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Matthias Braun

Matthias Braun

Herr Dipl.-Inf.

Technischer Mitarbeiter
Visualisierungsinstitut der Universität Stuttgart (VISUS)
Arbeitsgruppe Ertl

Kontakt

+49 711 685 88607
E-Mail

Allmandring 19
70569 Stuttgart
Deutschland
Raum: 00.106

Publikationen

2022
1. D. Garkov, C. Müller, M. Braun, D. Weiskopf, und F. Schreiber, „Research Data Curation in Visualization : Position Paper“, in 2022 IEEE Evaluation and Beyond - Methodological Approaches for Visualization (BELIV), in 2022 IEEE Evaluation and Beyond - Methodological Approaches for Visualization (BELIV). IEEE, 2022, S. 56–65. doi: 10.1109/BELIV57783.2022.00011.
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  @inproceedings{Garkov2022Resea, abstract = {Research data curation is the act of carefully preparing research data and artifacts for sharing and long-term preservation. Research data management is centrally implemented and formally defined in a data management plan to enable data curation. In tandem, data curation and management facilitate research repeatability. In contrast to other research fields, data curation and management in visualization are not yet part of the researcher’s compendium. In this position paper, we discuss the unique challenges visualization faces and propose how data curation can be practically realized. We share eight lessons learned in managing data in two large research consortia, outline the larger curation workflow, and define the typical roles. We complement our lessons with minimum criteria for selecting a suitable data repository and five challenging scenarios that occur in practice. We conclude with a vision of how the visualization research community can pave the way for new curation standards.}, author = {Garkov, Dimitar and Müller, Christoph and Braun, Matthias and Weiskopf, Daniel and Schreiber, Falk}, booktitle = {2022 IEEE Evaluation and Beyond - Methodological Approaches for Visualization (BELIV)}, doi = {10.1109/BELIV57783.2022.00011}, eventdate = {17 October 2022}, note = {Related to: Garkov, D., Müller, C., Braun, M., Weiskopf, D., & Schreiber, F. (2022). Research Data Curation in Visualization : Position Paper (Data), DOI: 10.18419/darus-3144}, pages = {56-65}, publisher = {IEEE}, title = {Research Data Curation in Visualization : Position Paper}, year = 2022 }
2021
1. K. Schatz u. a., „2019 IEEE Scientific Visualization Contest Winner: Visual Analysis of Structure Formation in Cosmic Evolution“, IEEE Computer Graphics and Applications (CG&A), Bd. 41, Nr. 06, Art. Nr. 06, Nov. 2021, doi: 10.1109/MCG.2020.3004613.
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  @article{9126163, abstract = {Simulations of cosmic evolution are a means to explain the formation of the universe as we see it today. The resulting data of such simulations comprise numerous physical quantities, which turns their analysis into a complex task. Here, we analyze such high-dimensional and time-varying particle data using various visualization techniques from the fields of particle visualization, flow visualization, volume visualization, and information visualization. Our approach employs specialized filters to extract and highlight the development of so-called active galactic nuclei and filament structures formed by the particles. Additionally, we calculate X-ray emission of the evolving structures in a pre-processing step to complement visual analysis. Our approach is integrated into a single visual analytics framework to allow for analysis of star formation at interactive frame rates. Finally, we lay out the methodological aspects of our work that led to success at the 2019 IEEE SciVis Contest.}, author = {Schatz, K. and Müller, C. and Gralka, P. and Heinemann, M. and Straub, A. and Schulz, C. and Braun, M. and Rau, T. and Becher, M. and Frey, S. and Reina, G. and Sedlmair, M. and Weiskopf, D. and Ertl, T. and Diehl, P. and Marcello, D. and Frank, J. and Müller, T.}, doi = {10.1109/MCG.2020.3004613}, issn = {1558-1756}, journal = {IEEE Computer Graphics and Applications (CG&A)}, month = {11}, number = 06, pages = {101-110}, title = {2019 IEEE Scientific Visualization Contest Winner: Visual Analysis of Structure Formation in Cosmic Evolution}, url = {https://ieeexplore.ieee.org/document/9126163}, volume = 41, year = 2021 }
  Link
  https://ieeexplore.ieee.org/document/9126163
2020
1. F. Frieß, M. Braun, V. Bruder, S. Frey, G. Reina, und T. Ertl, „Foveated Encoding for Large High-Resolution Displays“, IEEE Transactions on Visualization and Computer Graphics, S. 1–10, 2020, doi: 10.1109/TVCG.2020.3030445.
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  @article{9224182, abstract = {Collaborative exploration of scientific data sets across large high-resolution displays requires both high visual detail as wellas low-latency transfer of image data (oftentimes inducing the need to trade one for the other). In this work, we present a system thatdynamically adapts the encoding quality in such systems in a way that reduces the required bandwidth without impacting the detailsperceived by one or more observers. Humans perceive sharp, colourful details, in the small foveal region around the centre of the fieldof view, while information in the periphery is perceived blurred and colourless. We account for this by tracking the gaze of observers,and respectively adapting the quality parameter of each macroblock used by the H.264 encoder, considering the so-called visual acuityfall-off. This allows to substantially reduce the required bandwidth with barely noticeable changes in visual quality, which is crucial forcollaborative analysis across display walls at different locations. We demonstrate the reduced overall required bandwidth and the highquality inside the foveated regions using particle rendering and parallel coordinate}, author = {Frieß, F. and Braun, M. and Bruder, V. and Frey, S. and Reina, G. and Ertl, T.}, doi = {10.1109/TVCG.2020.3030445}, journal = {IEEE Transactions on Visualization and Computer Graphics}, pages = {1-10}, title = {Foveated Encoding for Large High-Resolution Displays}, url = {https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9224182}, year = 2020 }
  Link
  https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9224182
2019
1. C. Müller, M. Braun, und 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, in IEEE Conference on Virtual Reality and 3D User Interfaces, VR 2019, Osaka, Japan, March 23-27, 2019. IEEE, 2019, S. 97--102. doi: 10.1109/VR.2019.8798111.
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  @inproceedings{DBLP:conf/vr/MuilerBE19, abstract = {The advent of modern and affordable augmented reality head sets like Microsoft HoloLens has sparked new interest in using virtual and augmented reality technology in the analysis of molecular data. For all visualisation in immersive, mixed-reality scenarios, a sufficiently high rendering speed is an important factor, which leads to the issue of limited processing power available on fully untethered devices facing the situation of handling computationally expensive visualisations. Recent research shows that the space-filling model of even small data sets from the Protein Data Bank (PDB) cannot be rendered at desirable frame rates on the HoloLens. In this work, we report on how to improve the rendering speed of atom-based visualisation of proteins and how the rendering of more abstract representations of the molecules compares against it. We complement our findings with in-depth GPU and CPU performance numbers.}, author = {Müller, Christoph and Braun, Matthias and Ertl, Thomas}, bibsource = {dblp computer science bibliography, https://dblp.org}, booktitle = {IEEE Conference on Virtual Reality and 3D User Interfaces, VR 2019, Osaka, Japan, March 23-27, 2019}, doi = {10.1109/VR.2019.8798111}, pages = {97--102}, publisher = {IEEE}, title = {Optimised Molecular Graphics on the HoloLens}, url = {https://doi.org/10.1109/VR.2019.8798111}, year = 2019 }
  Link
  https://doi.org/10.1109/VR.2019.8798111
2. P. Gralka u. a., „MegaMol -- a comprehensive prototyping framework for visualizations“, The European Physical Journal (Special Topics), Bd. 227: Particle Methods in Natural Science and Engineering, Nr. 14, Art. Nr. 14, 2019, doi: 10.1140/epjst/e2019-800167-5.
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  @article{Gralka2019Megamol, abstract = {We present MegaMol, a low-overhead prototyping framework for interactive visualization of large scientific data sets. We give a brief summary of related work for context and then focus on a comprehensive overview of the core architecture of the framework. This is followed by the existing and novel features and techniques in MegaMol that define its current functionality. MegaMol has originally been developed to support the visualization and analysis of particle-based data sets that, for instance, come from molecular dynamics simulations. Meanwhile, the software has evolved beyond that. New algorithms and techniques have been implemented to handle many diverse tasks, including information visualization. Additionally, improvements have been made on the software engineering side to make MegaMol more accessible for domain scientists, like an easy-to-handle scripting interface.}, author = {Gralka, Patrick and Becher, Michael and Braun, Matthias and Frieß, Florian and Müller, Christoph and Rau, Tobias and Schatz, Karsten and Schulz, Christoph and Krone, Michael and Reina, Guido and Ertl, Thomas}, doi = {10.1140/epjst/e2019-800167-5}, issn = {1951-6401}, journal = {The European Physical Journal (Special Topics)}, number = 14, pages = {1817--1829}, title = {MegaMol -- a comprehensive prototyping framework for visualizations}, url = {https://doi.org/10.1140/epjst/e2019-800167-5}, volume = {227: Particle Methods in Natural Science and Engineering}, year = 2019 }
  Link
  https://doi.org/10.1140/epjst/e2019-800167-5
3. K. Schatz u. a., „Visual Analysis of Structure Formation in Cosmic Evolution“, in 2019 IEEE Scientific Visualization Conference (SciVis), in 2019 IEEE Scientific Visualization Conference (SciVis). 2019, S. 33–41. doi: 10.1109/scivis47405.2019.8968855.
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  @inproceedings{schatz2019visual, abstract = {The IEEE SciVis 2019 Contest targets the visual analysis of structure formation in the cosmic evolution of the universe from when the universe was five million years old up to now. In our submission, we analyze high-dimensional data to get an overview, then investigate the impact of Active Galactic Nuclei (AGNs) using various visualization techniques, for instance, an adapted filament filtering method for detailed analysis and particle flow in the vicinity of filaments. Based on feedback from domain scientists on these initial visualizations, we also analyzed X-ray emissions and star formation areas. The conversion of star-forming gas to stars and the resulting increasing molecular weight of the particles could be observed.}, author = {Schatz, Karsten and Müller, Christoph and Gralka, Patrick and Heinemann, Moritz and Straub, Alexander and Schulz, Christoph and Braun, Matthias and Rau, Tobias and Becher, Michael and Diehl, Patrick and Marcello, Dominic and Frank, Juhan and Müller, Thomas and Frey, Steffen and Reina, Guido and Weiskopf, Daniel and Ertl, Thomas}, booktitle = {2019 IEEE Scientific Visualization Conference (SciVis)}, doi = {10.1109/scivis47405.2019.8968855}, pages = {33-41}, title = {Visual Analysis of Structure Formation in Cosmic Evolution}, url = {http://dx.doi.org/10.1109/scivis47405.2019.8968855}, year = 2019 }
  Link
  http://dx.doi.org/10.1109/scivis47405.2019.8968855
2018
1. C. Schulz, K. Schatz, M. Krone, M. Braun, T. Ertl, und D. Weiskopf, „Uncertainty Visualization for Secondary Structures of Proteins“, in IEEE Pacific Visualization Symposium, in IEEE Pacific Visualization Symposium. 2018, S. 96–105. doi: 10.1109/PacificVis.2018.00020.
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  @inproceedings{Schulz2018Uncertainty, author = {Schulz, Christoph and Schatz, Karsten and Krone, Michael and Braun, Matthias and Ertl, Thomas and Weiskopf, Daniel}, booktitle = {IEEE Pacific Visualization Symposium}, doi = {10.1109/PacificVis.2018.00020}, pages = {96-105}, title = {Uncertainty Visualization for Secondary Structures of Proteins}, year = 2018 }

ORCID

https://orcid.org/0000-0001-8591-3690

Matthias Braun

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Publikationen

2022

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2021

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2020

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2019

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2018

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Matthias Braun

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Publikationen

2022

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2021

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2020

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2019

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2018

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