Project A03

A03 | Quantification of Visual Analytics Transformations and Mappings

Prof. Daniel A. Keim, Universität Konstanz
Email | Website

Prof. Daniel Weiskopf, Universität Stuttgart
Email | Website

Michael Blumenschein (formerly: Hund), Universität Konstanz – Website

About this project
Results

High-dimensional data analysis requires dealing with numerous challenges, such as selecting meaningful dimensions, finding relevant projections, and removing noise. As a result, the extraction of relevant and meaningful information from high-dimensional data is a difficult problem. This project aims at advancing the field of quality-metric-driven data visualization with the central research question of how to quantify the quality of transformations and mappings of high-dimensional data for visual analytics.

Research Questions

How can we measure and quantify the quality of a visualization? In which way do methods in the data space differ from methods in the image space?

How can we compare the measured quality of a visualization with the perception of a human?

How can the user be involved into a quality-metric-driven process of visual mappings and transformations?

What is the influence of perceptual effects on quality measures? Can we enhance the visual representation of information by introducing perceptual effects into visualizations?

Map visualization with original (top) and transformed (bottom) data. Adapted from: Schneidewind et al. "Pixnostics: Towards measuring the value of visualization." VAST, 2006.

Optimized ordering of dimensions in a Parallel Coordinate Plot to support cluster and correlation analysis. Adapted from: Johansson & Johansson. "Interactive dimensionality reduction through user-defined combinations of quality metrics." Visualization and Computer Graphics, 2009.

Publications

M. Hund et al., “Visual analytics for concept exploration in subspaces of patient groups.,” Brain Informatics, vol. 3, no. 4, pp. 233–247, 2016.
- BibTeX
- Link
@article{hund2016visual, author = {Hund, Michael and Böhm, Dominic and Sturm, Werner and Sedlmair, Michael and Schreck, Tobias and Ullrich, Torsten and Keim, Daniel A. and Majnaric, Ljiljana and Holzinger, Andreas}, doi = {10.1007/s40708-016-0043-5}, journal = {Brain Informatics}, number = 4, pages = {233-247}, title = {Visual analytics for concept exploration in subspaces of patient groups.}, url = {http://dx.doi.org/10.1007/s40708-016-0043-5}, volume = 3, year = 2016 }
M. Behrisch et al., “Magnostics: Image-based Search of Interesting Matrix Views for Guided Network Exploration.,” 2016, vol. 23, no. 1–1, p. 99.
- BibTeX
- Link
@conference{behrisch2016appear, author = {Behrisch, M. and Bach, B. and Hund, M. and von Rüden, L. and Delz, M. and Fekete, J.-D. and Schreck, T.}, editor = {Society, IEEE Computer}, number = {1-1}, pages = 99, title = {Magnostics: Image-based Search of Interesting Matrix Views for Guided Network Exploration.}, url = {http://dx.doi.org/10.1109/TVCG.2016.2598467}, volume = 23, year = 2016 }
M. Hund et al., “Subspace Nearest Neighbor Search - Problem Statement, Approaches, and Discussion - Position Paper.,” in SISAP, 2015, vol. 9371, pp. 307–313.
- BibTeX
- Link
@inproceedings{conf/sisap/HundBFSS0K15, author = {Hund, Michael and Behrisch, Michael and Färber, Ines and Sedlmair, Michael and Schreck, Tobias and Seidl, Thomas and Keim, Daniel A.}, booktitle = {SISAP}, crossref = {conf/sisap/2015}, editor = {Amato, Giuseppe and Connor, Richard C. H. and Falchi, Fabrizio and Gennaro, Claudio}, ee = {http://dx.doi.org/10.1007/978-3-319-25087-8_29}, isbn = {978-3-319-25086-1}, pages = {307-313}, publisher = {Springer}, series = {Lecture Notes in Computer Science}, title = {Subspace Nearest Neighbor Search - Problem Statement, Approaches, and Discussion - Position Paper.}, url = {http://dblp.uni-trier.de/db/conf/sisap/sisap2015.html#HundBFSS0K15}, volume = 9371, year = 2015 }
D. Jäckle, F. Stoffel, S. Mittelstädt, D. A. Keim, and H. Reiterer, “Interpretation of Dimensionally-Reduced Crime Data: A Study with Untrained Domain Experts.,” in Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, Best Student Paper Award, 2017, no. 3, pp. 164–175.
- BibTeX
- Link
@inproceedings{jackle2017appear, author = {Jäckle, Dominik and Stoffel, Florian and Mittelstädt, Sebastian and Keim, Daniel A. and Reiterer, Harald}, booktitle = {Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, Best Student Paper Award}, doi = {10.5220/0006265101640175}, number = 3, pages = {164-175}, title = {Interpretation of Dimensionally-Reduced Crime Data: A Study with Untrained Domain Experts.}, url = {https://bib.dbvis.de/publications/details/697}, year = 2017 }
D. Sacha et al., “SOMFlow: Guided exploratory cluster analysis with self-organizing maps and analytic provenance,” IEEE Conference on Visual Analytics Science and Technology, 2017.
- BibTeX
@article{sacha2017somflow, author = {Sacha, D. and Kraus, M. and Bernard, J. and Behrisch, M. and Schreck, T. and Asano, Y. and Keim, D. A}, booktitle = {IEEE Conference on Visual Analytics Science and Technology}, title = {SOMFlow: Guided exploratory cluster analysis with self-organizing maps and analytic provenance}, year = 2017 }
C. Schulz et al., “Generative Data Models for Validation and Evaluation of Visualization Techniques.,” in BELIV Workshop 2016, 2016, pp. 112--124.
- BibTeX
- Link
@inproceedings{schulz2016generative, author = {Schulz, Christoph and Nocaj, Arlind and El-Assady, Mennatallah and Frey, Steffen and Hlawatsch, Marcel and Hund, Michael and Karch, Grzegorz Karol and Netzel, Rudolf and Schätzle, Christin and Butt, Miriam and Keim, Daniel A. and Ertl, Thomas and Brandes, Ulrik and Weiskopf, Daniel}, booktitle = {BELIV Workshop 2016}, doi = {10.1145/2993901.2993907}, pages = {112--124}, title = {Generative Data Models for Validation and Evaluation of Visualization Techniques.}, url = {http://dx.doi.org/10.1145/2993901.2993907}, year = 2016 }
L. J. Debbeler, M. Gamp, M. Blumenschein, D. A. Keim, and B. Renner, “Polarized but illusory beliefs about tap and bottled water: A product- and consumer-oriented survey and blind tasting experiment,” 2018.
- BibTeX
@article{debbeler2018polarized, author = {Debbeler, L. J. and Gamp, M. and Blumenschein, M. and Keim, D. A. and Renner, B.}, title = {Polarized but illusory beliefs about tap and bottled water: A product- and consumer-oriented survey and blind tasting experiment }, year = 2018 }
M. Behrisch et al., “Magnostics: Image-Based Search of Interesting Matrix Views for Guided Network Exploration.,” IEEE Trans. Vis. Comput. Graph., vol. 23, no. 1, pp. 31–40, 2017.
- BibTeX
- Link
@article{journals/tvcg/BehrischBHDRFS17, author = {Behrisch, Michael and Bach, Benjamin and Hund, Michael and Delz, Michael and von Rüden, Laura and Fekete, Jean-Daniel and Schreck, Tobias}, ee = {http://doi.ieeecomputersociety.org/10.1109/TVCG.2016.2598467}, journal = {IEEE Trans. Vis. Comput. Graph.}, number = 1, pages = {31-40}, title = {Magnostics: Image-Based Search of Interesting Matrix Views for Guided Network Exploration.}, url = {http://dblp.uni-trier.de/db/journals/tvcg/tvcg23.html#BehrischBHDRFS17}, volume = 23, year = 2017 }
M. Behrisch et al., “Quality Metrics for Information Visualization.,” EuroVis STAR, 2018.
- BibTeX
- Link
@article{behrisch2018quality, author = {Behrisch, M. and Blumenschein, M. and Kim, N. W. and Shao, L. and El-Assady, M. and Fuchs, J. and Seebacher, D. and Diehl, A. and Brandes, U. and Pfister, H. and Schreck, T. and Weiskopf, D. and Keim, D. A.}, journal = {EuroVis STAR}, title = {Quality Metrics for Information Visualization.}, url = {https://bib.dbvis.de/publications/details/758}, year = 2018 }
M. Hund et al., “Subspace Nearest Neighbor Search - Problem Statement, Approaches, and Discussion,” in Similarity Search and Applications, vol. 1, no. 9371, G. Amato, R. Connor, F. Falchi, and C. Gennaro, Eds. Springer International Publishing, 2015, pp. 307–313.
- BibTeX
@incollection{HBF+15a, author = {Hund, Michael and Behrisch, Michael and Farber, Ines and Sedlmair, Michael and Schreck, Tobias and Seidl, Thomas and Keim, Daniel}, booktitle = {Similarity Search and Applications}, doi = {10.1007/978-3-319-25087-8_29}, editor = {Amato, Giuseppe and Connor, Richard and Falchi, Fabrizio and Gennaro, Claudio}, month = {Oktober}, number = 9371, pages = {307-313}, publisher = {Springer International Publishing}, series = {Lecture Notes in Computer Science}, title = {Subspace Nearest Neighbor Search - Problem Statement, Approaches, and Discussion}, volume = 1, year = 2015 }
L. Merino et al., “On the Impact of the Medium in the Effectiveness of 3D Software Visualizations,” in VISSOFT’17: Proceedings of the 5th IEEE Working Conference on Software Visualization, 2017.
- BibTeX
@inproceedings{merino2017impact, author = {Merino, L. and Fuchs, J. and Blumenschein, M. and Anslow, C. and Ghafari, M. and Nierstrasz, O. and M., Behrisch and Keim, D. A.}, booktitle = {VISSOFT'17: Proceedings of the 5th IEEE Working Conference on Software Visualization}, title = {On the Impact of the Medium in the Effectiveness of 3D Software Visualizations}, year = 2017 }
M. Blumenschein et al., “‘SMARTexplore: Simplifying High-Dimensional Data Analysis through a Table-Based Visual Analytics Approach,’” 2018.
- BibTeX
@inproceedings{blumenschein2018smartexplore, author = {Blumenschein, M. and Behrisch, M. and Schmid, S. and Butscher, S. and Wahl, D. R. and Villinger, K. and Renner, B. and Reiterer, H. and Keim, D. A}, organization = {IEEE Conference on Visual Analytics Science and Technology (VAST)}, title = {“SMARTexplore: Simplifying High-Dimensional Data Analysis through a Table-Based Visual Analytics Approach” }, year = 2018 }
M. Hund et al., “Visual Quality Assessment of Subspace Clusterings,” in KDD 2016 Interactive Data Exploration and Analytics (IDEA), 2016.
- BibTeX
@inproceedings{hund2016visual, author = {Hund, Michael and Färber, Ines and Behrisch, Michael and Tatu, Andrada and Schreck, Tobias and Keim, Daniel A. and Seidl, Thomas}, booktitle = {KDD 2016 Interactive Data Exploration and Analytics (IDEA)}, editor = {KDD 2016, IDEA}, title = {Visual Quality Assessment of Subspace Clusterings}, year = 2016 }
M. Stein et al., “Bring it to the Pitch: Combining Video and Movement Data to Enhance Team Sport Analysis.,” in IEEE Transactions on Visualization and Computer Graphics (Proceedings of the Visual Analytics Science and Technology), 2017.
- BibTeX
@inproceedings{stein2017bring, author = {Stein, M. and Janetzko, H. and Lamprecht, A. and Breitkreutz, T. and Zimmermann, P. and Goldlücke, B. and Schreck, T. and Andrienko, G. and Grossniklaus, M. and Keim, D. A.}, booktitle = {IEEE Transactions on Visualization and Computer Graphics (Proceedings of the Visual Analytics Science and Technology)}, title = {Bring it to the Pitch: Combining Video and Movement Data to Enhance Team Sport Analysis.}, year = 2017 }
D. Jäckle, M. Hund, M. Behrisch, D. A. Keim, and T. Schreck, “Pattern Trails: Visual Analysis of Pattern Transitions in Subspaces,” in IEEE Conference on Visual Analytics Science and Technology (VAST), 2017.
- BibTeX
@inproceedings{jackle2017pattern, author = {Jäckle, D. and Hund, M. and Behrisch, M. and Keim, D. A. and Schreck, T.}, booktitle = {IEEE Conference on Visual Analytics Science and Technology (VAST)}, title = {Pattern Trails: Visual Analysis of Pattern Transitions in Subspaces}, year = 2017 }