VESBA – Visuelle Entscheidungsunterstützung bei der ganzheitlichen Planung und Steuerung von Bahnprozessen

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The goal of the project is to develop visual decision support for the holistic planning and control of railway processes. A central focus is on the perfectly visualised design of the planning cycle, in particular the planning model. The focus is on perfect user interaction, both during the manual creation of the planning and during manual intervention in time-critical operational planning situations. The aim is also to optimise user interaction when using artificial intelligence for automatic planning. The solution must be able to process enormous amounts of data and allow it to be labelled, sorted and filtered. The project mainly addresses interactions with the node network as well as integrated interactions between the node network and the Gantt chart. Long-term planning tasks aim to achieve the best possible global solutions, while the best possible solutions with minimum reaction time should be achieved in the event of failures. Various visual methods are being researched for both problems. The aim is to significantly improve the efficiency, precision and responsiveness of railway process planning through these measures. The team members qualify in visualising complex data structures in an understandable and appealing way and in developing user-friendly tools for decision support.

Related Publications

Keck, M., Stoll, E., Kammer, D. (2021). A Didactic Framework for Analyzing Learning Activities to Design InfoVis Courses. In: IEEE Computer Graphics and Applications. https://doi.org/10.1109/MCG.2021.3115416

Kammer, D., Stoll, E., Urban, A. (2021). Experience of Teaching Data Visualization using Project-based Learning. In: VisActivities: 2nd IEEE VIS Workshop on Data Vis Activities to Facilitate Learning, Reflecting, Discussing, and Designing, held in conjunction with IEEE VIS 2021. http://visactivities.github.io/. http://arxiv.org/abs/2111.04428

Keck, M., Kammer, D., Ferreira, A., Giachetti, A., Groh, R. (2020). VIDEM 2020: Workshop on Visual Interface Design Methods. In: AVI '20: Proceedings of the International Conference on Advanced Visual Interfaces. https://doi.org/10.1145/3399715.3400863

Kammer, D., Keck, M., Gründer, T., Maasch, A., Thom, T., Kleinsteuber, M., Groh, R. (2020). Glyphboard: Visual Exploration of High-dimensional Data Combining Glyphs with Dimensionality Reduction. In: IEEE Transactions on Visualization and Computer Graphics. https://doi.org/10.1109/TVCG.2020.2969060

Vosough, Z., Kammer, D., Keck, M., Groh, R. (2019). Visualization approaches for understanding uncertainty in flow diagrams. In: Journal of Computer Languages. http://doi.org/10.1016/j.cola.2019.03.002

Vosough, Z., Kammer, D., Keck, M., Groh, R. (2018). Mirroring Sankey Diagrams for Visual Comparison Tasks. In: Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and applications. https://doi.org/10.5220/0006651203490355

Keck, M., Kammer, D. (2018). Exploring Visualization Challenges for Interactive Recommender Systems. In: Proceedings of VisBIA 2018 – Workshop on Visual Interfaces for big Data environments in Industrial applications, International Working Conference on advanced Visual Interfaces. http://ceur-ws.org/Vol-2108/paper3.pdf

Keck, M., Kammer, D., Groh, R. (2018). Visual Version Comparison of Multidimensional Data Sets Using Glyphs. In: IEEE VIS 2018 Posters. http://ieeevis.org/year/2018/info/posters

Kammer, D., Keck, M., Both, A., Jacucci, G., Groh, R. (2018). VisBIA 2018 – Workshop on Visual Interfaces for Big Data Environments in Industrial Applications. In: Proceedings of the 2018 International Working Conference on advanced Visual Interfaces. https://doi.org/10.1145/3206505.3206603

Kammer, D., Keck, M., Gründer, T., Groh, R. (2018). Big Data Landscapes: Improving the Visualization of Machine Learning-based Clustering Algorithms. In: Proceedings of the 2018 International Working Conference on advanced Visual Interfaces. https://doi.org/10.1145/3206505.3206556

Vosough, Z., Kammer, D., Keck, M., Groh, R. (2017). Visualizing Uncertainty in Flow Diagrams: A Case Study in Product Costing. In: Proceedings of VINCI ’17. https://doi.org/10.1145/3105971.3105972

Keck, M., Kammer, D., Gründer, T., Thom, T., Kleinsteuber, M., Maasch, A., Groh, R. (2017). Towards Glyph-based Visualizations for Big Data Clustering. In: Proceedings of VINCI ’17. https://doi.org/10.1145/3105971.3105979

Wojdziak, J., Kirchner, B., Kammer, D., Herrmann, M., Groh, R. (2016). Towards a Visual Data Language to Improve Insights into Complex Multidimensional Data. In: Human Interface and the Management of Information: Information, Design and Interaction. https://doi.org/10.1007/978-3-319-40349-6_20

Both, A., Nguyen, V., Keck, M., Herrmann, M., Kammer, D., Groh, R., Henkens, D. (2014). Motive-based Search using a Recommendation-driven Visual Divide and Conquer Approach. In: IADIS International Journal on WWW/Internet. http://www.iadisportal.org/ijwi/papers/2014121208.pdf

Keck, M., Kammer, D., Iwan, R., Groh, R., Taranko S. (2011). DelViz: Exploration of Tagged Information Visualizations. In: Informatik 2011 - Interaktion und Visualisierung im Daten-Web. https://www.user.tu-berlin.de/komm/CD/paper/060514.pdf

Keck, M., Koalick, G., Kammer, D., Taranko, S., Wojdziak, J. (2011). DelViz: Ein Werkzeug zur Exploration von Visualisierungen. In: Wieder mehr sehen! - Aktuelle Einblicke in die Technische Visualistik. https://t1p.de/ndv8

Keck, M., Kammer, D., Wojdziak, J., Taranko, S., Groh, R. (2010). DelViz: Untersuchen von Visualisierungsformen durch eine Klassifizierung beruhend auf Social Tagging. In: Virtual enterprises, Communities & social networks: Workshop GeneMe ’10 Gemeinschaften in neuen Medien. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-142838