2026
@article{bib:jiang:2026,
author = { Jiang, Qinyue and Merkus, Veerle A. and Lindelauf, Ciska and Krijgsman, Jens and Guo, Nannan and Ouboter, Laura F. and Höllt, Thomas and Voorneveld, Philip W. and Meijer-Boekel, Caroline R. and Koning, Frits and van der Meulen-de Jong, Andrea E and Pascutti, Maria Fernanda and van Unen, Vincent },
title = { Tissue-embedded CD4+ plasticity defines mucosal immunity in inflammatory bowel disease },
journal = { Mucosal Immunology },
year = { 2026 },
pages = { 100369 },
doi = { 10.1016/j.mucimm.2026.100369 },
abstract = {CD4+ T helper (Th) cell responses to commensal microbiota are linked to Inflammatory Bowel Disease (IBD), yet how Th programs coexist and evolve in human tissues remains poorly defined. Here, we profiled CD4+ memory T cells in intestinal biopsies using immunological and histological approaches to map phenotypes, functional states, and spatial relationships across disease states. A marked expansion of CD4+ T cells concomitant with a RORγt+ Th population with elevated T-bet expression was linked to the progression of inflammation. Moreover, Foxp3+ cells co-expressing RORγt emerged within the inflamed niche, indicating regulatory–Th17 plasticity. Trajectory visualization revealed a potential branched differentiation path toward regulatory or tissue-resident Th17-like fates, with both termini expressing activation and proliferation markers. Correlation network analysis connected pro-inflammatory CD4+ states to T-bet+Granzyme-B+ CD8+ subsets, indicating coordination between helper and cytotoxic lineages. Histology revealed increased T-cell infiltration and spatial segregation of tissue-resident subsets, with CD103+CD4+ T cells localized mainly in the lamina propria and CD103+CD8+ T cells near the epithelium. TCR stimulation during active disease revealed broad suppression of CD4+ pro-inflammatory cytokines alongside Foxp3+ expansion. Conversely, HLA-DR+CD38+ memory subset retained multifunctionality, producing elevated levels of pro-inflammatory cytokines. Together, these results define a dynamic, tissue-embedded CD4 T-cell landscape in IBD.},
pdf = {pdfs/2026-Jiang-MucosalImmunology.pdf},
images = {images/2026-Jiang-MucosalImmunology.png},
thumbnails = {images/2026-Jiang-MucosalImmunology-icon.png},
}
@article{balaka2026hamcat,
author = {Balaka, Hanna and Hauser, Helwig and Garrison, Laura Ann},
title = {HamCat: Ego-Centric Relationship Exploration for Multidimensional Categorical Data},
year = {2026},
journal = {Computer Graphics Forum},
pages = {e70440},
doi = {10.1111/cgf.70440},
abstract = {We introduce HamCat, a novel visualization method for exploring and analyzing multidimensional categorical survey data. Typical visualization approaches for multidimensional categorical data do not support simultaneous analysis of attributes and items, nor do they allow for in-depth similarity analysis of an entire dataset from the perspective of a specific reference point. HamCat, in contrast, aims to facilitate detailed analysis of multidimensional categorical data across both attributes and items. Our approach builds on the concept of a Hamming ball combined with a force-directed layout to support ego-centric, user-steered analysis of inter-item and inter-attribute relationships in multidimensional categorical survey data. In addition, our method supports the inclusion and nuanced visualization of missingness. We illustrate the value of HamCat through two case studies. The first case focuses on a survey on wellbeing collected by the European Social Survey, while the second is an expert-driven study for a survey on sense of belonging in computer science higher education. These case studies show how HamCat complements existing analysis workflows to reveal relationships and item groupings across attributes that are not easily discoverable through conventional means. Supplementary materials for our method are available at https://osf.io/uz2jv/.},
pdf = {pdfs/balaka2026hamcat.pdf},
images = {images/balaka2026hamcat.png},
thumbnails = {images/balaka2026hamcat_thumb.png},
}
@inproceedings{saharan2026normative,
author = {Saharan, Shehryar and Al-Hazwani, Ibrahim and Meyer, Miriah and Garrison, Laura Ann},
title = {A critical reflection on the values and assumptions
in data visualization},
booktitle = {Proc CHI 2026"},
year = {2026},
numpages = {8},
publisher = {ACM},
address = {New York},
doi = {10.48550/arXiv.2602.22051},
abstract = {Visualization has matured into an established research field, producing widely adopted tools, design frameworks, and empirical foundations. As the field has grown, ideas from outside computer science have increasingly entered visualization discourse, questioning the fundamental values and assumptions on which visualization research stands. In this short position paper, we examine a set of values that we see underlying the seminal works of Jacques Bertin, John Tukey, Leland Wilkinson, Colin Ware, and Tamara Munzner. We articulate three prominent values in these texts — universality, objectivity, and efficiency — and examine how these values permeate visualization tools, curricula, and research practices. We situate these values within a broader set of critiques that call for more diverse priorities and viewpoints. By articulating these tensions, we call for our community to embrace a more pluralistic range of values to shape our future visualization tools and guidelines.},
pdf = {pdfs/saharan2026normative.pdf},
images = {images/saharan2026normative.png},
thumbnails = {images/saharan2026normative_thumb.png},
}2025
[Bibtex] @inproceedings{balaka2025mobaexplorer,
title = {The MoBa GWAS Explorer: Designing Approachable Visualizations of GWAS Data for a Mixed Audience},
author = {Balaka, Hanna and Vaudel, Marc and Garrison, Laura},
booktitle = {Proceedings of VAHC workshop at IEEE VIS},
year = {2025},
numpages = {7},
abstract = {Public health studies generate extensive datasets providing important insights into human health. The Norwegian Mother, Father, and Child Cohort Study (MoBa) is a longitudinal cohort study capturing information on pregnancy and early childhood. This information helps uncover the genetic underpinnings of traits or diseases drawing interest from researchers in public health. Non-experts are also attracted to the study, both to understand their contributions as data donors and relevant health determinants. However, the complexity of MoBa data hinders its exploration, analysis, and dissemination. We present a design study exploring the needs and uses of the MoBa dataset in a mixed-user context and introducing the MoBa GWAS Explorer, a web-based visual tool for exploration and analysis of MoBa data by a mixed audience. This tool supports experts in exploring and analyzing MoBa data interactively. Though designed primarily for researchers, we explored the potential for onboarding strategies to make this tool more approachable for non-experts. We conducted a qualitative study with both user groups to evaluate their experience with the tool and its usability. Our evaluation indicates that the application, along with the integrated onboarding, has potential to serve both expert and non-expert groups. Supplementary materials for this study are available at https://osf.io/k5bvj/.},
pdf = {pdfs/balaka2025mobaexplorer.pdf},
thumbnails = {images/balaka2025mobaexplorer_thumb.png},
images = {images/balaka2025mobaexplorer.png},
git = {https://osf.io/k5bvj/},
}
@inproceedings{zhang2025melodification,
title = {Data Melodification FM: Where Musical Rhetoric Meets Sonification},
author = {Zhang, Ke Er Amy and Grellscheid, David and Garrison, Laura},
booktitle = {Proceedings of alt.VIS workshop at IEEE VIS},
year = {2025},
numpages = {5},
eprint = {2510.00222},
archiveprefix = {arXiv},
primaryclass = {cs.HC},
doi = {10.48550/arXiv.2510.00222},
abstract = {We propose a design space for data melodification, where standard visualization idioms and fundamental data characteristics map to rhetorical devices of music for a more affective experience of data. Traditional data sonification transforms data into sound by mapping it to different parameters such as pitch, volume, and duration. Often and regrettably, this mapping leaves behind melody, harmony, rhythm and other musical devices that compose the centuries-long persuasive and expressive power of music. What results is the occasional, unintentional sense of tinnitus and horror film-like impending doom caused by a disconnect between the semantics of data and sound. Through this work we ask, can the aestheticization of sonification through (classical) music theory make data simultaneously accessible, meaningful, and pleasing to one’s ears?},
pdf = {pdfs/zhang2025melodification.pdf},
thumbnails = {images/zhang2025melodification_thumb.png},
images = {images/zhang2025melodification.png},
git = {https://osf.io/zx3ac/},
}
@article{ziman2025genaixbiomedvis,
title={"It looks sexy but it's wrong." Tensions in creativity and accuracy using genAI for biomedical visualization},
author = {Ziman, Roxanne and Saharan, Shehryar and McGill, Ga\"{e}l and Garrison, Laura},
journal = {arXiv, IEEE Transactions on Visualization and Computer Graphics--in press},
year = {2025},
numpages = {11},
publisher = {arXiv},
doi = {10.48550/arXiv.2507.14494},
abstract = {We contribute an in-depth analysis of the workflows and tensions arising from generative AI (genAI) use in biomedical visualization (BioMedVis). Although genAI affords facile production of aesthetic visuals for biological and medical content, the architecture of these tools fundamentally limits the accuracy and trustworthiness of the depicted information, from imaginary (or fanciful) molecules to alien anatomy. Through 17 interviews with a diverse group of practitioners and researchers, we qualitatively analyze the concerns and values driving genAI (dis)use for the visual representation of spatially-oriented biomedical data. We find that BioMedVis experts, both in roles as developers and designers, use genAI tools at different stages of their daily workflows and hold attitudes ranging from enthusiastic adopters to skeptical avoiders of genAI. In contrasting the current use and perspectives on genAI observed in our study with predictions towards genAI in the visualization pipeline from prior work, our refocus the discussion of genAI's effects on projects in visualization in the here and now with its respective opportunities and pitfalls for future visualization research. At a time when public trust in science is in jeopardy, we are reminded to first do no harm, not just in biomedical visualization but in science communication more broadly. Our observations reaffirm the necessity of human intervention for empathetic design and assessment of accurate scientific visuals.},
pdf = {pdfs/ziman2025genaixbiomedvis.pdf},
images = {images/ziman2025itlookssexy.png},
thumbnails = {images/ziman2025itlookssexy_thumb.png},
project = {VIDI},
git = {https://osf.io/mbw86/}
}![[YT]](https://vis.uib.no/wp-content/papercite-data/images/youtube.png)
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