Visualization of Biomedical Data - Shaping the Future and Building Bridges (Dagstuhl Seminar 23451)

Authors Katja Bühler, Barbora Kozlíková, Michael Krone, Cagatay Turkay, Ramasamy Pathmanaban and all authors of the abstracts in this report

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Author Details

Katja Bühler
  • VRVis - Wien, AT
Barbora Kozlíková
  • Masaryk University - Brno, CZ
Michael Krone
  • Universität Tübingen, DE
Cagatay Turkay
  • University of Warwick - Coventry, GB
Ramasamy Pathmanaban
  • Ghent University, BE
and all authors of the abstracts in this report

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Katja Bühler, Barbora Kozlíková, Michael Krone, Cagatay Turkay, and Ramasamy Pathmanaban. Visualization of Biomedical Data - Shaping the Future and Building Bridges (Dagstuhl Seminar 23451). In Dagstuhl Reports, Volume 13, Issue 11, pp. 1-19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)


The last decades of advancements in biology and medicine and their interplay with the visualization domain proved that these fields are naturally tightly connected. Visualization plays an irreplaceable role in making, understanding, and communicating biological and medical discoveries. The goal of Dagstuhl Seminar 23451 was to serve as an interdisciplinary platform for a collective approach to the contemporary and emerging future scientific and societal challenges at the intersection of visualization, biology, and medicine in the context of increasing complexity in data, data analytics, and data-intensive science communication. Building on the success of the previous seminars and our ongoing community efforts, participants of this seminar critically tackled highly relevant scientific questions of interest to the bioinformatics, medical informatics, and visualization communities. These challenges include the increasing complexity and amount of data that are produced in biomedical research, the role of visualization in supporting interdisciplinary research and in communicating biological and medical discoveries to experts and broader audiences, and visualization for a user-centric and trustworthy explainable AI in biomedical applications. The seminar was an important step towards strengthening and widening a sustainable and vibrant interdisciplinary community of biological, medical, and visualization researchers from both academia and industry through an in-depth, comprehensive, and inclusive exchange of ideas, experiences, and perspectives. The identified key topics span methodological, technical, infrastructural, and societal challenges. The discussions and exchange of ideas revolved around the most pressing problems among the biological and biomedical domains and how these problems could be approached through data visualization, thus opening up room for innovation in designs and methodologies.

Subject Classification

ACM Subject Classification
  • Applied computing → Bioinformatics
  • Applied computing → Health informatics
  • Human-centered computing → Scientific visualization
  • Human-centered computing → Visual analytics
  • Human-centered computing → Information visualization
  • Human-centered computing → Visualization theory, concepts and paradigms
  • Human-centered computing → Visualization design and evaluation methods
  • Computing methodologies → Neural networks
  • biology
  • computational biology
  • interdisciplinary
  • medicine
  • visualization


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