D04 | Quantitative Aspects of Immersive Analytics for the Life Sciences

Prof. Dr. Falk Schreiber, University of Konstanz
Email | Website

Falk Schreiber

Prof. Marc Ernst, Ulm University
Email | Website

Marc Ernst

Michael Aichem, University of Konstanz – Email | Website

Sabrina Jaeger-Honz, University of Konstanz – Email | Website

Stefan Feyer, University of Konstanz – Email | Website

Wilhelm Kerle-Malcharek, University of Konstanz – Email | Website (from Dec 2023)

Immersive Analytics (IA) is an emerging field that studies technologies facilitating a deep cognitive, perceptual and/or emotional involvement of humans when understanding and reasoning with data. The goal of this project is to investigate and quantify the impact of such technologies on immersion, and the role of immersion for data analytics. We aim to further develop the Immersive Analytics methodology and investigate the applicability of IA approaches to research tasks in the life sciences, with a particular focus on quantitative aspects of immersive analytics. We will design  immersive environments for selected applications of the life sciences  and develop new methodologies that allow us to put the human in the loop for an immersive experience during an analytics workflow.

Research Questions

How can we quantify immersion in an analytics process, and how can we quantify the impact of immersion?

How can we best support analytics and decision making tasks with Immersive Analytics approaches facilitated by new technologies?

What are new potentials and benefits that IA brings for tasks in the life sciences, and how can we quantify them?

Fig. 1: Immersive Analytics (IA).

Publications

  1. L. Joos, S. Jaeger-Honz, F. Schreiber, D. A. Keim, and K. Klein, “Visual Comparison of Networks in VR,” IEEE Transactions on Visualization and Computer Graphics, vol. 28, no. 11, Art. no. 11, 2022, doi: 10.1109/TVCG.2022.3203001.
  2. F. Schreiber and D. Weiskopf, “Quantitative Visual Computing,” it - Information Technology, vol. 64, no. 4–5, Art. no. 4–5, 2022, doi: doi:10.1515/itit-2022-0048.
  3. Y. Zhang, K. Klein, O. Deussen, T. Gutschlag, and S. Storandt, “Robust Visualization of Trajectory Data,” it - Information Technology, vol. 64, no. 4–5, Art. no. 4–5, 2022, doi: doi:10.1515/itit-2022-0036.
  4. D. Bienroth et al., “Spatially resolved transcriptomics in immersive environments,” Visual Computing for Industry, Biomedicine, and Art, vol. 5, no. 1, Art. no. 1, 2022, doi: 10.1186/s42492-021-00098-6.
  5. K. Klein, M. Sedlmair, and F. Schreiber, “Immersive Analytics: An Overview,” it - Information Technology, vol. 64, no. 4–5, Art. no. 4–5, 2022, doi: doi:10.1515/itit-2022-0037.
  6. D. Garkov, C. Müller, M. Braun, D. Weiskopf, and F. Schreiber, “Research Data Curation in Visualization: Position Paper,” in 2022 IEEE Evaluation and Beyond - Methodological Approaches for Visualization (BELIV), M. Sedlmair, Ed., in 2022 IEEE Evaluation and Beyond - Methodological Approaches for Visualization (BELIV). 2022, pp. 56–65. doi: 10.1109/BELIV57783.2022.00011.
  7. M. Aichem et al., “Visual exploration of large metabolic models,” Bioinformatics, vol. 37, no. 23, Art. no. 23, May 2021, doi: 10.1093/bioinformatics/btab335.
  8. K. Klein et al., “Visual analytics of sensor movement data for cheetah behaviour analysis,” Journal of Visualization, 2021, doi: 10.1007/s12650-021-00742-6.
  9. K. Klein, M. Aichem, Y. Zhang, S. Erk, B. Sommer, and F. Schreiber, “TEAMwISE : synchronised immersive environments for exploration and analysis of animal behaviour,” Journal of Visualization, 2021, doi: 10.1007/s12650-021-00746-2.
  10. M. Kraus et al., “Immersive Analytics with Abstract 3D Visualizations: A Survey,” Computer Graphics Forum, 2021, doi: https://doi.org/10.1111/cgf.14430.
  11. K. Klein, D. Garkov, S. Rütschlin, T. Böttcher, and F. Schreiber, “QSDB—a graphical Quorum Sensing Database,” Database, vol. 2021, no. 2021, Art. no. 2021, Nov. 2021, doi: 10.1093/database/baab058.
  12. M. Kraus, K. Klein, J. Fuchs, D. A. Keim, F. Schreiber, and M. Sedlmair, “The Value of Immersive Visualization,” IEEE Computer Graphics and Applications (CG&A), vol. 41, no. 4, Art. no. 4, 2021, doi: 10.1109/MCG.2021.3075258.
  13. B. Sommer et al., “Tiled Stereoscopic 3D Display Wall - Concept, Applications and Evaluation,” Electronic Imaging, vol. 2019, no. 3, Art. no. 3, 2019, doi: 10.2352/ISSN.2470-1173.2019.3.SDA-641.
  14. K. Klein, M. Aichem, B. Sommer, S. Erk, Y. Zhang, and F. Schreiber, “TEAMwISE: Synchronised Immersive Environments for Exploration and Analysis of Movement Data,” in Proceedings of the ACM Symposium on Visual Information Communication and Interaction (VINCI), in Proceedings of the ACM Symposium on Visual Information Communication and Interaction (VINCI). ACM, 2019, pp. 9:1-9:5. doi: 10.1145/3356422.3356450.
  15. S. Jaeger et al., “Challenges for Brain Data Analysis in VR Environments,” in 2019 IEEE Pacific Visualization Symposium (PacificVis), in 2019 IEEE Pacific Visualization Symposium (PacificVis). 2019, pp. 42–46. doi: 10.1109/PacificVis.2019.00013.
  16. K. Klein et al., “Fly with the flock : immersive solutions for animal movement visualization and analytics,” Journal of the Royal Society Interface, vol. 16, no. 153, Art. no. 153, 2019, doi: 10.1098/rsif.2018.0794.
  17. K. Klein et al., “Visual Analytics for Cheetah Behaviour Analysis.,” in VINCI, in VINCI. ACM, 2019, pp. 16:1-16:8. [Online]. Available: http://dblp.uni-trier.de/db/conf/vinci/vinci2019.html#0001JMWHBS19
  18. V. Yoghourdjian, T. Dwyer, K. Klein, K. Marriott, and M. Wybrow, “Graph Thumbnails: Identifying and Comparing Multiple Graphs at a Glance,” IEEE Transactions on Visualization and Computer Graphics, vol. 24, no. 12, Art. no. 12, 2018, doi: 10.1109/TVCG.2018.2790961.
  19. M. Klapperstueck et al., “Contextuwall: Multi-site Collaboration Using Display Walls,” Journal of Visual Languages & Computing, vol. 46, pp. 35–42, 2018, doi: 10.1016/j.jvlc.2017.10.002.
  20. K. Marriott et al., Immersive Analytics, vol. 11190. in Lecture Notes in Computer Science (LNCS), vol. 11190. Springer International Publishing, 2018. doi: 10.1007/978-3-030-01388-2.
  21. Y. Zhu et al., “Genome-scale Metabolic Modeling of Responses to Polymyxins in Pseudomonas Aeruginosa,” GigaScience, vol. 7, no. 4, Art. no. 4, 2018, doi: 10.1093/gigascience/giy021.
  22. M. Ghaffar et al., “3D Modelling and Visualisation of Heterogeneous Cell Membranes in Blender,” in Proceedings of the 11th International Symposium on Visual Information Communication and Interaction, in Proceedings of the 11th International Symposium on Visual Information Communication and Interaction. Växjö, Sweden: Association for Computing Machinery, 2018, pp. 64–71. doi: 10.1145/3231622.3231639.
  23. M. de Ridder, K. Klein, and J. Kim, “A Review and Outlook on Visual Analytics for Uncertainties in Functional Magnetic Resonance Imaging,” Brain Informatics, vol. 5, no. 2, Art. no. 2, 2018, doi: 10.1186/s40708-018-0083-0.
  24. M. de Ridder, K. Klein, and J. Kim, “Temporaltracks: Visual Analytics for Exploration of 4D fMRI Time-series Coactivation,” in Proceedings of the Computer Graphics International Conference (CGI), X. Mao, D. Thalmann, and M. L. Gavrilova, Eds., in Proceedings of the Computer Graphics International Conference (CGI). ACM, 2017, pp. 13:1-13:6. doi: 10.1145/3095140.3095153.
  25. H. T. Nim et al., “Design Considerations for Immersive Analytics of Bird Movements Obtained by Miniaturised GPS Sensors,” in Proceedings of the Eurographics Workshop on Visual Computing for Biology and Medicine (VCBM), in Proceedings of the Eurographics Workshop on Visual Computing for Biology and Medicine (VCBM). Eurographics Association, 2017. doi: 10.2312/vcbm.20171234.
  26. T. Chandler et al., “Immersive Analytics,” in Proceedings of the IEEE Symposium on Big Data Visual Analytics (BDVA), in Proceedings of the IEEE Symposium on Big Data Visual Analytics (BDVA). IEEE, 2015, pp. 73–80. doi: 10.1109/BDVA.2015.7314296.

Project Group A

Models and Measures

 

Completed

 

Project Group B

Adaptive Algorithms

 

Completed

 

Project Group C

Interaction

 

Completed

 

Project Group D

Applications

 

Completed