@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 = "//visweek.org/visweek/2012/tutorial/interactive-visual-analysis-scientific-data",
pres = "pdfs/Hauser12VisTutorialPres01.pdf"
}