362456.2362487",
    acmid = "2362487",
    keywords = "attribute derivation, families of curves, interactive visual analysis, knowledge generations"
    }
    [Bibtex]
    @MISC {Hauser12Dagstuhl,
    author = "Helwig Hauser",
    title = "Automated Methods in Information Visualization",
    howpublished = "Invited talk at the Dagstuhl seminar 12081",
    month = "February",
    year = "2012",
    abstract = "Visualization and Machine Learning have related goals in terms of helping analysts to understand characteristic aspects of data. While visualization aims at involving the user through interactive depictions of data, machine learning is generally represented by automatic methods that yield optimal results with respect to certain initially specified tasks. Not at the least within the research direction of visual analytics it seems promising to think about opportunities to integrate both methodologies in order to exploit the strengths of both sides. Up to now, examples of integration very often encompass the visualization of results from automatic methods as well as attempts to make originally automated methods partially interactive. A vision for the future would be to integrate interactive and automatic methods in order to solve problems. A possible realization could be an iterative process where the one or other approach is chosen on demand at each step. ",
    images = "images/Hauser12Dagstuhl.png",
    thumbnails = "images/Hauser12Dagstuhl_thumb.png",
    location = "Wadern, Germany",
    url = "http://www.dagstuhl.de/en/program/calendar/semhp/?semnr=12081",
    pres = "pdfs/Hauser12Dagstuhl-pres.pdf"
    }
    [Bibtex]
    @MISC {Hauser12TAVA,
    author = "Helwig Hauser",
    title = "Compromises and Added Value in Visual Analytics",
    howpublished = "Keynote talk at the TAVA 2012 workshop",
    month = "September",
    year = "2012",
    images = "images/Hauser12TAVA.png",
    thumbnails = "images/Hauser12TAVA_thumb.png",
    location = "Graz, Austria",
    pres = "pdfs/Hauser12TAVA-slides.pdf"
    }
    [PDF] [DOI] [Bibtex]
    @ARTICLE {Ma12ScientificStorytelling,
    author = "Kwan-Liu Ma and I. Liao and J. Frazier and H. Hauser and H.-N. Kostis",
    title = "Scientific Storytelling Using Visualization",
    journal = "Computer Graphics and Applications, IEEE",
    year = "2012",
    volume = "32",
    number = "1",
    pages = "12 -19",
    month = "Jan.--Feb.",
    abstract = "Scientists frequently tell stories using visualizations of scientific data, in the process of disseminating findings to peers and the general public. However, techniques and methods for effective scientific storytelling have received little attention so far. This article explores how literary and theatrical narrative conventions can inform the design and presentation of visualizations, and discusses the challenges of adapting scientific visualizations for broader audiences. It also summarizes recent workshops' findings on the role of storytelling in visualizations, and presents several examples of successful scientific-storytelling production teams. The conclusion is that scientific storytelling deserves greater support and recognition by the visualization community.",
    pdf = "pdfs/Ma12ScientificStorytelling.pdf",
    images = "images/Ma12ScientificStorytelling01.jpg, images/Ma12ScientificStorytelling02.jpg , images/Ma12ScientificStorytelling03.jpg, ../../../_images/CGA--2012-01--Cover.png",
    thumbnails = "images/Ma12ScientificStorytelling01_thumb.jpg, images/Ma12ScientificStorytelling02_thumb.jpg , images/Ma12ScientificStorytelling03_thumb.jpg, ../../../_images/CGA--2012-01--Cover_thumb.png",
    keywords = "literary narrative convention;scientific data visualization; scientific storytelling;theatrical narrative convention;data visualisation; natural sciences computing;",
    doi = "10.1109/MCG.2012.24",
    url = "http://dx.doi.org/10.1109/MCG.2012.24",
    issn = "0272-1716"
    }
    [Bibtex]
    @MISC {Hauser12EuroVA,
    author = "Helwig Hauser",
    title = "The Iterative Process of Interactive Visual Analysis",
    howpublished = "Keynote talk at the EuroVA 2012 workshop",
    month = "June",
    year = "2012",
    abstract = "One central characteristic of our information age is that increasingly often we should exploit the wealth of available data for the sake of learning, decision making, as well as other tasks. A promising approach - not at the least also targeted by visual analytics - is to integrate the strengths of computers (fast computation, efficient handling of large datasets, comparably low costs, etc.) with the strengths of the users (perceptual capabilities, considering domain knowledge, detecting the unexpected, etc.). In this talk, we look at one possible solution, i.e., the concept of interactive visual analysis, and describe it as an iterative process, enabling the integration of computational and interactive means for data exploration and analysis. We consider a data scenario that opposes dependent and independent data dimensions (like in a table), general enough to match many different application cases. We focus on the case of multivariate data, but also address the case of high-dimensional data and opportunities for exploring and analyzing such data. After all, we think of interactive visual analysis as an iterative process, where each step is performed on the basis of a toolbox with computational and interactive visual solutions.",
    images = "images/Hauser12EuroVA.jpg",
    thumbnails = "images/Hauser12EuroVA_thumb.jpg",
    location = "Vienna, Austria",
    url = "http://www.eurova.org/previous-events/eurova-2012",
    pres = "pdfs/Hauser12EuroVA-pres.pdf"
    }
    [Bibtex]
    @BOOK {peikert12topological,
    author = "Ronald Peikert and Helwig Hauser and Hamish Carr and Raphael Fuchs",
    title = "Topological Methods in Data Analysis and Visualization II: Theory, Algorithms, and Applications",
    publisher = "Springer",
    year = "2012",
    series = "Mathematics and Visualization",
    abstract = "When scientists analyze datasets in a search for underlying phenomena, patterns or causal factors, their first step is often an automatic or semi-automatic search for structures in the data. Of these feature-extraction methods, topological ones stand out due to their solid mathematical foundation. Topologically defined structures -as found in scalar, vector and tensor fields- have proven their merit in a wide range of scientific domains, and scientists have found them to be revealing in subjects such as physics, engineering, and medicine. Full of state-of-the-art research and contemporary hot topics in the subject, this volume is a selection of peer-reviewed papers originally presented at the fourth Workshop on Topology-Based Methods in Data Analysis and Visualization, TopoInVis 2011, held in Zurich, Switzerland. The workshop brought together many of the leading lights in the field for a mixture of formal presentations and discussion. One topic currently generating a great deal of interest, and explored in several chapters here, is the search for topological structures in time-dependent flows, and their relationship with Lagrangian coherent structures. Contributors also focus on discrete topologies of scalar and vector fields, and on persistence-based simplification, among other issues of note. The new research results included in this volume relate to all three key areas in data analysis-theory, algorithms and applications.",
    images = "images/peikert12topological.png",
    thumbnails = "images/peikert12topological_thumb.png",
    isbn = "978-3-642-23175-9",
    url = "http://www.springer.com/mathematics/computational+science+%26+engineering/book/978-3-642-23174-2"
    }
    [Bibtex]
    @MISC {Hauser12PaVis,
    author = "Helwig Hauser and Stephen G. Kobourov and Huamin Qu",
    title = "Proceedings of the 2012 IEEE Pacific Visualization Symposium",
    howpublished = "Conference proceedings",
    month = "February-March",
    year = "2012",
    images = "images/Helwig12PaVis01.png",
    thumbnails = "images/Helwig12PaVis01.png",
    location = "Songdo, Korea",
    url = "http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=6178307"
    }
    [Bibtex]
    @MISC {Hauser12VisTutorial,
    author = "Steffen Oeltze and Helmut Doleisch and Helwig Hauser and Gunther Weber",
    title = "Interactive Visual Analysis of Scientific Data",
    howpublished = "Tutorial at the IEEE VisWeek 2012",
    month = "October",
    year = "2012",
    abstract = "In a growing number of application areas, a subject or phenomenon is investigated by means of multiple datasets being acquired over time (spatiotemporal), comprising several attributes per data point (multi-variate), stemming from different data sources (multi-modal) or multiple simulation runs (multirun/ensemble). Interactive visual analysis (IVA) comprises concepts and techniques for a user-guided knowledge discovery in such complex data. Through a tight feedback loop of computation, visualization and user interaction, it provides new insight into the data and serves as a vehicle for hypotheses generation or validation. It is often implemented via a multiple coordinated view framework where each view is equipped with interactive drill-down operations for focusing on data features. Two classes of views are integrated: physical views show information in the context of the spatiotemporal observation space while attribute views show relationships between multiple data attributes. The user may drill-down the data by selecting interesting regions of the observation space or attribute ranges leading to a consistent highlighting of this selection in all other views (brushing-and-linking). In this tutorial, we discuss examples for successful applications of IVA to scientific data from various fields: automotive engineering, climate research, biology, and medicine. We base our discussions on a theoretical foundation of IVA which helps the tutorial attendees in transferring the subject matter to their own data and application area. This universally applicable knowledge is complemented in a tutorial part on IVA of very large data which accounts for the tera- and petabytes being generated by simulations and experiments in many areas of science, e.g., physics, astronomy, and climate research. The tutorial further provides an overview of off-the-shelf IVA solutions. It is concluded by a summary of the gained knowledge and a discussion of open problems in IVA of scientific data.",
    images = "images/Hauser12VisTutorial.png",
    thumbnails = "images/Hauser12VisTutorial_thumb.png",
    location = "Seattle (WA), USA",
    url = "http://visweek.org/visweek/2012/tutorial/interactive-visual-analysis-scientific-data",
    pres = "pdfs/Hauser12VisTutorialPres01.pdf"
    }
    [PDF] [Bibtex]
    @INPROCEEDINGS {Lidal12Design,
    author = "Endre M. Lidal and Helwig Hauser and Ivan Viola",
    title = "Design Principles for Cutaway Visualization of Geological Models",
    booktitle = "Proceedings of Spring Conference on Computer Graphics (SCCG 2012)",
    year = "2012",
    pages = "53--60",
    month = "May",
    abstract = "In this paper, we present design principles for cutaway visualizations that emphasize shape and depth communication of the focus features and their relation to the context. First, to eliminate cutaway-flatness we argue that the cutaway axis should have an angular offset from the view direction. Second, we recommend creating a box-shaped cutaway. Such a simple cutaway shape allows for easier context extrapolation in the cutaway volume. Third, to improve the relationship between the focus features and the context, we propose to selectively align the cutaway shape to familiar structures in the context. Fourth, we emphasize that the illumination model should effectively communicate the shape and spatial ordering inside the cutaway, through shadowing as well as contouring and other stylized shading models. Finally, we recommend relaxing the view-dependency constraint of the cutaway to improve the depth perception through the motion parallax. We have identified these design principles while developing interactive cutaway visualizations of 3D geological models, inspired by geological illustrations and discussions with the domain illustrators and experts.",
    pdf = "pdfs/Lidal12Design.pdf",
    images = "images/Lidal12Design01.jpg, images/Lidal12Design02.jpg",
    thumbnails = "images/Lidal12Design01_thumb.jpg, images/Lidal12Design02_thumb.jpg",
    location = "Smolenice castle, Slovakia",
    project = "geoillustrator"
    }
    [PDF] [Bibtex]
    @ARTICLE {Brambilla12AHierarchical,
    author = "Andrea Brambilla and Ivan Viola and Helwig Hauser",
    title = "A Hierarchical Splitting Scheme to Reveal Insight into Highly Self-Occluded Integral Surfaces",
    journal = "Journal of WSCG",
    year = "2012",
    volume = "20",
    number = "1",
    pages = "57--64",
    month = "July",
    abstract = "In flow visualization, integral surfaces are of particular interest for their ability to describe trajectories of massless particles. In areas of swirling motion, integral surfaces can become very complex and difficult to understand. Taking inspiration from traditional illustration techniques, such as cut-aways and exploded views, we propose a surface analysis tool based on surface splitting and focus+context visualization. Our surface splitting scheme is hierarchical and at every level of the hierarchy the best cut is chosen according to a surface complexity metric. In order to make the interpretation of the resulting pieces straightforward, cuts are always made along isocurves of specific flow attributes. Moreover, a degree of interest can be specified, so that the splitting procedure attempts to unveil the occluded interesting areas. Through practical examples, we show that our approach is able to overcome the lack of understanding originating from structural occlusion.",
    pdf = "pdfs/Brambilla12AHierarchical.pdf",
    images = "images/Brambilla12AHierarchical01.png, images/Brambilla12AHierarchical02.png, images/Brambilla12AHierarchical03.png",
    thumbnails = "images/Brambilla12AHierarchical01_thumb.png, images/Brambilla12AHierarchical02_thumb.png, images/Brambilla12AHierarchical03_thumb.png",
    issn = "1213-6972",
    publisher = "Union Agency",
    url = "http://wscg.zcu.cz/JWSCG/",
    event = "WSCG 2012 - 20th International Conference on Computer Graphics, Visualization and Computer Vision",
    location = "Pilsen, Czech Republic",
    pres = "pdfs/Brambilla12AHierarchical.pptx",
    project = "semseg"
    }
    [Bibtex]
    @MISC {Pobitzer12PacificVisTutorial,
    author = "Helwig Hauser and Alexander Kuhn and Armin Pobitzer and Maik Schulze",
    title = "Time-Dependent Flow Visualization",
    howpublished = "Tutorial at 5th IEEE PacificVis Symposium",
    month = "February",
    year = "2012",
    abstract = "Vector fields are a common representation of many kinds of dynamic phenomena in a large variety of application fields. A particularly interesting class of vector fields represent time-dependent flows, i.e., flows where the vectors change over time themselves. A lot of good and relevant research work has been done on the question of how to visualize such unsteady vector fields and an overview is presented in this tutorial. In particularly, we emphasize Lagrangian methods, space-time domain approaches, and interactive visual analysis as three interesting and promising types of methodology. The tutorial is also introduced with some general remarks, in particular also on the question of why it often is not straight forward to extend methods that originally were developed for steady flows to the domain of unsteady flows. A number of examples illustrate the overview.",
    images = "images/Pobitzer12PacificVisTutorial.png",
    thumbnails = "images/Pobitzer12PacificVisTutorial_thumb.png",
    location = "Songdo, South Korea",
    url = "http://www.semseg.eu/download/2012-02-28--TimeDepFlowVizTutorial--materials/"
    }
    [PDF] [Bibtex]
    @INPROCEEDINGS {Pobitzer12AStatistics,
    author = "Armin Pobitzer and Alan Lez and Kresimir Matkovic and Helwig Hauser",
    title = "A Statistics-based Dimension Reduction of the Space of Path Line Attributes for Interactive Visual Flow Analysis",
    booktitle = "Proceedings of the IEEE Pacific Visualization Symposium (PacificVis 2012)",
    year = "2012",
    pages = "113--120",
    month = "March",
    abstract = "Recent work has shown the great potential of interactive flow analysis by the analysis of path lines. The choice of suitable attributes, describing the path lines, is, however, still an open question. This paper addresses this question performing a statistical analysis of the path line attribute space. In this way we are able to balance the usage of computing power and storage with the necessity to not loose relevant information. We demonstrate how a carefully chosen attribute set can improve the benefits of state-of-the art interactive flow analysis. The results obtained are compared to previously published work.",
    pdf = "pdfs/Pobitzer12AStatistics.pdf",
    images = "images/Pobitzer12AStatistics.png",
    thumbnails = "images/Pobitzer12AStatistics_thumb.png",
    location = "Songdo, Korea"
    }
    [Bibtex]
    @MISC {Hauser12VCF,
    author = "Helwig Hauser",
    title = "The Iterative Process of Interactive Visual Analysis",
    howpublished = "Talk in the Visual Computing Forum (VCF) at UiB",
    month = "September",
    year = "2012",
    abstract = "One central characteristic of our information age is that increasingly often we should exploit the wealth of available data for the sake of learning, decision making, as well as other tasks. A promising approach - not at the least also targeted by visual analytics - is to integrate the strengths of computers (fast computation, efficient handling of large datasets, comparably low costs, etc.) with the strengths of the users (perceptual capabilities, considering domain knowledge, detecting the unexpected, etc.). In this talk, we look at one possible solution, i.e., the concept of interactive visual analysis, and describe it as an iterative process, enabling the integration of computational and interactive means for data exploration and analysis. We consider a data scenario that opposes dependent and independent data dimensions (like in a table), general enough to match many different application cases. We focus on the case of multivariate data, but also address the case of high-dimensional data and opportunities for exploring and analyzing such data. After all, we think of interactive visual analysis as an iterative process, where each step is performed on the basis of a toolbox with computational and interactive visual solutions.",
    images = "images/Hauser12VCF.jpg",
    thumbnails = "images/Hauser12VCF_thumb.jpg",
    location = "Bergen, Norway",
    url = "http://www.ii.uib.no/vis/vcf/"
    }
    [Bibtex]
    @MISC {Hauser12SemSegWorkshop,
    author = "Helwig Hauser and Kresimir Matkovic",
    title = "Interactive Visual Analysis of Time-Dependent Flows",
    howpublished = "Presentation at the 3rd SemSeg User Forum Workshop",
    month = "February",
    year = "2012",
    images = "images/Hauser12SemSegWorkshop.png",
    thumbnails = "images/Hauser12SemSegWorkshop_thumb.png",
    location = "Magdeburg, Germany",
    url = "http://vc.cs.ovgu.de/index.php?article_id=232",
    pres = "pdfs/Hauser12SemSegWorkshop-pres.pdf",
    project = "semseg"
    }

2011

    [Bibtex]
    @INCOLLECTION {oye11illustrativeCouinaud,
    author = "Ola Kristoffer {\O }ye and Dag Magne Ulvang and Odd Helge Gilja and Helwig Hauser and Ivan Viola",
    title = "Illustrative Couinaud Segmentation for Ultrasound Liver Examinations",
    booktitle = "Smart Graphics",
    publisher = "Springer Berlin / Heidelberg",
    year = "2011",
    volume = "6815",
    series = "Lecture Notes in Computer Science",
    pages = "60--77",
    abstract = "Couinaud segmentation is a widely used liver partitioning scheme for describing the spatial relation between diagnostically relevant anatomical and pathological features in the liver. In this paper, we propose a new methodologyfor effectively conveying these spatial relations during the ultrasound examinations. We visualize the two-dimensional ultrasound slice in the context of a three-dimensional Couinaud partitioning of the liver. The partitioning is described by planes in 3D reflecting the vascular tree anatomy, specified in the patient by the examiner using her natural interaction tool, i.e., the ultrasound transducer with positional tracking. A pre-defined generic liver model is adapted to the specified partitioning in order to provide a representation of the patients liver parenchyma. The specified Couinaud partitioning and parenchyma model approximation is then used to enhance the examination by providing visual aids to convey the relationships between the placement of the ultrasound plane and the partitioned liver. The 2D ultrasound slice is augmented with Couinaud partitioning intersection information and dynamic label placement. A linked 3D view shows the ultrasound slice, cutting the liver and displayed using fast exploded view rendering. The described visual augmentation has been characterized by the clinical personnel as very supportive during the examination procedure, and also as a good basis for pre-operative case discussions.",
    images = "images/oye11illustrativeCouinaud1.jpg, images/oye11illustrativeCouinaud2.jpg, images/oye11illustrativeCouinaud3.jpg",
    thumbnails = "images/oye11illustrativeCouinaud1_thumb.jpg, images/oye11illustrativeCouinaud2_thumb.jpg, images/oye11illustrativeCouinaud3_thumb.jpg",
    isbn = "978-3-642-22570-3",
    url = "http://dx.doi.org/10.1007/978-3-642-22571-0_6",
    project = "illustrasound,medviz,illvis"
    }
    [Bibtex]
    @ARTICLE {pobitzer11topology,
    author = "Armin Pobitzer and Ronald Peikert and Raphael Fuchs and Benjamin Schindler and Alexander Kuhn and Holger Theisel and Kresimir Matkovic and Helwig Hauser",
    title = "The State of the Art in Topology-based Visualization of Unsteady Flow",
    journal = "Computer Graphics Forum",
    year = "2011",
    volume = "30",
    number = "6",
    pages = "1789--1811",
    month = "September",
    abstract = "Vector fields are a common concept for the representation of many different kinds of flow phenomena in science and engineering. Methods based on vector field topology are known for their convenience for visualizing and analyzing steady flows, but a counterpart for unsteady flows is still missing. However, a lot of good and relevant work aiming at such a solution is available.We give an overview of previous research leading towards topology-based and topology-inspired visualization of unsteady flow, pointing out the different approaches and methodologies involved as well as their relation to each other, taking classical (i.e., steady) vector field topology as our starting point. Particularly, we focus on Lagrangian methods, space-time domain approaches, local methods, and stochastic and multi-field approaches. Furthermore, we illustrate our review with practical examples for the different approaches.",
    images = "images/pobitzer10topology.jpg,",
    thumbnails = "images/pobitzer10topology_thumb.jpg",
    project = "semseg",
    url = "http://dx.doi.org/10.1111/j.1467-8659.2011.01901.x"
    }
    [Bibtex]
    @INPROCEEDINGS {florekHauser11modeTree,
    author = "Martin Florek and Helwig Hauser",
    title = "Interactive Bivariate Mode Trees for Visual Structure Analysis",
    booktitle = "Proceedings of the Spring Conference on Computer Graphics (SCCG 2011)",
    year = "2011",
    pages = "??--??",
    abstract = "The number of modes in a kernel density estimation of a certaindata distribution is strongly dependent on the chosen scale parameter.In this paper, we present an interactive mode tree visualizationthat allows to visually analyze the modality structure of a datadistribution. Due to the branched structure of the bivariate modetree, composed of many curved arcs in 3D, we need to utilize advancedtechniques, including clutter removal through transparency,on demand outlier suppression or preservation, and best views, toimprove the legibility of the visualization mapping.",
    images = "images/florekHauser11modeTree.jpg, images/florekHauser11modeTree2.jpg",
    thumbnails = "images/florekHauser11modeTree_thumb.jpg, images/florekHauser11modeTree2_thumb.jpg",
    location = "Budmerice, Slovakia"
    }
    [PDF] [Bibtex]
    @INPROCEEDINGS {turkay11cluster,
    author = "Cagatay Turkay and Julius Parulek and Nathalie Reuter and Helwig Hauser",
    title = "Integrating Cluster Formation and Cluster Evaluation in Interactive Visual Analysis",
    booktitle = "Proc. Spring Conference on Computer Graphics (SCCG 2011) -- second best paper",
    year = "2011",
    pages = "??--??",
    abstract = "Cluster analysis is a popular method for data investigation wheredata items are structured into groups called clusters. This analysisinvolves two sequential steps, namely cluster formation and clusterevaluation. In this paper, we propose the tight integration of clusterformation and cluster evaluation in interactive visual analysis in orderto overcome the challenges that relate to the black-box nature ofclustering algorithms. We present our conceptual framework in theform of an interactive visual environment. In this realization of ourframework, we build upon general concepts such as cluster comparison,clustering tendency, cluster stability and cluster coherence.Additionally, we showcase our framework on the cluster analysis ofmixed lipid bilayers.",
    pdf = "pdfs/turkay11cluster.pdf",
    images = "images/turkay11cluster2.jpg, images/turkay11cluster1.jpg, images/turkay11cluster3.jpg",
    thumbnails = "images/turkay11cluster2_thumb.jpg, images/turkay11cluster1_thumb.jpg, images/turkay11cluster3_thumb.jpg",
    location = "Budmerice, Slovakia"
    }
    [Bibtex]
    @ARTICLE {turkay11brushingDimensions,
    author = "Cagatay Turkay and Peter Filzmoser and Helwig Hauser",
    title = "Brushing Dimensions -- A Dual Visual Analysis Model for High-dimensional Data",
    journal = "IEEE Transactions on Visualization and Computer Graphics",
    year = "2011",
    volume = "17",
    number = "12",
    pages = "2591--2599",
    abstract = "In many application fields, data analysts have to deal with datasets that contain many expressions per item. The effective analysisof such multivariate datasets is dependent on the users ability to understand both the intrinsic dimensionality of the dataset as well as the distribution of the dependent values with respect to the dimensions. In this paper, we propose a visualization model that enables the joint interactive visual analysis of multivariate datasets with respect to their dimensions as well as with respect to the actual data values. We describe a dual setting of visualization and interaction in items space and in dimensions space. The visualization of items is linked to the visualization of dimensions with brushing and focus+context visualization. With this approach, the user is able to jointly study the structure of the dimensions space as well as the distribution of data items with respect to the dimensions. Even though the proposed visualization model is general, we demonstrate its application in the context of a DNA microarray data analysis.",
    images = "images/turkay11dimensions.png, images/turkay11dimensions3.png, images/turkay11dimensions2.png",
    thumbnails = "images/turkay11dimensions_thumb.png, images/turkay11dimensions3_thumb.png, images/turkay11dimensions2_thumb.png",
    event = "IEEE Information Visualization Conference 2011",
    location = "Providence, RI, USA",
    url = "http://dx.doi.org/10.1109/TVCG.2011.178"
    }
    [PDF] [Bibtex]
    @MISC {Hauser2011Dagstuhl,
    author = "Helwig Hauser",
    title = "Helwig Hauser on Interactive Visual Analysis of Multi-Dimensional Scientific Data",
    howpublished = "Invited talk at the Dagstuhl Seminar on Scientific Visualization in Dagstuhl, Germany.",
    month = "June",
    year = "2011",
    abstract = "Invited talk at the Dagstuhl Seminar on Scientific Visualization in Dagstuhl, Germany.",
    pdf = "pdfs/2011-06-06-Dagstuhl-MultiDimSciDataIVA-print-new-2up.pdf",
    images = "images/2011-06-06-Dagstuhl-MultiDimSciDataIVA-print-new-2up_Image_0001.jpg, images/2011-06-06-Dagstuhl-MultiDimSciDataIVA-print-new--2up_Image_0002.jpg, images/2011-06-06-Dagstuhl-MultiDimSciDataIVA-print-new-2up_Image_0002(2).jpg, images/2011-06-06-Dagstuhl-MultiDimSciDataIVA-print-new-2up_Image_0004.jpg",
    thumbnails = "images/2011-06-06-Dagstuhl-MultiDimSciDataIVA-print-new-2up_Image_0001(2).jpg"
    }
    [Bibtex]
    @ARTICLE {pobitzer11energyScale,
    author = "Armin Pobitzer and Murat Tutkun and {\O }yvind Andreassen and Raphael Fuchs and Ronald Peikert and Helwig Hauser",
    title = "Energy-scale Aware Feature Extraction for Flow Visualization",
    journal = "Computer Graphics Forum",
    year = "2011",
    volume = "30",
    number = "3",
    pages = "771--780",
    abstract = "In the visualization of flow simulation data, feature detectors often tend to result in overly rich response, making some sort of filtering or simplification necessary to convey meaningful images. In this paper we present an approach that builds upon a decomposition of the flow field according to dynamical importance of different scales of motion energy. Focusing on the high-energy scales leads to a reduction of the flow field while retaining the underlying physical process. The presented method acknowledges the intrinsic structures of the flow according to its energy and therefore allows to focus on the energetically most interesting aspects of the flow. Our analysis shows that this approach can be used for methods based on both local feature extraction and particle integration and we provide a discussion of the error caused by the approximation. Finally, we illustrate the use of the proposed approach for both a local and a global feature detector and in the context of numerical flow simulations.",
    images = "images/pobitzer11energyScale1.jpg, images/pobitzer11energyScale3.jpg, images/pobitzer11energyScale2.jpg",
    thumbnails = "images/pobitzer11energyScale1_thumb.jpg, images/pobitzer11energyScale3_thumb.jpg, images/pobitzer11energyScale2_thumb.jpg",
    url = "http://dx.doi.org/10.1111/j.1467-8659.2011.01926.x",
    event = "EuroVis 2011",
    location = "Bergen, Norway",
    project = "semseg"
    }
    [DOI] [Bibtex]
    @ARTICLE {Matkovic11CurrentTrends,
    author = "Kresimir Matkovic and Alan Lez and Helwig Hauser and Armin Pobitzer and Holger Theisel and Alexander Kuhn and Mathias Otto and Ronald Peikert and Benjamin Schindler and Raphael Fuchs",
    title = "Current Trends for 4D Space-Time Topology for Semantic Flow Segmentation",
    journal = "Procedia Computer Science",
    year = "2011",
    volume = "7",
    number = "0",
    pages = "253--255",
    abstract = "Recent advances in computing and simulation technology promote the simulation of time-dependent flows, i.e., flows where the velocity field changes over time. The simulation of time-dependent flow is a more realistic approximation of natural phenomena and it represents an invaluable tool for scientists and practitioners in multiple disciplines, including meteorology, vehicle design, and medicine. Flow visualization, a subfield of scientific visualization, is one of several research areas which deal with the analysis of flows. There are many methods for the analysis of steady flows, but the extension to the time-dependent case is not straight forward. The SemSeg project, a FET-Open project in the 7th Framework programme, attempts to provide a solution for the semantic segmentation of time-dependent flows. It aims at the formulation of a sound theoretical mechanism to describe structural features in time-dependent flow. In this paper, we briefly summarize recent research results from the SemSeg project. Several different approaches are pursued in the project, including methods based on the finite-time Lyapunov exponent (FTLE), methods based on vector field topology (VFT), and interactive visual analysis (IVA) methods. Uncertainty visualization and the interactive evaluation of methods are helping in evaluating the results.",
    images = "images/Matkovic11CurrentTrends.png",
    thumbnails = "images/Matkovic11CurrentTrends_thumb.png",
    note = "Proceedings of the 2nd European Future Technologies Conference and Exhibition 2011 (FET 11)",
    issn = "1877-0509",
    doi = "10.1016/j.procs.2011.09.013",
    url = "http://www.sciencedirect.com/science/article/pii/S1877050911005734"
    }
    [PDF] [Bibtex]
    @INPROCEEDINGS {lampe11modelbuilding,
    author = "Ove Daae Lampe and Helwig Hauser ",
    title = "Model Building in Visualization Space ",
    booktitle = "Proceedings of Sigrad 2011 ",
    year = "2011",
    abstract = "Researching formal models that explain selected natural phenomena of interest is a central aspect of most scientific work. A tested and confirmed model can be the key to classification, knowledge crystallization, and prediction.With this paper we propose a new approach to rapidly draft, fit and quantify model prototypes in visualization space. We also show that these models can provide important insights and accurate metrics about the original data. Using our technique, which is similar to the statistical concept of de-trending, data that behaves according to the model is de-emphasized, leaving only outliers and potential model flaws for further inspection. Moreover, we provide several techniques to assist the user in the process of prototyping such models. We demonstrate the usability of this approach in the context of the analysis of streaming process data from the Norwegian oil and gas industry, and on weather data, investigating the distribution of temperatures over the course of a year.",
    pdf = "pdfs/lampe11sigrad.pdf",
    images = "images/lampe11sigrad.jpg",
    thumbnails = "images/lampe11sigrad_thumb.jpg",
    location = "Stockholm, Sweeden",
    url = "http://www.ep.liu.se/ecp_article/index.en.aspx?issue=065;article=007",
    pres = "http://folk.uib.no/ola062/sigrad2011/",
    project = "elad"
    }
    [PDF] [VID] [Bibtex]
    @ARTICLE {angelelli11straightening,
    author = "Paolo Angelelli and Helwig Hauser",
    title = "Straightening Tubular Flow for Side-by-Side Visualization",
    journal = "IEEE Transactions on Visualization and Computer Graphics",
    year = "2011",
    volume = "17",
    number = "12",
    pages = "2063--2070",
    abstract = "Flows through tubular structures are common in many fields, including blood flow in medicine and tubular fluid flows in engineering.The analysis of such flows is often done with a strong reference to the main flow direction along the tubular boundary. In this paper we present an approach for straightening the visualization of tubular flow. By aligning the main reference direction of the flow, i.e., the center lineof the bounding tubular structure, with one axis of the screen, we are able to natively juxtapose (1.) different visualizations of the same flow,either utilizing different flow visualization techniques, or by varying parameters of a chosen approach such as the choice of seeding locationsfor integration-based flow visualization, (2.) the different time steps of a time-dependent flow, (3.) different projections around the center line, and (4.) quantitative flow visualizations in immediate spatial relation to the more qualitative classical flow visualization. We describe how to utilize this approach for an informative interactive visual analysis. We demonstrate the potential of our approach by visualizing two datasets from two different fields: an arterial blood flow measurement and a tubular gas flow simulation from the automotive industry.",
    pdf = "pdfs/angelelli11straightening.pdf",
    vid = "vids/angelelli11TubularFlowStraightening.wmv",
    images = "images/angelelli11straightening1.jpg, images/angelelli11straightening2.jpg",
    thumbnails = "images/angelelli11straightening1_thumb.jpg, images/angelelli11straightening2_thumb.jpg",
    event = "IEEE Visualization Conference 2011",
    location = "Providence, RI, USA",
    url = "http://dx.doi.org/10.1109/TVCG.2011.235"
    }
    [PDF] [VID] [Bibtex]
    @ARTICLE {kehrer11heterogeneous,
    author = "Johannes Kehrer and Philipp Muigg and Helmut Doleisch and Helwig Hauser",
    title = "Interactive Visual Analysis of Heterogeneous Scientific Data across an Interface",
    journal = "IEEE Transactions on Visualization and Computer Graphics",
    year = "2011",
    volume = "17",
    number = "7",
    pages = "934--946",
    abstract = "We present a systematic approach to the interactive visual analysis of heterogeneous scientific data. The data consists of two interrelated parts given on spatial grids over time (e.g., atmosphere and ocean part from a coupled climate model). By integrating both data parts in a framework of coordinated multiple views (with linking and brushing), the joint investigation of features across the data parts is enabled. An interface is constructed between the data parts that specifies (a) which grid cells in one part are related to grid cells in the other part, and vice versa, (b) how selections (in terms of feature extraction via brushing) are transferred between the two parts, and (c) how an update mechanism keeps the feature specification in both data parts consistentduring the analysis. We also propose strategies for visual analysis that result in an iterative refinement of features specified across both data parts. Our approach is demonstrated in the context of a complex simulation of fluid--structure interaction and a multi-run climate simulation.",
    pdf = "pdfs/kehrer11heterogeneous.pdf",
    vid = "vids/kehrer11heterogeneous.html",
    images = "images/kehrer11heterogeneous2.jpg, images/kehrer11heterogeneous3.jpg, images/kehrer11heterogeneous0.jpg, images/kehrer11heterogeneous1.jpg",
    thumbnails = "images/kehrer11heterogeneous2_thumb.jpg, images/kehrer11heterogeneous3_thumb.jpg, images/kehrer11heterogeneous0_thumb.jpg, images/kehrer11heterogeneous1_thumb.jpg",
    event = "IEEE VisWeek 2011",
    location = "Providence, RI, USA",
    url = "http://dx.doi.org/10.1109/TVCG.2010.111"
    }
    [PDF] [VID] [Bibtex]
    @INPROCEEDINGS {lampe11kde,
    author = "Ove Daae Lampe and Helwig Hauser",
    title = "Interactive Visualization of Streaming Data with Kernel Density Estimation",
    booktitle = "Proceedings of the IEEE Pacific Visualization Symposium (PacificVis 2011)",
    year = "2011",
    pages = "171--178",
    month = "March",
    abstract = "In this paper, we discuss the extension and integration of the statistical concept of Kernel Density Estimation (KDE) in a scatterplot-like visualization for dynamic data at interactive rates. We present a line kernel for representing streaming data, we discuss how the concept of KDE can be adapted to enable a continuous representation of the distribution of a dependent variable of a 2D domain. We propose to automatically adapt the kernel bandwith of KDE to the viewport settings, in an interactive visualization environment that allows zooming and panning. We also present a GPU-based realization of KDE that leads to interactive frame rates, even for comparably large datasets. Finally, we demonstrate the usefulness of our approach in the context of three application scenarios -- one studying streaming ship traffic data, another one from the oil and gas domain, where process data from the operation of an oil rig is streaming in to an on-shore operational center, and a third one studying commercial air traffic in the US spanning 1987 to 2008.",
    pdf = "pdfs/lampe11kde.pdf",
    vid = "vids/lampe11kde.mp4",
    images = "images/lampe11kde1.jpg, images/lampe11kde2.jpg",
    thumbnails = "images/lampe11kde1_thumb.jpg, images/lampe11kde2_thumb.jpg",
    location = "Hong Kong",
    url = "http://dx.doi.org/10.1109/PACIFICVIS.2011.5742387"
    }
    [Bibtex]
    @INPROCEEDINGS {lez11pathlines,
    author = "Alan Lez and Andreas Zajic and Kresimir Matkovic and Armin Pobitzer and Michael Mayer and Helwig Hauser",
    title = "Interactive Exploration and Analysis of Pathlines in Flow Data",
    booktitle = "Proc. International Conference in Central Europe on ComputerGraphics, Visualization and Computer Vision (WSCG 2011)",
    year = "2011",
    pages = "17--24",
    abstract = "The rapid development of large-scale scientific computing nowadays allows to inherently respect the unsteady character of natural phenomena in computational flow simulation. With this new trend to more regularly consider time-dependent flow scenarios, an according new need for advanced exploration and analysis solutions emerges. In this paper, we now present three new concepts in pathline analysis which further improve the abilities of analysis: a multi-step analysis which helps to save time and space needed for computation, direct pathline brushing, and usage of pre-configured view arrangements. We have found that clever combining of these three concepts with already existing methods creates very powerful tool for pathline analysis. The coordinated multiple views (CMV) tool used supports iterative composite brushing which enables a quick information drill-down. We illustrate the usefulness using an example from the automotive industry. We have analyzed an exhaust manifoldtime-dependent simulation data set.",
    images = "images/lez11pathlines1.jpg, images/lez11pathlines2.jpg",
    thumbnails = "images/lez11pathlines1_thumb.jpg, images/lez11pathlines2_thumb.jpg",
    location = "Plzen, Czech Republic",
    project = "semseg"
    }
    [Bibtex]
    @ARTICLE {Matkovic11InteractiveVisual,
    author = "Kresimir Matkovic and Denis Gracanin and Mario Jelovic and Helwig Hauser",
    title = "Interactive Visual Analysis Supporting Design, Tuning, and Optimization of Diesel Engine Injection",
    journal = "Proceedings of IEEE Visualization 2011 (Discovery Exhibition)",
    year = "2011",
    abstract = "Design and optimization of modern, complex systems is unimaginable without simulation. Although the design goals are known in advance, finding an optimal combination of input parameters is a long and tedious task. Simulation of car engine injection systems is a relatively short process. It is possible to run many simulations and then to explore the parameter space. Efficient tools and techniques for parameter space exploration and optimization are needed. We have developed an interactive visual analysis tool, ComVis, and related techniques. We illustrate how ComVis is used to explore the parameter space and to tune and optimize car engine injection systems. The collaboration between domain experts and visualization experts resulted in a new workflow for injection system design, and in development of new, commercially available tools.",
    images = "images/Matkovic11InteractiveVisual01.png, Matkovic11InteractiveVisual02.png, Matkovic11InteractiveVisual03.png",
    thumbnails = "images/Matkovic11InteractiveVisual_thumb.png",
    url = "http://www.discoveryexhibition.org/pmwiki.php/Entries/2011Matkovic"
    }
    [PDF] [VID] [Bibtex]
    @ARTICLE {angelelli11ultrasoundStatistics,
    author = "Paolo Angelelli and Kim Nylund and Odd Helge Gilja and Helwig Hauser",
    title = "Interactive Visual Analysis of Contrast-enhanced Ultrasound Databased on Small Neighborhood Statistics",
    journal = "Computers \& Graphics - Special Issue on Visual Computing in Biology and Medicine",
    year = "2011",
    volume = "35",
    number = "2",
    pages = "218--226",
    abstract = "Contrast-enhanced ultrasound (CEUS) has recently become an important technology for lesion detection and characterization in cancer diagnosis. CEUS is used to investigate the perfusion kinetics in tissue over time, which relates to tissue vascularization. In this paper we present a pipeline that enables interactive visual exploration and semi-automatic segmentation and classification of CEUS data.For the visual analysis of this challenging data, with characteristic noise patterns and residual movements, we propose a robust method to derive expressive enhancement measures from small spatio-temporal neighborhoods. We use this information in a stagedvisual analysis pipeline that leads from a more local investigation to global results such as the delineation of anatomic regions according to their perfusion properties. To make the visual exploration interactive, we have developed an accelerated frameworkbased on the OpenCL library, that exploits modern many-cores hardware. Using our application, we were able to analyze datasets from CEUS liver examinations, being able to identify several focal liver lesions, segment and analyze them quickly and precisely, and eventually characterize them.",
    pdf = "pdfs/angelelli11CEUSIVA.pdf",
    vid = "vids/angelelli11CEUSSegmentation.wmv",
    images = "images/angelelli11ultrasoundStatistics2.jpg, images/angelelli11ultrasoundStatistics1.jpg",
    thumbnails = "images/angelelli11ultrasoundStatistics2_thumb.jpg, images/angelelli11ultrasoundStatistics1_thumb.jpg",
    url = "http://dx.doi.org/10.1016/j.cag.2010.12.005",
    project = "illustrasound,medviz,illvis"
    }
    [Bibtex]
    @ARTICLE {lampe11curveDensity,
    author = "Ove Daae Lampe and Helwig Hauser",
    title = "Curve Density Estimates",
    journal = "Computer Graphics Forum",
    year = "2011",
    volume = "30",
    number = "3",
    pages = "633--642",
    abstract = "In this work, we present a technique based on kernel density estimation for rendering smooth curves. With this approach, we produce uncluttered and expressive pictures, revealing frequency information about one, or, multiple curves, independent of the level of detail in the data, the zoom level, and the screen resolution. With this technique the visual representation scales seamlessly from an exact line drawing, (for low-frequency/low-complexity curves) to a probability density estimate for more intricate situations. This scale-independence facilitates displays based on non-linear time, enabling high-resolution accuracy of recent values, accompanied by long historical series forcontext. We demonstrate the functionality of this approach in the context of prediction scenarios and in the context of streaming data.",
    images = "images/lampe11curveDensity3.jpg, images/lampe11curveDensity1.jpg, images/lampe11curveDensity2.jpg",
    thumbnails = "images/lampe11curveDensity3_thumb.jpg, images/lampe11curveDensity1_thumb.jpg, images/lampe11curveDensity2_thumb.jpg",
    url = "http://dx.doi.org/10.1111/j.1467-8659.2011.01912.x",
    event = "EuroVis 2011",
    location = "Bergen, Norway",
    project = "elad"
    }
    [Bibtex]
    @ARTICLE {turkay11temporalCluster,
    author = "Cagatay Turkay and Julius Parulek and Nathalie Reuter and Helwig Hauser",
    title = "Interactive Visual Analysis of Temporal Cluster Structures",
    journal = "Computer Graphics Forum",
    year = "2011",
    volume = "30",
    number = "3",
    pages = "711--720",
    abstract = "Cluster analysis is a useful method which reveals underlying structures and relations of items after grouping them into clusters. In the case of temporal data, clusters are defined over time intervals where they usually exhibit structural changes. Conventional cluster analysis does not provide sufficient methods to analyze these structural changes, which are, however, crucial in the interpretation and evaluation of temporal clusters. In this paper, we present two novel and interactive visualization techniques that enable users to explore and interpret the structural changes of temporal clusters. We introduce the temporal cluster view, which visualizes the structural quality of a number of temporal clusters, and temporal signatures, which represents the structure of clusters over time. We discuss how these views are utilized to understand the temporal evolution of clusters. We evaluate the proposedtechniques in the cluster analysis of mixed lipid bilayers.",
    images = "images/turkay11temporal1.jpg, images/turkay11temporal2.jpg, images/turkay11temporal3.jpg",
    thumbnails = "images/turkay11temporal1_thumb.jpg, images/turkay11temporal2_thumb.jpg, images/turkay11temporal3_thumb.jpg",
    url = "http://dx.doi.org/10.1111/j.1467-8659.2011.01920.x",
    event = "EuroVis 2011",
    location = "Bergen, Norway"
    }
    [Bibtex]
    @INPROCEEDINGS {pobitzer11semseg,
    author = "Armin Pobitzer and Helwig Hauser",
    title = "The {SemSeg} project and recent developments in flow visualization",
    booktitle = "Proc. Sixth National Conference on Computational Mechanics (MekIT'11)",
    year = "2011",
    pages = "281--292",
    address = "Trondheim, Norway",
    month = "May",
    publisher = "Tapir Academic Press",
    abstract = "The present paper discusses recent efforts to develop semantic segmentation of spacetime flow domains for visualization purposes, taking thework of the SemSeg project as a starting point. In particular we address separation structures based on Finite-time Lyapunov exponents and their extraction, the incorporation of uncertainty, and the application of Interactive Visual Analysis in the context of flow visualization.",
    images = "images/pobitzer11semseg.jpg",
    thumbnails = "images/pobitzer11semseg_thumb.jpg",
    editors = "B. Skallerud and H.I. Andersson",
    project = "semseg"
    }

2010

    [Bibtex]
    @ARTICLE {matkovic10modelView,
    author = "Kresimir Matkovic and Denis Gracanin and Mario Jelovic and Andreas Ammer and Alan Lez and Helwig Hauser",
    title = "Interactive Visual Analysis of Multiple Simulation Runs using the Simulation Model View:  Understanding and Tuning of an Electronic Unit Injector",
    journal = "IEEE Transactions on Visualization and Computer Graphics",
    year = "2010",
    volume = "16",
    number = "6",
    pages = "1449--1457 ",
    abstract = "Multiple simulation runs using the same simulation model with different values of control parameters usually generate large data sets that capture the variational aspects of the behavior of the modeled and simulated phenomenon. We have identified a conceptual and visual gap between the simulation model behavior and the data set that makes data analysis more difficult thannecessary. We propose a simulation model view that helps to bridge that gap by visually combining the simulation model description and the generated data. The simulation model view provides a visual outline of the simulation process and the corresponding simulation model. The view is integrated in a Coordinated Multiple Views (CMV) system. We use three levels of details to efficiently use the display area provided by the simulation model view. We collaborated with a domain expert and used the simulation model view on a problem in the automotive application domain, i.e., meeting the emission requirements for Diesel engines. One of the key components is a fuel injector unit so our goal was to understand and tune an electronic unit injector (EUI). We were mainly interested in understanding the model and how to tune it for three different operation modes: low emission, low consumption, and high power. Very positive feedback from the domain expert shows that the use of the simulation model view and the corresponding analysis procedures within a CMV system amount to an effective technique for interactive visual analysis of multiple simulation runs. We also developed new analysis procedures based on these results.",
    images = "images/matkovic10model1.jpg, images/matkovic10model2.jpg, images/matkovic10model3.jpg",
    thumbnails = "images/matkovic10model1_thumb.jpg, images/matkovic10model2_thumb.jpg, images/matkovic10model3_thumb.jpg",
    event = "IEEE Visualization 2010",
    location = "Salt Lake City, US",
    url = "http://dx.doi.org/10.1109/TVCG.2010.171"
    }
    [Bibtex]
    @MISC {hauser10levelsOfComplexity,
    author = "Helwig Hauser",
    title = "Interactive Visual Analysis with different levels of complexity",
    howpublished = "Invited talk at TU Delft",
    month = "June 24",
    year = "2010",
    abstract = "Interactive visual data exploration and analysis is a powerful methodology for enabling insight into complex and also large data. The iterative process of visualization and interaction (and back to visualization, aso.) can be seen as a visual dialog between the user and the data. Thereby, powerful data analysis schemes are enabled such as a step-by-step information drill-down, steered by the users perception, cognition, and knowledge. In this talk, we look at different levels of this methodology (in the sense of levels of complexity), starting at the first level of ``show \& brush'' continuing then via ``relational analysis'' to a third level that we call ``complex analysis.'' The hypothesis is stated that it indeed is useful to have these different levels of complexity for interactive visual data analysis: a large share of all addressed problems can be satisfyingly solved with the ``simple'' level of ``show \& brush,'' while the more complex levels of this methodology are only paying off in special cases. Along with a characterization of these levels, we also take a look at a number of illustrative examples.",
    images = "images/hauser10levelsOfComplexity.jpg",
    thumbnails = "images/hauser10levelsOfComplexity_thumb.png",
    location = "Delft, The Netherlands",
    pres = "pdfs/hauser10levelsOfComplexity-pres.pdf"
    }
    [Bibtex]
    @INPROCEEDINGS {pobitzer10topology,
    author = "Armin Pobitzer and Ronald Peikert and Raphael Fuchs and Benjamin Schindler and Alexander Kuhn and Holger Theisel and Kresimir Matkovic and Helwig Hauser",
    title = "On the Way Towards Topology-Based Visualization of Unsteady Flow - the State of the Art",
    booktitle = "EuroGraphics 2010 State of the Art Reports (STARs)",
    year = "2010",
    pages = "137--154",
    abstract = "Vector fields are a common concept for the representation of many different kinds of flow phenomena in science and engineering. Topology-based methods have shown their convenience for visualizing and analyzing steady flow but a counterpart for unsteady flow is still missing. However, a lot of good and relevant work has been done aiming at such a solution.We give an overview of the research done on the way towards topology-based visualization of unsteady flow, pointing out the different approaches and methodologies involved as well as their relation to each other, takingclassical (i.e. steady) vector field topology as our starting point. Particularly, we focus on Lagrangian Methods, Space-Time Domain Approaches, Local Methods, and Stochastic and Multi-Field Approaches. Furthermore, weillustrated our review with practical examples for the different approaches.",
    images = "images/pobitzer10topology.jpg,",
    thumbnails = "images/pobitzer10topology_thumb.jpg",
    event = "EuroGraphics 2010",
    location = "Norrk{\"o}ping, Sweden",
    pres = "pdfs/pobitzer10topology-presentation.pdf",
    project = "semseg"
    }
    [VID] [Bibtex]
    @ARTICLE {kehrer10moments,
    author = "Johannes Kehrer and Peter Filzmoser and Helwig Hauser",
    title = "Brushing Moments in Interactive Visual Analysis",
    journal = "Computer Graphics Forum",
    year = "2010",
    volume = "29",
    number = "3",
    pages = "813--822",
    month = "june",
    abstract = "We present a systematic study of opportunities for the interactive visual analysis of multi-dimensional scientific data. This is based on the integration of statistical aggregations along selected data dimensions in a framework of coordinated multiple views (with linking and brushing). Traditional and robust estimates of the four statistical moments (mean, variance, skewness, and kurtosis) as well as measures of outlyingness are integrated in an iterative visual analysis process. Brushing particular statistics, the analyst can investigate data characteristics such as trends and outliers. We present a categorization of beneficial combinations of attributes in 2D scatterplots: (a) k-th vs. (k+1)-th statistical moment of a traditional or robust estimate, (b) traditional vs. robust version of the same moment, (c) two different robust estimates of the same moment. We propose selected view transformations to iteratively construct this multitude of informative views as well as to enhance the depiction of the statistical properties in the scatterplots. In the framework, we interrelate the original distributional data and the aggregated statistics, which allows the analyst to work with both data representations simultaneously. We demonstrate our approach in the context of two visual analysis scenarios of multi-run climate simulations.",
    vid = "vids/kehrer10moments.html",
    images = "images/kehrer10moments.jpg, images/kehrer10moments1.jpg, images/kehrer10moments2.jpg",
    thumbnails = "images/kehrer10moments_thumb.jpg, images/kehrer10moments1_thumb.jpg, images/kehrer10moments2_thumb.jpg",
    event = "EuroVis 2010",
    location = "Bordeaux, France",
    pres = "pdfs/kehrer10moments-presentation.pdf",
    url = "http://dx.doi.org/10.1111/j.1467-8659.2009.01697.x"
    }
    [PDF] [VID] [Bibtex]
    @INPROCEEDINGS {angelelli10guided,
    author = "Paolo Angelelli and Ivan Viola and Kim Nylund and Odd Helge Gilja and Helwig Hauser",
    title = "Guided Visualization of Ultrasound Image Sequences",
    booktitle = "Proceedings of Eurographics Workshop on Visual Computing for Biology and Medicine (VCBM)",
    year = "2010",
    pages = "125--132",
    abstract = "Ultrasonography allows informative and expressive real time examinations of patients. Findings are usually reported as printouts, screen shots and video sequences. However, in certain scenarios, the amount of imaged ultrasound data is considerable or it is challenging to detect the anatomical features of interest. Post-examination access to the information present in the data is, therefore, cumbersome. The examiner must, in fact, review entire videosequences or risk to lose relevant information by reducing the examination to single screen shot and printouts. In this paper we propose a novel post-processing pipeline for guided visual exploration of ultrasound video sequences, to allow easier and richer exploration and analysis of the data. We demonstrate the usefulness of this approach by applying it to a liver examination case, showing easier and quicker ultrasound image selection and data exploration.",
    pdf = "pdfs/angelelli2010usvideovis.pdf",
    vid = "vids/angelelli10DOISound.mp4",
    images = "images/angelelli10guided0.jpg, images/angelelli10guided3.jpg, images/angelelli10guided2.jpg, images/angelelli10guided4.jpg",
    thumbnails = "images/angelelli10guided0_thumb.jpg, images/angelelli10guided3_thumb.jpg, images/angelelli10guided2_thumb.jpg, images/angelelli10guided4_thumb.jpg",
    location = "Leipzig, Germany",
    project = "illustrasound,medviz,illvis"
    }
    [Bibtex]
    @ARTICLE {ladstaedter10explorationClimateData,
    author = "Florian Ladst{\"a}dter and Andrea K. Steiner and Bettina C. Lackner and Barbara Pirscher and Gottfried Kirchengast and Johannes Kehrer and Helwig Hauser and Philipp Muigg and Helmut Doleisch",
    title = "Exploration of Climate Data Using Interactive Visualization",
    journal = "Journal of Atmospheric and Oceanic Technology",
    year = "2010",
    volume = "27",
    number = "4",
    pages = "667--679",
    month = "April",
    abstract = "In atmospheric and climate research, the increasing amount of data available from climate models and observations provides new challenges for data analysis. We present interactive visual exploration as an innovative approach to handle large datasets. Visual exploration does not require any previous knowledge about the data as is usually the case with classical statistics. It facilitatesiterative and interactive browsing of the parameter space in order to quickly understand the data characteristics, to identify deficiencies, to easily focus on interesting features, and to come up with new hypotheses about the data. These properties extend the common statistical treatment of data, and provide a fundamentally different approach. We demonstrate the potential of this technology by exploring atmospheric climate data from different sources including reanalysis datasets, climate models, and radio occultation satellite data. Results are compared to those from classical statistics revealing the complementary advantages of visual exploration. Combining both, the analytical precision of classical statistics and the holistic power of interactive visual exploration, the usual work flow of studying climate data can be enhanced.",
    images = "images/ladstaedter10exploration.jpg, images/ladstaedter10exploration1.jpg, images/ladstaedter10exploration3.jpg, images/ladstaedter10exploration2.jpg",
    thumbnails = "images/ladstaedter10exploration_thumb.jpg, images/ladstaedter10exploration1_thumb.jpg, images/ladstaedter10exploration3_thumb.jpg, images/ladstaedter10exploration2_thumb.jpg",
    url = "http://dx.doi.org/10.1175/2009JTECHA1374.1"
    }
    [Bibtex]
    @MISC {hauser10interactiveStoryTelling,
    author = "Helwig Hauser",
    title = "Interactive Story Telling for Presentation with Visualization",
    howpublished = "Talk at CMR Forum",
    month = "December 17",
    year = "2010",
    images = "images/hauser10interactiveStoryTelling.png",
    thumbnails = "images/hauser10interactiveStoryTelling_thumb.jpg",
    location = "Christian Michelsen Research, Bergen, www.CMR.no",
    pres = "pdfs/hauser10interactiveStoryTelling.pdf"
    }
    [Bibtex]
    @INPROCEEDINGS {florek10kde,
    author = "Martin Florek and Helwig Hauser",
    title = "Quantitative data visualization with interactive KDE surfaces",
    booktitle = "Proceedings of the Spring Conference on Computer Graphics (SCCG 2010)",
    year = "2010",
    pages = "--",
    month = "May",
    abstract = "Kernel density estimation (KDE) is an established statistical concept for assessing the distributional characteristics of data that also has proven its usefulness for data visualization. In this work,we present several enhancements to such a KDE-based visualization that aim (a) at an improved specificity of the visualization with respect to the communication of quantitative information about the data and its distribution and (b) at an improved integration of such a KDE-based visualization in an interactive visualization setting, where, for example, linking and brushing is easily possible both from and to such a visualization. With our enhancements to KDE-based visualization, we can extend the utilization of this great statistical concept in the context of interactive visualization.",
    images = "images/florek10kde.jpg",
    thumbnails = "images/florek10kde_thumb.jpg",
    location = "Budmerice, Slovakia",
    url = "http://dx.doi.org/10.1145/1925059.1925068"
    }
    [Bibtex]
    @MISC {hauser10brainPerfusion,
    author = "Helwig Hauser and Sylvia Gla\ßer",
    title = "Visualizing Statistics of Brain Perfusion Data",
    howpublished = "Talk in the MedViz Seminar Series",
    month = "October 8",
    year = "2010",
    abstract = "Following up earlier cooperative research work with the University of Magdeburg in Germany (with Steffen Oeltze et al.), we are pursuing a new study of perfusion data (this time with Sylvia Glasser et al.) based on statistical tools (such as correlation analysis and principal component analysis) and interactive visual analysis. Shape parameters of concentration time curves are investigated (as well as other quantities that we derived from them) to analyze brain regions that are affected by tumors. Low and high grade tumors are compared. In this talk, a short update on the current state of this research is presented, more results are expected during the weeks and months to come.",
    images = "images/hauser10brainPerf.png",
    thumbnails = "images/hauser10brainPerf_thumb.jpg",
    location = "Bergen, Norway",
    pres = "pdfs/hauser10brainPerfusion-pres.pdf"
    }
    [Bibtex]
    @ARTICLE {fuchs10lagrangian,
    author = "Raphael Fuchs and Jan Kemmler and Benjamin Schindler and Jrgen Waser and Filip Sadlo and Helwig Hauser and Ronald Peikert",
    title = "Toward a Lagrangian Vector Field Topology",
    journal = "Computer Graphics Forum",
    year = "2010",
    volume = "29",
    number = "3",
    pages = "1163--1172",
    month = "june",
    abstract = "In this paper we present an extended critical point concept which allows us to apply vector field topology in the case of unsteady flow. We propose a measure for unsteadiness which describes the rate of change of the velocities ina fluid element over time. This measure allows us to select particles for which topological properties remain intact inside a finite spatio-temporal neighborhood. One benefit of this approach is that the classification of critical points based on the eigenvalues of the Jacobian remains meaningful. In the steady case the proposed criterion reduces to the classical definition of critical points. As a first step we show that finding an optimal Galilean frame of reference can be obtained implicitly by analyzing the acceleration field. In a second step we show that this can be extended by switching to the Lagrangian frame of reference. This way the criterion can detect critical points moving along intricate trajectories. We analyze the behavior of the proposed criterion based on two analytical vector fields for which a correct solution is defined by their inherent symmetries and present results for numerical vector fields.",
    images = "images/fuchs10lagrangian2.jpg, images/fuchs10lagrangian.jpg",
    thumbnails = "images/fuchs10lagrangian2_thumb.jpg, images/fuchs10lagrangian_thumb.jpg",
    event = "EuroVis 2010",
    location = "Bordeaux, France",
    url = "http://dx.doi.org/10.1111/j.1467-8659.2009.01686.x",
    project = "semseg"
    }
    [Bibtex]
    @ARTICLE {viola10editorial,
    author = "Ivan Viola and Helwig Hauser and David Ebert",
    title = "Editorial note for special section on illustrative visualization",
    journal = "Computers \& Graphics",
    year = "2010",
    volume = "34",
    number = "4",
    pages = "335--336",
    images = "images/viola10editorial.jpg",
    thumbnails = "images/viola10editorial_thumb.jpg",
    url = "http://dx.doi.org/10.1016/j.cag.2010.05.011",
    project = "illvis"
    }
    [Bibtex]
    @MISC {hauser10visualDialog,
    author = "Helwig Hauser",
    title = "Interactive Visualization as a Visual Dialog for Data Investigation",
    howpublished = "Talk at Visualiseringsdag Stockholm",
    month = "April 13",
    year = "2010",
    images = "images/hauser10visualDialog.png",
    thumbnails = "images/hauser10visualDialog_thumb.jpg",
    location = "Stockholm, Sweden",
    pres = "pdfs/hauser10visualDialog.pdf"
    }
    [PDF] [VID] [Bibtex]
    @INPROCEEDINGS {lampe10differenceViews,
    author = "Ove Daae Lampe and Johannes Kehrer and Helwig Hauser",
    title = "Visual Analysis of Multivariate Movement Data Using Interactive Difference Views",
    booktitle = "Proceedings of Vision, Modeling, and Visualization (VMV 2010)",
    year = "2010",
    pages = "315--322",
    abstract = "Movement data consisting of a large number of spatio-temporal agent trajectories is challenging to visualize, especially when all trajectories are attributed with multiple variates. In this paper, we demonstrate the visualexploration of such movement data through the concept of interactive difference views. By reconfiguring the difference views in a fast and flexible way, we enable temporal trend discovery. We are able to analyze large amounts of such movement data through the use of a frequency-based visualization based on kernel density estimates (KDE), where it is also possible to quantify differences in terms of the units of the visualized data. Using the proposed techniques, we show how the user can produce quantifiable movement differences and compare different categorical attributes (such as weekdays, ship-type, or the general wind direction), or a range of a quantitative attribute (such as how two hours traffic compares to the average). We present results from the exploration of vessel movement data from the Norwegian Coastal Administration, collected by the Automatic Identification System (AIS) coastaltracking. There are many interacting patterns in such movement data, both temporal and other more intricate, such as weather conditions, wave heights, or sunlight. In this work we study these movement patterns, answering specific questions posed by Norwegian Coastal Administration on potential shipping lane optimizations.",
    pdf = "pdfs/lampe10difference.pdf",
    vid = "vids/lampe10difference.mp4",
    images = "images/lampe10difference1.jpg,images/lampe10difference3.jpg,images/lampe10difference2.jpg",
    thumbnails = "images/lampe10difference1_thumb.jpg,images/lampe10difference3_thumb.jpg,images/lampe10difference2_thumb.jpg",
    location = "Siegen, Germany",
    pres = "pdfs/lampe10difference-presentation.pdf"
    }
    [Bibtex]
    @MISC {hauser10storyTelling,
    author = "Helwig Hauser",
    title = "Story Telling for Visualization",
    howpublished = "Talk at Story Telling workshop 2010, UC Davis",
    month = "November 1",
    year = "2010",
    images = "images/hauser10storyTelling.png",
    thumbnails = "images/hauser10storyTelling_thumb.jpg",
    location = "Davis, CA",
    pres = "pdfs/hauser10storyTelling.pdf"
    }
    [Bibtex]
    @INPROCEEDINGS {matkovic10car,
    author = "Kresimir Matkovic and Denis Gracanin and R. Splechtna and Helwig Hauser",
    title = "Interactive Visual Analysis of Families of Surfaces: An Application to Car Race and Car Setup",
    booktitle = "Proceedings of the Internat. Symp. on Visual Analytics Science and Technology (EuroVAST 2010)",
    year = "2010",
    pages = "--",
    abstract = "Modern simulations often produce time series, or even functions of two variables as outputs for single attributes. Such complex data require carefully chosen and designed analysis procedures and the corresponding data model. The use of previously developed curve and surface views provides strong support for visual exploration and analysis of complex data. In this paper we describe how interactive visual analysis can support users in getting insightinto complex data. The case study, based on TORCS 3D racing cars simulator, illustrates our approach and its successful application to a real world problem. The analysis of the car parameters and driving performances during races provides an insight and explanation for race results. That insight is then used to fine-tune car parameters to achieve better driving performance.",
    images = "images/matkovic10car.jpg, images/matkovic10car2.jpg",
    thumbnails = "images/matkovic10car_thumb.jpg, images/matkovic10car2_thumb.jpg",
    location = "Bordeaux, France"
    }

2009

    [Bibtex]
    @ARTICLE {matkovic09surfaces,
    author = "Kresimir Matkovic and Denis Gracanin and Borislav Klarin and Helwig Hauser",
    title = "Interactive Visual Analysis of Complex Scientific Data as Families of Data Surfaces",
    journal = "IEEE Transactions on Visualization and Computer Graphics",
    year = "2009",
    volume = "15",
    number = "6",
    pages = "1351--1358",
    abstract = "The widespread use of computational simulation in science and engineering provides challenging research opportunities. Multiple independent variables are considered and large and complex data are computed, especially in the case of multi-run simulation. Classical visualization techniques deal well with 2D or 3D data and also with time-dependent data. Additional independent dimensions, however, provide interesting new challenges. We present an advanced visual analysis approach that enables a thorough investigation of families of data surfaces, i.e., datasets, with respect to pairs of independent dimensions. While it is almost trivial to visualize one such data surface, the visual exploration and analysis of many such data surfaces is a grand challenge, stressing the users perception and cognition. We propose an approach that integrates projections and aggregations of the data surfaces at different levels (one scalar aggregate per surface, a 1D profile per surface, or the surface as such). We demonstrate the necessity for a flexible visual analysis system that integrates many different (linked) views for making sense of this highly complex data. To demonstrate its usefulness, we exemplify our approach in the context of a meteorological multi-run simulation data case and in the context of the engineering domain, where our collaborators are working with the simulation of elastohydrodynamic (EHD) lubrication bearing in the automotive industry.",
    images = "images/matkovic09surfaces.jpg, images/matkovic09surfaces2.jpg",
    thumbnails = "images/matkovic09surfaces_thumb.jpg, images/matkovic09surfaces2_thumb.jpg",
    event = "IEEE Visualization 2009",
    url = "http://dx.doi.org/10.1109/TVCG.2009.155"
    }
    [Bibtex]
    @ARTICLE {patel09knowledge,
    author = "Daniel Patel and {\O }yvind Sture and Helwig Hauser and Christopher Giertsen and Meister Eduard Gr{\"o}ller",
    title = "Knowledge-assisted visualization of seismic data",
    journal = "Computers \& Graphics",
    year = "2009",
    volume = "33",
    number = "5",
    pages = "585--596",
    abstract = "We present novel techniques for knowledge-assisted annotation and computer-assisted interpretation of seismic data for oil and gas exploration. We describe the existing procedure for oil and gas search which consists of manually extracting information from seismic data and then aggregating it into knowledge in a detail-oriented bottom-up approach. We then point out the weaknesses of this approach and propose how to improve on it by introducing a holistic computer-assisted top-down approach intended as a preparation step enabling a quicker, more focused and accurate bottom-up interpretation. The top-down approach also enables early representations of hypotheses and knowledge using domain-specific textures for annotating the data. Finally we discuss how these annotations can be extended to 3D for volumetric annotations.",
    images = "images/patel09knowledge2.jpg, images/patel09knowledge1.jpg, images/patel09knowledge3.jpg, images/patel09knowledge4.jpg",
    thumbnails = "images/patel09knowledge2_thumb.jpg, images/patel09knowledge1_thumb.jpg, images/patel09knowledge3_thumb.jpg, images/patel09knowledge4_thumb.jpg",
    url = "http://dx.doi.org/10.1016/j.cag.2009.06.005"
    }
    [Bibtex]
    @INPROCEEDINGS {matkovic09imagecollection,
    author = "Kresimir Matkovic and Denis Gra\v{c}anin and Wolfgang Freiler and Jana Banova and Helwig Hauser",
    title = "Large Image Collections---Comprehension and Familiarization by Interactive Visual Analysis",
    booktitle = "Proceedings of the 10th International Symposium on Smart Graphics (SG'09)",
    year = "2009",
    pages = "15--26",
    publisher = "Springer-Verlag",
    abstract = "Large size and complex multi-dimensional characteristics of image collections demand a multifaceted approach to exploration and analysis providing better comprehension and appreciation. We explore large and complex data-sets composed of images and parameters describing the images. We describe a novel approach providing new and exciting opportunities for the exploration and understanding of such data-sets. We utilize coordinated, multiple views for interactive visual analysis of all parameters. Besides iterative refinement and drill-down in the image parameters space, exploring such data-sets requiresa different approach since visual content cannot be completely parameterized. We simultaneously brush the visual content and the image parameter values. The user provides a visual hint (using an image) for brushing in addition to providing a complete image parameters specification. We illustrate our approach on a data-set of more than 26,000 images from Flickr. The developed approach can be used in many application areas, including sociology, marketing, or everyday use.",
    images = "images/matkovic09image1.jpg, images/matkovic09image.jpg",
    thumbnails = "images/matkovic09image1_thumb.jpg, images/matkovic09image_thumb.jpg",
    url = "http://dx.doi.org/10.1007/978-3-642-02115-2_2"
    }
    [Bibtex]
    @INPROCEEDINGS {shi09path,
    author = "Kuangyu Shi and Holger Theisel and Helwig Hauser and Tino Weinkauf and Kresimir Matkovic and Hans-Christian Hege and Hans-Peter Seidel",
    title = "Path Line Attributes -- an Information Visualization Approach to Analyzing the Dynamic Behavior of 3D Time-Dependent Flow Fields",
    booktitle = "Topology-Based Methods in Visualization II",
    year = "2009",
    pages = "75--88",
    abstract = "We describe an approach to visually analyzing the dynamic behavior of 3D time-dependent flow fields by considering the behavior of the path lines. At selectedpositions in the 4D space-time domain, we compute a number of local and global properties of path lines describing relevant features of them. The resulting multivariate data set is analyzed by applying state-of-the-art information visualization approaches in the sense of a set of linked views (scatter plots, parallel coordinates, etc.) with interactive brushing and focus+context visualization. The selected path lines with certain properties are integrated and visualized as colored 3D curves. This approach allows an interactive exploration of intricate 4D flow structures. We apply our method to a number of flow data sets and describe how path line attributes are used for describing characteristic features of these flows.",
    images = "images/shi09path1.jpg, images/shi09path2.jpg",
    thumbnails = "images/shi09path1_thumb.jpg, images/shi09path2_thumb.jpg",
    url = "http://dx.doi.org/10.1007/978-3-540-88606-8_6"
    }
    [Bibtex]
    @INPROCEEDINGS {konyha09iva,
    author = "Zoltan Konyha and Kresimir Matkovic and Helwig Hauser",
    title = "Interactive Visual Analysis in Engineering: A Survey",
    booktitle = "Proceedings of the Spring Conference on Computer Graphics (SCCG 2009)",
    year = "2009",
    pages = "31--38",
    month = "apr",
    abstract = "Interactive visual analysis has become a very popular research field. There is a significant body of literature on making sense of massive data sets, on visualization and interaction techniques as well as on analysis concepts. However, surveying how those results can be applied to actual engineering problems, including both product and manufacturing design as well as evaluation of simulation and measurement data, has not been discussed sufficiently to date. In this paper we provide a selection of demonstration cases that document the potential benefits of using interactive visual analysis in a wide range of engineering domains, including the investigation of flow and particle dynamics, automotive engine design tasks and change management in the product design process. We attempt to identify some of the proven technological details such as the linking of space-time and attribute views through an application-wide coherent selection mechanism. This paper might be an interesting survey for readers with a relation to the engineering sector, both reflecting on available technological building blocks for interactive visual data analysis as well as exemplifying the potential benefits on behalf of the application side.",
    images = "images/konyha09iva.jpg",
    thumbnails = "images/konyha09iva_thumb.jpg",
    location = "Budmerice, Slovakia",
    url = "http://www.cg.tuwien.ac.at/research/publications/2009/Konyha_2009_survey/"
    }
    [Bibtex]
    @INCOLLECTION {hauserSchumann09pipeline,
    author = "Helwig Hauser and Heidrun Schumann",
    title = "Visualization Pipeline",
    booktitle = "Encyclopedia of Database Systems",
    publisher = "Springer US",
    year = "2009",
    editor = "Ling Liu and M. Tamer {\"O}zsu",
    pages = "3414--3416",
    abstract = "Without Abstract",
    images = "images/hauserSchumann09pipeline.jpg, images/hauserSchumann09pipeline2.jpg",
    thumbnails = "images/hauserSchumann09pipeline_thumb.jpg, images/hauserSchumann09pipeline2_thumb.jpg",
    url = "http://dx.doi.org/10.1007/978-0-387-39940-9_1133"
    }
    [Bibtex]
    @ARTICLE {fuchs09star,
    author = "Raphael Fuchs and Helwig Hauser",
    title = "Visualization of Multi-Variate Scientific Data",
    journal = "Computer Graphics Forum",
    year = "2009",
    volume = "28",
    number = "6",
    pages = "1670--1690",
    abstract = "In this state-of-the-art report we discuss relevant research worksrelated to the visualization of complex, multi-variate data. We discuss how different techniques take effect at specific stages of the visualization pipeline and how they apply to multi-variate data sets being composed of scalars, vectors and tensors. We also provide a categorization of these techniques with the aim for a better overview of related approaches. Based on this classification we highlight combinable and hybrid approaches and focus on techniques that potentially lead towards new directions in visualization research. In the second part of this paper we take a look at recent techniques that are useful for the visualization of complex data sets either because they are general purpose or because they can be adapted to specific problems.",
    images = "images/buerger07star1.png, images/buerger07star2.png",
    thumbnails = "images/buerger07star1_thumb.png, images/buerger07star2_thumb.png",
    url = "http://dx.doi.org/10.1111/j.1467-8659.2009.01429.x"
    }
    [Bibtex]
    @ARTICLE {lampe09cuvicentric,
    author = "Ove Daae Lampe and Carlos Correa and Kwan-Liu Ma and Helwig Hauser",
    title = "Curve-Centric Volume Reformation for Comparative Visualization",
    journal = "IEEE Transactions on Visualization and Computer Graphics",
    year = "2009",
    volume = "15",
    number = "6",
    pages = "1235--1242",
    abstract = "We present two visualization techniques for curve-centric volume reformation with the aim to create compelling comparative visualizations. A curve-centric volume reformation deforms a volume, with regards to a curve in space, to create a new space in which the curve evaluates to zero in two dimensions and spans its arc-length in the third. The volume surrounding the curve is deformed such that spatial neighborhood to the curve is preserved. The result of the curve-centric reformation produces images where one axis is aligned to arc-length, and thus allows researchers and practitioners to apply their arc-length parameterized data visualizations in parallel for comparison. Furthermore we show that when visualizing dense data, our technique provides an inside out projection, from the curve and out into the volume, which allows for inspection what is around the curve. Finally we demonstrate  the usefulness of our techniques in the context of two application cases. We show that existing data visualizations of arc-length parameterized data can be enhanced by using our techniques, in addition to creating a new view and perspective on volumetric data around curves. Additionally we show how volumetric data can be brought into plotting environments that allow precise readouts. In the first case we inspect streamlines in a flow field around a car, and in the second we inspect seismic volumes and well logs from drilling.",
    images = "images/lampe09cuvicentric4.jpg, images/lampe09cuvicentric5.jpg, images/lampe09cuvicentric2.jpg, images/lampe09cuvicentric3.jpg",
    thumbnails = "images/lampe09cuvicentric4_thumb.jpg, images/lampe09cuvicentric5_thumb.jpg, images/lampe09cuvicentric2_thumb.jpg, images/lampe09cuvicentric3_thumb.jpg",
    event = "IEEE Visualization 2009",
    url = "http://dx.doi.org/10.1109/TVCG.2009.136"
    }
    [Bibtex]
    @INPROCEEDINGS {oeltze09perfusion,
    author = "Steffen Oeltze and Bernhard Preim and Helwig Hauser and Jarle R{\O }rvik and Arvid Lundervold",
    title = "Visual analysis of cerebral perfusion data -- four interactive approaches and a comparison",
    booktitle = "Proceedings of the 6th Intern. Symp. on Image and Signal Processing and Analysis (ISPA 2009)",
    year = "2009",
    pages = "582--589",
    month = "Sept.",
    abstract = "Cerebral perfusion data are acquired to characterize the regional blood supply of brain tissue. One of their major diagnostic applications is ischemicstroke assessment. We present a comparison of four interactive approaches to analyzingcerebral perfusion data from ischemic stroke patients which are based on (1) concentration-time curves (CTC) derived from the original data, (2) parameters describing the CTC shape, (3) enhancement trends computed in a statistical analysis, and (4) semi-quantitative perfusion parameters derived via parametric modelling and deconvolution. The comparison is carried out with regard to the involved data pre-processing, the complexity of the interactive analysis and the resulting tissue selections. It is supported by a visual analysis framework that integrates the different approaches. The rich information content in time-dependent 3D perfusion data is both an opportunity for improved diagnosis and a challenge how to optimize the assessment of such rich data. With our comparison we contribute to a discussion between data-near and model-near assessment strategies and their respective opportunities.",
    images = "images/oeltze09perfusion1.jpg, images/oeltze09perfusion2.jpg",
    thumbnails = "images/oeltze09perfusion1_thumb.jpg, images/oeltze09perfusion2_thumb.jpg"
    }
    [PDF] [VID] [Bibtex]
    @INPROCEEDINGS {lie09glyphBased3Dvisualization,
    author = "Andreas E. Lie and Johannes Kehrer and Helwig Hauser",
    title = "Critical Design and Realization Aspects of Glyph-based 3D Data Visualization",
    booktitle = "Proceedings of the Spring Conference on Computer Graphics (SCCG 2009)",
    year = "2009",
    pages = "27--34",
    month = "April",
    abstract = "Glyphs are useful for the effective visualization of multi-variate  data. They allow for easily relating multiple data attributes to each  other in a coherent visualization approach. While the basic principle  of glyph-based visualization has been known for a long time,  scientific interest has recently increased focus on the question of  how to achieve a clever and successful glyph design. Along this  newer trend, we present a structured discussion of several critical  design aspects of glyph-based visualization with a special focus on  3D data. For three consecutive steps of data mapping, glyph instantiation,  and rendering, we identify a number of design considerations.  We illustrate our discussion with a new glyph-based visualization  of time-dependent 3D simulation data and demonstrate how  effective results are achieved.",
    pdf = "pdfs/lie09glyphBased3Dvisualization.pdf",
    vid = "vids/lie09glyphBased3Dvisualization.mp4",
    images = "images/lie09glyphs.png, images/lie09dpf.jpg, images/lie09hurricane2.jpg, images/lie09hurricane.jpg",
    thumbnails = "images/lie09glyphs_thumb.png, images/lie09dpf_thumb.jpg, images/lie09hurricane2_thumb.jpg, images/lie09hurricane_thumb.jpg",
    location = "Budmerice, Slovakia",
    url = "http://dx.doi.org/10.1145/1980462.1980470"
    }
    [Bibtex]
    @ARTICLE {nylund2009sonography,
    author = "Kim Nylund and Svein {\O }degaard and Trygve Hausken and Geir Folvik and Golen Arslan Lied and Ivan Viola and Helwig Hauser and Odd Helge Gilja",
    title = "Sonography of the small intestine",
    journal = "World Journal of Gastroenterology",
    year = "2009",
    volume = "15",
    number = "11",
    pages = "1319--1330",
    month = "March",
    abstract = "In the last two decades, there has been substantial development in the diagnostic possibilities for examining the small intestine. Compared with computerized tomography, magnetic resonance imaging, capsule endoscopy and double-balloon endoscopy, ultrasonography has the advantage of being cheap, portable, flexible and user- and patient-friendly, while at the same time providing the clinician with image data of high temporal and spatial resolution. The method has limitations with penetration in obesity and with intestinal air impairing image quality. The flexibility ultrasonography offers the examiner also implies that a systematic approach during scanning is needed. This paper reviews the basic scanning techniques and new modalities such as contrast-enhanced ultrasound, elastography, strain rate imaging, hydrosonography, allergosonography, endoscopic sonography and nutritional imaging, and the literature on disease-specific findings in the small intestine. Some of these methods have shown clinical benefit, while others are under research and development to establish their role in the diagnostic repertoire. However, along with improved overall image quality of new ultrasound scanners, these methods have enabled more anatomical and physiological changes in the small intestine to be observed. Accordingly, ultrasound of the small intestine is an attractive clinical tool to study patients with a range of diseases.",
    images = "images/nylund09sonosmall.jpg",
    thumbnails = "images/nylund09sonosmall_thumb.jpg",
    url = "http://www.wjgnet.com/1007-9327/15/1319.pdf",
    project = "medviz"
    }
    [Bibtex]
    @INPROCEEDINGS {ropinski09closeups,
    author = "Timo Ropinski and Ivan Viola and Martin Biermann and Helwig Hauser and Klaus Hinrichs",
    title = "Multimodal Visualization with Interactive Closeups",
    booktitle = "EGUK Theory and Practice of Computer Graphics",
    year = "2009",
    month = "June",
    abstract = "Closeups are used in illustrations to provide detailed views on regions of interest. They are integrated into the rendering of the whole structure in order to reveal their spatial context. In this paper we present the concept of interactive closeups for medical reporting. Each closeup is associated with a region of interest and may show a single modality or a desired combination of the available modalities using different visualization styles. Thus it becomes possible to visualize multiple modalities simultaneously and to support doctor-to-doctor communication on the basis of interactive multimodal closeup visualizations. We discuss how to compute a layout for 2D and 3D closeups, and how to edit a closeup configuration to prepare a presentation or a subsequent doctor-to-doctor communication. Furthermore, we introduce a GPU-based rendering algorithm, which allows to render multiple closeups at interactive frame rates. We demonstrate the application of the introduced concepts to multimodal PET/CT data sets additionally co-registered with MRI.",
    images = "http://viscg.uni-muenster.de/publications/2009/RVBHH09/bc-case_closeups.png, http://viscg.uni-muenster.de/publications/2009/RVBHH09/3dcloseup.jpg, http://viscg.uni-muenster.de/publications/2009/RVBHH09/closeup0.jpg, http://viscg.uni-muenster.de/publications/2009/RVBHH09/interaction2.jpg",
    thumbnails = "images/ropinski09closeup_thumb.jpg, http://viscg.uni-muenster.de/publications/2009/RVBHH09/.thumbs/3dcloseup.jpg.jpg, http://viscg.uni-muenster.de/publications/2009/RVBHH09/.thumbs/closeup0.jpg.jpg, http://viscg.uni-muenster.de/publications/2009/RVBHH09/.thumbs/interaction2.jpg.jpg",
    url = "http://viscg.uni-muenster.de/publications/2009/RVBHH09/",
    project = "illvis,medviz"
    }
    [Bibtex]
    @INPROCEEDINGS {piringer09hds,
    author = "Harald Piringer and Matthias Buchetics and Helwig Hauser and Meister Eduard Gr{\"o}ller",
    title = "Hierarchical Difference Scatterplots - Interactive Visual Analysis of Data Cubes",
    booktitle = "Proceedings of the ACM SIGKDD Workshop on Visual Analytics and Knowledge Discovery (VAKD)",
    year = "2009",
    pages = "56--65",
    month = "jun",
    abstract = "Data cubes as employed by On-Line Analytical Processing(OLAP) play a key role in many application domains. The analysis typically involves to compare categories of different hierarchy levels with respect to size and pivoted values. Most existing visualization methods for pivotedvalues, however, are limited to single hierarchy levels. Themain contribution of this paper is an approach calledHierarchical Difference Scatterplot (HDS). A HDS allows forrelating multiple hierarchy levels and explicitly visualizesdifferences between them in the context of the absoluteposition of pivoted values. We discuss concepts of tightlycoupling HDS to other types of tree visualizations andpropose the integration in a setup of multiple views, whichare linked by interactive queries on the data. We evaluateour approaches by analyzing social survey data incollaboration with a domain expert.",
    images = "images/piringer09hds.jpg, images/piringer09hds2.jpg",
    thumbnails = "images/piringer09hds_thumb.jpg, images/piringer09hds2_thumb.jpg",
    location = "Paris, France",
    url = "http://www.cg.tuwien.ac.at/research/publications/2009/piringer-2009-hds/"
    }

2008

    [VID] [Bibtex]
    @ARTICLE {kehrer08hypothesisGeneration,
    author = "Johannes Kehrer and Florian Ladst{\"a}dter and Philipp Muigg and Helmut Doleisch and Andrea Steiner and Helwig Hauser",
    title = "Hypothesis Generation in Climate Research with Interactive Visual Data Exploration",
    journal = "IEEE Transactions on Visualization and Computer Graphics (IEEE TVCG)",
    year = "2008",
    volume = "14",
    number = "6",
    pages = "1579--1586",
    month = "Oct",
    abstract = "One of the most prominent topics in climate research is the investigation, detection, and allocation of climate change. In this paper, we aim at identifying regions in the atmosphere (e.g., certain height layers) which can act as sensitive and robust indicators for climate change. We demonstrate how interactive visual data exploration of large amounts of multi-variate and time-dependent climate data enables the steered generation of promising hypotheses for subsequent statistical evaluation. The use of new visualization and interaction technology -- in the context of a coordinated multiple views framework -- allows not only to identify these promising hypotheses, but also to efficiently narrow down parameters that are required in the process of computational data analysis. Two datasets, namely an ECHAM5 climate model run and the ERA-40 reanalysis incorporating observational data, are investigated. Higher-order information such as linear trends or signal-to-noise ratio is derived and interactively explored in order to detect and explore those regions which react most sensitively to climate change. As one conclusion from this study, we identify an excellent potential for usefully generalizing our approach to other, similar application cases, as well.",
    vid = "vids/kehrer08hypothesis.html",
    images = "images/kehrer08vis01.jpg, images/kehrer08vis03.jpg, images/kehrer08vis04.png",
    thumbnails = "images/kehrer08vis01_thumb.jpg, images/kehrer08vis03_thumb.jpg, images/kehrer08vis04_thumb.png",
    event = "IEEE Visualization 2008",
    location = "Columbus, Ohio, USA",
    url = "http://dx.doi.org/10.1109/TVCG.2008.139",
    pres = "pdfs/kehrer08vis-presentation.pdf"
    }
    [Bibtex]
    @ARTICLE {freiler08setTyped,
    author = "Wolfgang Freiler and Kresimir Matkovic and Helwig Hauser",
    title = "Interactive Visual Analysis of Set-Typed Data",
    journal = "IEEE Transactions on Visualization and Computer Graphics (IEEE TVCG)",
    year = "2008",
    volume = "14",
    number = "6",
    pages = "1340--1347",
    month = "Oct",
    abstract = "While it is quite typical to deal with attributes of different data types in the visualization of heterogeneous and multivariate  datasets, most existing techniques still focus on the most usual data types such as numerical attributes or strings. In this paper we present a new approach to the interactive visual exploration and analysis of data that contains attributes which are of set type. A set-typed attribute of a data item -- like one cell in a table -- has a list of n>=0 elements as its value.  We present the setogram as a new visualization approach to represent data of set type and to enable interactive visual exploration and analysis. We also demonstrate how this approach is capable to help in dealing with datasets that have a larger number of dimensions (more than a dozen or more),  especially also in the context of categorical data. To illustrate the effectiveness of our approach, we present the interactive visual analysis of a CRM dataset with data from a questionnaire on the education and shopping habits of about 90000 people.",
    images = "images/freiler08setTyped.png, images/freiler08setTyped1.png, images/freiler08setTyped2.png",
    thumbnails = "images/freiler08setTyped_thumb.png, images/freiler08setTyped1_thumb.png, images/freiler08setTyped2_thumb.png",
    event = "IEEE Information Visualization 2008",
    location = "Columbus, Ohio, USA",
    url = "http://dx.doi.org/10.1109/TVCG.2008.144"
    }
    [VID] [Bibtex]
    @INPROCEEDINGS {viola08illustrasound,
    author = "Ivan Viola and Kim Nylund and Ola Kristoffer {\O }ye and Dag Magne Ulvang and Odd Helge Gilja and Helwig Hauser",
    title = "Illustrated Ultrasound for Multimodal Data Interpretation of Liver Examinations",
    booktitle = "Proceedings of Eurographics Workshop on Visual Computing in Biomedicine",
    year = "2008",
    pages = "125--133",
    month = "Oct",
    abstract = "Traditional visualization of real-time 2D ultrasound data is difficult to interpret, even for experienced medical personnel. To make the interpretation during the education phase easier, we enhance the visualization during liver examinations with an abstracted depiction of relevant anatomical structures, here denoted as illustrated ultrasound. The specifics of enhancing structures are available through an interactively co-registered computed tomography, which has been enhanced by semantic information. To assist the orientation in the liver, we partition the liver into Couinaud segments. They are defined in a rapid segmentation process based on linked 2D slice views and 3D exploded views. The semantics are interactively related from the co-registered modality to the real-time ultrasound via co-registration. During the illustrated ultrasound examination training we provide visual enhancements that depict which liver segments are intersected by the ultrasound slice.",
    vid = "vids/viola08illustrasound.mp4",
    images = "images/viola08illustrasound.jpg, images/viola08illustrasound1.jpg, images/viola08illustrasound2.jpg, images/viola08illustrasound3.jpg",
    thumbnails = "images/viola08illustrasound_thumb.jpg, images/viola08illustrasound1_thumb.jpg, images/viola08illustrasound2_thumb.jpg, images/viola08illustrasound3_thumb.jpg",
    location = "Delft, The Netherlands",
    url = "http://www.ii.uib.no/vis/team/viola/_pdfs/viola_2008_vcbm.pdf",
    project = "illvis,illustrasound,medviz"
    }
    [PDF] [Bibtex]
    @ARTICLE {fuchs08parallel,
    author = "Raphael Fuchs and Ronald Peikert and Helwig Hauser and Filip Sadlo and Philipp Muigg",
    title = "Parallel Vectors Criteria for Unsteady Flow Vortices",
    journal = "IEEE Transactions on Visualization and Computer Graphics (IEEE TVCG)",
    year = "2008",
    volume = "14",
    number = "3",
    pages = "615--626",
    month = "May",
    abstract = "Feature-based flow visualization is naturally dependent on feature extraction. To extract flow features, often higher-order properties of the flow data are used such as the Jacobian or curvature properties, implicitly describing the flow features in terms of their inherent flow characteristics (e.g., collinear flow and vorticity vectors). In this paper we present recent research which leads to the (not really surprising) conclusion that feature extraction algorithms need to be extended to a time-dependent analysis framework (in terms of time derivatives) when dealing with unsteady flow data. Accordingly, we present two extensions of the parallel vectors based vortex extraction criteria to the time-dependent domain and show the improvements of feature-based flow visualization in comparison to the steady versions of this extraction algorithm both in the context of a high-resolution dataset, i.e., a simulation specifically designed to evaluate our new approach, as well as for a real-world dataset from a concrete application.",
    pdf = "http://dx.doi.org10.1109/TVCG.2007.70633",
    images = "images/fuchs08parallel.jpg, images/fuchs08parallel1.jpg",
    thumbnails = "images/fuchs08parallel_thumb.jpg, images/fuchs08parallel1_thumb.jpg",
    keywords = "Time-Varying Data Visualization, Vortex Feature Detection",
    url = "http://www.cg.tuwien.ac.at/research/publications/2008/fuchs_raphael_2007_par/"
    }
    [Bibtex]
    @ARTICLE {Muigg08four,
    author = "Philipp Muigg and Johannes Kehrer and Steffen Oeltze and Harald Piringer and Helmut Doleisch and Bernhard Preim and Helwig Hauser",
    title = "A Four-level Focus+Context Approach to Interactive Visual Analysis of Temporal Features in Large Scientific Data",
    journal = "Computer Graphics Forum",
    year = "2008",
    volume = "27",
    number = "3",
    pages = "775--782",
    month = "may",
    abstract = "In this paper we present a new approach to the interactive visual analysis of time-dependent scientific data both from measurements as well as from computational simulation by visualizing a scalar function over time  for each of tenthousands or even millions of sample points. In order to cope  with overdrawing and cluttering, we introduce a new four-level method of focus+context visualization. Based on a setting of coordinated, multiple views (with linking and brushing), we integrate three different kinds of focus and also the context in every single view. Per data item we use three values (from  the unit interval each) to represent to which degree the data item is part of  the respective focus level. We present a color compositing scheme which is capable of expressing all three values in a meaningful way, taking semantics  and their relations amongst each other (in the context of our multiple linked  view setup) into account. Furthermore, we present additional image-based postprocessing methods to enhance the visualization of large sets of function graphs, including a texture-based technique based on line integral convolution  (LIC). We also propose advanced brushing techniques which are specific to the timedependent nature of the data (in order to brush patterns over time more efficiently). We demonstrate the usefulness of the new approach in the context of medical perfusion data.",
    images = "images/muigg08_eurovis3.jpg, images/muigg08_eurovis1.jpg, images/muigg08_eurovis2.jpg",
    thumbnails = "images/muigg08_eurovis3_thumb.jpg, images/muigg08_eurovis1_thumb.jpg, images/muigg08_eurovis2_thumb.jpg",
    event = "EuroVis 2008",
    location = "Eindhooven, Netherlands",
    url = "http://dx.doi.org/10.1111/j.1467-8659.2008.01207.x"
    }
    [VID] [Bibtex]
    @INPROCEEDINGS {balabanian08hierarchical,
    author = "Jean-Paul Balabanian and Martin Ystad and Ivan Viola and Arvid Lundervold and Helwig Hauser and Meister Eduard Gr{\"o}ller",
    title = "Hierarchical Volume Visualization of Brain Anatomy",
    booktitle = "Proceeding of Vision, Modeling and Visualization (VMV 2008)",
    year = "2008",
    pages = "313--322",
    month = "oct",
    abstract = "Scientific data-sets often come with an inherent hierarchical  structure such as functional substructures within organs. In this work we propose a new  visualization approach for volume data which is  augmented by the explicit representation of hierarchically structured data. The volumetric structures are organized in an interactive hierarchy view. Seamless zooming between data visualization, with volume rendering, and map viewing, for orientation and navigation within the hierarchy, facilitates deeper insight on multiple levels. The map shows all structures, organized in multiple hierarchy levels. Focusing on a selected node allows a visual analysis of a substructure as well as identifying its location in the hierarchy. The visual style of the  node in focus, its parent and child nodes are automatically  adapted during interaction to emphasize the embedding in the hierarchy. The hierarchy view is linked to a traditional  tree view. The value of this new visualization approach is demonstrated on segmented  MRI brain data consisting of hundreds of cortical and sub-cortical structures.",
    vid = "vids/balabanian08hierarchical.mp4",
    images = "images/balabanian08hierarchical1.jpg, images/balabanian08hierarchical2.jpg, images/balabanian08hierarchical3.jpg",
    thumbnails = "images/balabanian08hierarchical1_thumb.jpg, images/balabanian08hierarchical2_thumb.jpg, images/balabanian08hierarchical3_thumb.jpg, images/wmv_thumb.png",
    isbn = "978-3-89838-609-8",
    location = "Konstanz, Germany",
    url = "http://www.cg.tuwien.ac.at/research/publications/2008/balabanian-2008-hvv/",
    project = "illvis,medviz"
    }
    [Bibtex]
    @INPROCEEDINGS {piringer08comparing,
    author = "Harald Piringer and Wolfgang Berger and Helwig Hauser",
    title = "Quantifying and Comparing Features in High-Dimensional Datasets",
    booktitle = "Proceedings of the International Conference on Information Visualisation (IV 2008)",
    year = "2008",
    pages = "240--245",
    address = "Washington, DC, USA",
    month = "7",
    publisher = "IEEE Computer Society",
    abstract = "Linking and brushing is a proven approach to analyzing multi-dimensional datasets in the context of multiple coordinated views. Nevertheless, most of the respective visualization techniques only offer qualitative visual results. Many user tasks, however, also require precise quantitative results as, for example, offered by statistical analysis.  In succession of the useful Rank-by-Feature Framework, this paper describes a joint visual and statistical approach for guiding the user through a high-dimensional dataset by ranking  dimensions (1D case) and pairs of dimensions (2D case) according to statistical summaries. While the original Rank-by-Feature Framework is limited to global features, the most important novelty here is the concept to consider local features, i.e., data subsets defined by brushing in linked views. The ability to compare subsets to other subsets and subsets to the whole dataset in the context of a large number of dimensions significantly extends the benefits of the approach especially in later stages of an exploratory data analysis. A case study illustrates the workflow by analyzing counts of keywords for classifying e-mails as spam or no-spam.",
    images = "images/piringer08comparing1.png, images/piringer08comparing2.png, images/piringer08comparing3.png",
    thumbnails = "images/piringer08comparing1_thumb.png, images/piringer08comparing2_thumb.jpg, images/piringer08comparing3_thumb.png",
    location = "London, UK",
    url = "http://dx.doi.org/10.1109/IV.2008.17"
    }
    [Bibtex]
    @INPROCEEDINGS {matkovic08comVis,
    author = "Kresimir Matkovic and Wolfgang Freiler and Denis Gracanin and Helwig Hauser",
    title = "ComVis: a Coordinated Multiple Views System for Prototyping New Visualization Technology",
    booktitle = "Proceedings of the International Conference on Information Visualisation (IV 2008)",
    year = "2008",
    pages = "215--220",
    address = "Washington, DC, USA",
    month = "7",
    publisher = "IEEE Computer Society",
    abstract = "There is a large number of interactive visualization tools, however no universal tool exists that covers all relevant aspects for all possible application domains. We have developed a tool, ComVIs, which was intended to be used as a research prototype for new visualization techniques. We have identified some interesting aspects from developers and users point of view during tool development. In this paper we describe lessons learned during the process, and share our findings with visualization research community. Examples at the end prove the usefulness of the developed tool. One particular example, the concept of families of function graphs and application to analysis of fuel injection concludes the paper.",
    images = "images/matkovic08comvis.jpg",
    thumbnails = "images/matkovic08comvis_thumb.jpg",
    url = "http://dx.doi.org/10.1109/IV.2008.87",
    location = "London, UK"
    }
    [Bibtex]
    @ARTICLE {matkovic08visualSteering,
    author = "Kresimir Matkovic and Denis Gracanin and Mario Jelovic and Helwig Hauser",
    title = "Interactive Visual Steering - Rapid Visual Prototyping of a Common Rail Injection System",
    journal = "IEEE Transactions on Visualization and Computer Graphics (IEEE TVCG)",
    year = "2008",
    volume = "14",
    number = "6",
    pages = "1699--1706",
    month = "Oct",
    abstract = "Interactive steering with visualization has been a common goal of the visualization research community for twenty years, but it is rarely ever realized in practice. In this paper we describe a successful realization of a tightly coupled steering loop, integrating new simulation technology and interactive visual analysis in a prototyping environment for automotive industry system design. Due to increasing pressure on car manufacturers to meet new emission regulations, to improve efficiency, and to reduce noise, both simulation  and visualization are pushed to their limits. Automotive system components, such as the powertrain system or the injection system, have an increasing number of parameters, and new design approaches are required. It is no longer possible to optimize such a system solely based on experience or forward optimization. By coupling interactive visualization with the simulation back-end (computational steering), it is now possible to quickly prototype a new system, starting from a non-optimized initial prototype and the corresponding simulation model. The prototyping continues through the refinement of the simulation model, of the simulation parameters and through trial-and-error attempts to an optimized solution. The ability to early see the first results from a multidimensional simulation space -- thousands of simulations are run for a multidimensional variety of input parameters --  and to quickly go back into the simulation and request more runs in particular parameter regions of interest significantly improves the prototyping process and provides a deeper understanding of the system behavior. The excellent results which we achieved for the common rail injection system strongly suggest that our approach has a great potential of being generalized to other, similar scenarios.",
    images = "images/matkovic08vis.png, images/matkovic08vis1.png, images/matkovic08vis3.png, images/matkovic08vis4.png",
    thumbnails = "images/matkovic08vis_thumb.png, images/matkovic08vis1_thumb.png, images/matkovic08vis3_thumb.png, images/matkovic08vis4_thumb.png",
    event = "IEEE Visualization 2008",
    location = "Columbus, Ohio, USA",
    url = "http://dx.doi.org/10.1109/TVCG.2008.145"
    }

2007

    [Bibtex]
    @ARTICLE {muigg07hybrid,
    author = "Philipp Muigg and Markus Hadwiger and Helmut Doleisch and Helwig Hauser",
    title = "Scalable Hybrid Unstructured and Structured Grid Raycasting",
    journal = "IEEE Transactions on Visualization and Computer Graphics (IEEE TVCG)",
    year = "2007",
    volume = "13",
    number = "6",
    pages = "1592--1599",
    month = "nov",
    abstract = "This paper presents a scalable framework for real-time raycasting of large unstructured volumes that employs a hybrid bricking approach. It adaptively combines original unstructured bricks in important (focus) regions, with structured bricks that are resampled on demand in less important (context) regions. The basis of this focus+context approach is interactive specification of a scalar degree-of-interest (DOI) function. Thus, rendering always considers two volumes simultaneously: a scalar data volume, and the current DOI volume. The crucial problem of visibility sorting is solved by raycasting individual bricks and compositing in visibility order from front to back. In order to minimize visual errors at the grid boundary, it is always rendered accurately, even for resampled bricks. A variety of different rendering modes can be combined, including contour enhancement. A very important property of our approach is that it supports a variety of cell types natively, i.e., it is not constrained to tetrahedral grids, even when interpolation within cells is used. Moreover, our framework can handle multi-variate data, e.g., multiple scalar channels such as temperature or pressure, as well as time-dependent data. The combination of unstructured and structured bricks with different quality characteristics such as the type of interpolation or resampling resolution in conjunction with custom texture memory management yields a very scalable system.",
    images = "images/muigg07hybrid.png, images/muigg07hybrid1.png, images/muigg07hybrid2.png",
    thumbnails = "images/muigg07hybrid_thumb.png, images/muigg07hybrid1_thumb.png, images/muigg07hybrid2_thumb.png",
    issn = "1077-2626",
    location = "Sacramento, California, USA",
    event = "IEEE Visualization 2007",
    url = "http://dx.doi.org/10.1109/TVCG.2007.70588",
    publisher = "IEEE Computer Society"
    }
    [Bibtex]
    @ARTICLE {oeltze07perfusion,
    author = "Steffen Oeltze and Helmut Doleisch and Helwig Hauser and Philipp Muigg and Bernhard Preim",
    title = "Interactive Visual Analysis of Perfusion Data",
    journal = "IEEE Transactions on Visualization and Computer Graphics (IEEE TVCG)",
    year = "2007",
    volume = "13",
    number = "6",
    pages = "1392-1399",
    month = "nov",
    abstract = "Perfusion data are dynamic medical image data which characterize the regional blood flow in human tissue. These data bear a great potential in medical diagnosis, since diseases can be better distinguished and detected at an earlier stage compared to static image data. The wide-spread use of perfusion data is hampered by the lack of efficient evaluation methods. For each voxel, a time-intensity curve characterizes the enhancement of a contrast agent. Parameters derived from these curves characterize the perfusion and have to be integrated for diagnosis. The diagnostic evaluation of this multi-field data is challenging and time-consuming due to its complexity. For the visual analysis of such datasets, feature-based approaches allow to reduce the amount of data and direct the user to suspicious areas. We present an interactive visual analysis approach for the evaluation of perfusion data. For this purpose, we integrate statistical methods and interactive feature specification. Correlation analysis and Principal Component Analysis (PCA) are applied for dimensionreduction and to achieve a better understanding of the inter-parameter relations. Multiple, linked views facilitate the definition of features by brushing multiple dimensions. The specification result is linked to all views establishing a focus+context style of visualization in 3D. We discuss our approach with respect to clinical datasets from the three major application areas: ischemic stroke diagnosis, breast tumor diagnosis, as well as the diagnosis of the coronary heart disease (CHD). It turns out that the significance of perfusion parameters strongly depends on the individual patient, scanning parameters, and data pre-processing.",
    images = "images/oeltze07perfusion.png, images/oeltze07perfusion1.png",
    thumbnails = "images/oeltze07perfusion_thumb.png, images/oeltze07perfusion1_thumb.png",
    issn = "1077-2626",
    publisher = "IEEE Computer Society",
    location = "Sacramento, California, USA",
    event = "IEEE Visualization 2007",
    url = "http://dx.doi.org/10.1109/TVCG.2007.70569"
    }
    [PDF] [Bibtex]
    @ARTICLE {Lampe2007TMV,
    author = "Ove Daae Lampe and Ivan Viola and Nathalie Reuter and Helwig Hauser",
    title = "Two-Level Approach to Efficient Visualization of Protein Dynamics",
    journal = "IEEE Transactions on Visualization and Computer Graphics (IEEE TVCG)",
    year = "2007",
    volume = "13",
    number = "6",
    pages = "1616--1623",
    month = "nov",
    abstract = "Proteins are highly flexible and large amplitude deformations of their structure, also called slow dynamics, are often decisive to their function. We present a two-level rendering approach that enables visualization of slow dynamics of large protein assemblies. Our approach is aligned with a hierarchical model of large scale molecules. Instead of constantly updating positions of large amounts of atoms, we update the position and rotation of residues, i.e., higher level building blocks of a protein. Residues are represented by one vertex only indicating its position and additional information defining the rotation. The atoms in the residues are generated on-the-fly on the GPU, exploiting the new graphics hardware geometry shader capabilities. Moreover, we represent the atoms by billboards instead of tessellated spheres. Our representation is then significantly faster and pixel precise. We demonstrate the usefulness of our new approach in the context of our collaborative bioinformatics project.",
    pdf = "pdfs/lampe_2007_tvcg.pdf",
    images = "images/moleculevr_single_mol-20070329-0857270.jpeg, images/color_per_chain.jpeg, images/nanoThickWallSleveCHonly_anaglyph.jpeg, images/phi29Contour.jpeg, images/python 2007-06-25 23-07-54-84.jpeg, images/python 2007-06-25 23-31-18-14.jpeg",
    thumbnails = "images/moleculevr_single_mol-20070329-0857270_thumb.jpeg, images/color_per_chain_thumb.jpeg, images/nanoThickWallSleveCHonly_anaglyph_thumb.jpeg, images/phi29Contour_thumb.jpeg, images/python 2007-06-25 23-07-54-84_thumb.jpeg, images/python 2007-06-25 23-31-18-14_thumb.jpeg",
    event = "IEEE Visualization 2007",
    location = "Sacramento, California, USA",
    issn = "1077-2626"
    }
    [Bibtex]
    @INPROCEEDINGS {buerger2007star,
    author = "Raphael B{\"u}rger and Helwig Hauser",
    title = "Visualization of Multi-variate Scientific Data",
    booktitle = "EuroGraphics 2007 State of the Art Reports (STARs)",
    year = "2007",
    pages = "117--134",
    abstract = "In this state-of-the-art report we discuss relevant research works related to the visualization of complex, multi-variate data. We focus on ''non-classical'' approaches, i.e. approaches which haven't been discussed in previous related reports, and we highlight techniques which potentially lead towards new directions in visualization research. We discuss how different techniques take effect at specific stages of the visualization pipeline and how they apply to multi-variate data sets being composed of scalars, vectors, and tensors. We also provide a categorization of these techniques in the aim for a better overview of related approaches. In the second part of this paper we take a look at recent techniques that are useful for the visualization of complex data sets either because they are general purpose or because they can be adapted to specific problems.",
    images = "images/buerger07star1.png, images/buerger07star2.png",
    thumbnails = "images/buerger07star1_thumb.png, images/buerger07star2_thumb.png",
    isbn = "1017-4656",
    keywords = "scientific data, multi-variate data",
    event = "EuroGraphics 2007",
    location = "Prague, Czech Republic",
    url = "http://www.cg.tuwien.ac.at/research/publications/2007/buerger-2007-star/"
    }
    [Bibtex]
    @INPROCEEDINGS {matkovic07color_lines_view,
    author = "Kresimir Matkovic and Denis Gracanin and Zoltan Konyha and Helwig Hauser",
    title = "Color Lines View: An Approach to Visualization of Families of Function Graphs",
    booktitle = "Proceeding of the 11th International Conference on Information Visualization (IV 2007)",
    year = "2007",
    pages = "59-64",
    month = "7",
    abstract = "Data sets often include information that can be represented as a mapping that describes how a dependent variable depends on an independent variable. Such a mapping, usually represented as a function graph, can be parameterized to provide a family of function graphs. The challenge is how to efficiently aggregate individual function graph views to represent the whole family and allow visual analysis and search for patterns. We propose a novel view, called the color lines view, which provides a two dimensional, rectangular view where each line represents a single function graph. The points on the line correspond to values of the independent variable. The point colors represent the value of the dependent variable. The lines, placed next to each other in parallel, show a family of function graphs. The color lines view offers sorting and brushing features which support visual analysis procedures that are difficult to perform with previously existing views.",
    images = "images/matkovic07color_lines_view1.png, images/matkovic07color_lines_view.png",
    thumbnails = "images/matkovic07color_lines_view1_thumb.png, images/matkovic07color_lines_view_thumb.png",
    location = "Z{\"u}rich, Switzerland",
    url = "http://dx.doi.org/10.1109/IV.2007.35"
    }
    [Bibtex]
    @INPROCEEDINGS {konyha07timing_chain,
    author = "Zoltan Konyha and Kresimir Matkovix and Denis Graxanin and Mario Duras and Josip Juric and Helwig Hauser",
    title = "Interactive Visual Analysis of a Timing Chain Drive Using Segmented Curve View and other Coordinated Views",
    booktitle = "Proceeding of the 5th Intern. Conference on Coordinated \& Multiple Views in Exploratory Visualization (CMV 2007)",
    year = "2007",
    pages = "3-15",
    month = "7",
    abstract = "A timing chain drive transfers motion from the engine's crankshaft to the camshaft that operates the valves. The design process of timing chain drives involves computer simulation of many design variants in order to find an optimum. Most of the simulation results can be represented as families of function graphs (data series). Previously, the analysis of those results was based on static 2D diagrams and animated 3D visualizations. They were suitable for the detailed analysis of a few simulation variants, but not for the comparison of many cases. In this paper we propose a new approach to the analysis based on coordinated linked views and advanced brushing features. Our proposed method supports the interactive analysis of many design variants. We introduce a novel view, called segmented curve view, which can display distributions in families of function graphs. The segmented curve view combines individual function graphs where for a fixed value of the independent variable, a bar extends from minimum to maximum values across the family of function graphs. Each bar is divided into segments (bins) with a color that represents the number of function graphs with the value in that segment. In the case study, we demonstrate that the new view combined with traditional; views provides a strong support for the interactive visual exploration and analysis of a real world timing chain design problem.",
    images = "images/konya07timing_chain2.png, images/konya07timing_chain.png, images/konya07timing_chain1.png",
    thumbnails = "images/konya07timing_chain2_thumb.png, images/konya07timing_chain_thumb.png, images/konya07timing_chain1_thumb.png",
    location = "Z{\"u}rich, Switzerland",
    url = "http://dx.doi.org/10.1109/CMV.2007.13"
    }

2003

    [PDF] [YT] [Bibtex]
    @INPROCEEDINGS {Bruckner-2003-IWN,
    author = "Stefan Bruckner and Dieter Schmalstieg and Helwig Hauser and Meister Eduard Gr{\"o}ller",
    title = "The Inverse Warp: Non-Invasive Integration of Shear-Warp Volume Rendering into Polygon Rendering Pipelines",
    booktitle = "Proceedings of VMV 2003",
    year = "2003",
    editor = "T. Ertl, B. Girod, G. Greiner, H. Niemann, H.-P. Seidel, E. Steinbach, R. Westermann",
    pages = "529--536",
    month = "nov",
    publisher = "infix",
    abstract = "In this paper, a simple and efficient solution for combining shear-warp  volume rendering and the hardware graphics pipeline is presented.  The approach applies an inverse warp transformation to the Z-Buffer,  containing the rendered geometry. This information is used for combining  geometry and volume data during compositing. We present applications  of this concept which include hybrid volume rendering, i.e., concurrent  rendering of polygonal objects and volume data, and volume clipping  on convex clipping regions. Furthermore, it can be used to efficiently  define regions with different rendering modes and transfer functions  for focus+context volume rendering. Empirical results show that the  approach has very low impact on performance.",
    pdf = "pdfs/Bruckner-2003-IWN.pdf",
    images = "images/Bruckner-2003-IWN.jpg",
    thumbnails = "images/Bruckner-2003-IWN.png",
    youtube = "https://www.youtube.com/watch?v=l_49gLBUO3E,https://www.youtube.com/watch?v=zmWQfUs3Bmc,https://www.youtube.com/watch?v=qFwv-Ru8Ftc",
    affiliation = "tuwien",
    isbn = "3898380483",
    keywords = "focus+context techniques, clipping, hybrid volume rendering",
    url = "http://www.cg.tuwien.ac.at/research/publications/2003/Bruckner-2003-The/"
    }