INF | Collaboration Infrastructure

Prof. Thomas ErtlFP2, University of Stuttgart
Email | Website

Prof. Falk Schreiber, University of Konstanz
Email | Website

Prof. Daniel WeiskopfFP3, University of Stuttgart
Email | Website

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Daniel Weiskopf
Falk Schreiber

There is no advisor for this project.

Dimitar Garkov, University of Konstanz – Email | Website

Project Collaboration Infrastructure (INF) supports the research projects across the consortium primarily in the areas of research data management (RDM) and data curation, shared resources, and virtual collaboration. RDM is essential for repeatable research, and even more for state-of-the-art research projects and consortia, where
infrastructure and coordination on a large scale are needed. Providing reliable storage and open access supports long-term outreach, open science, and trust in the scientific field. Shared resources (e.g., hard- and software) allows research groups to work with a large variety of advanced devices often not affordable for a single group, while sharing information (e.g., high-quality streaming of events) supports virtual collaboration and doctoral training across sites.

Fig. 1: Talk at the Powerwall at the University of Konstanz

Publications

  1. A. Niarakis et al., “Addressing barriers in comprehensiveness, accessibility, reusability, interoperability and reproducibility of computational models in systems biology,” Briefings in bioinformatics, vol. 23, no. 4, Art. no. 4, 2022, doi: 10.1093/bib/bbac212.
  2. D. Garkov, C. Müller, M. Braun, D. Weiskopf, and F. Schreiber, “Research Data Curation in Visualization: Position Paper,” in Proceedings of the Ninth Workshop on Evaluation and BEyond - methodoLogIcal approaches for Visualization (BELIV), 2022.
  3. C. Müller, M. Heinemann, D. Weiskopf, and T. Ertl, “Power Overwhelming: Quantifying the Energy Cost of Visualisation,” 2022.
  4. 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.
  5. M. Becher et al., “Situated Visual Analysis and Live Monitoring for Manufacturing,” IEEE Computer Graphics and Applications, pp. 1–1, 2022, doi: 10.1109/MCG.2022.3157961.
  6. 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.
  7. K. Schatz et al., “2019 IEEE Scientific Visualization Contest Winner: Visual Analysis of Structure Formation in Cosmic Evolution,” IEEE Computer Graphics and Applications, vol. 41, no. 6, Art. no. 6, 2021, doi: 10.1109/MCG.2020.3004613.
  8. F. Frieß, M. Becher, G. Reina, and T. Ertl, “Amortised Encoding for Large High-Resolution Displays,” in 2021 IEEE 11th Symposium on Large Data Analysis and Visualization (LDAV), 2021, pp. 53–62. doi: 10.1109/LDAV53230.2021.00013.
  9. F. Frieß, M. Braun, V. Bruder, S. Frey, G. Reina, and T. Ertl, “Foveated Encoding for Large High-Resolution Displays,” IEEE Transactions on Visualization and Computer Graphics, vol. 27, no. 2, Art. no. 2, 2021, doi: 10.1109/TVCG.2020.3030445.
  10. 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.
  11. V. Bruder, C. Müller, S. Frey, and T. Ertl, “On Evaluating Runtime Performance of Interactive Visualizations,” IEEE Transactions on Visualization and Computer Graphics, vol. 26, pp. 2848–2862, Sep. 2020, doi: 10.1109/TVCG.2019.2898435.
  12. F. Frieß, C. Müller, and T. Ertl, “Real-Time High-Resolution Visualisation,” in Proceedings of the Eurographics Symposium on Vision, Modeling, and Visualization (VMV), 2020, pp. 127–135. doi: 10.2312/vmv.20201195.
  13. C. Müller, M. Braun, and T. Ertl, “Optimised Molecular Graphics on the HoloLens,” in IEEE Conference on Virtual Reality and 3D User Interfaces, VR 2019, Osaka, Japan, March 23-27, 2019, 2019, pp. 97–102. doi: 10.1109/VR.2019.8798111.
  14. F. Frieß, M. Landwehr, V. Bruder, S. Frey, and T. Ertl, “Adaptive Encoder Settings for Interactive Remote Visualisation on High-Resolution Displays,” in Proceedings of the IEEE Symposium on Large Data Analysis and Visualization - Short Papers (LDAV), 2018, pp. 87–91. doi: 10.1109/LDAV.2018.8739215.

The RTSP streaming solution for the tele-conferencing solution has been implemented and is now regularly used for the lecture series and other invited talks.