Rajendran, S., Arleo, A., von Landesberger, T., Miksch, S., sondag, max, Tuscher, M., & Filipov, V. (2025). Don’t Stop Me Now: Visualizing Disruptions in Railroad Networks. In IEEEVisShort 2025. IEEE VIS 2025, Vienna, Austria.
E193-07 - Forschungsbereich Visual Analytics E056-18 - Fachbereich Visual Analytics and Computer Vision Meet Cultural Heritage
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Published in:
IEEEVisShort 2025
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Date (published):
5-Nov-2025
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Event name:
IEEE VIS 2025
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Event date:
2-Nov-2025 - 7-Nov-2025
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Event place:
Vienna, Austria
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Peer reviewed:
Yes
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Keywords:
spatio-temporal data; networks; railroad networks; Information diffusion; delay
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Abstract:
Railroad networks are complex systems where a single disruption can have cumulative effects, impacting services' planned schedules and degrading the network's performance. To support railroad planners in identifying these disruptions, we propose a Visual Analytics approach with multiple coordinated views: a map, calendar heatmap, Marey graph, and a multi-line chart. Our proposed approach enables the exploration and analysis of the disruptions' spatial and temporal patterns and delay accumulation to identify vulnerable segments in the railroad network. We assess the effectiveness of our approach through an expert interview highlighting how the accumulation of delays and disruptions is lucidly communicated and provides valuable insights into their spread across the network. We discuss the outcomes of the expert interview alongside the limitations we identified and how we resolve these. Finally, we illustrate directions for future work, including online data to assist railroad planners with real-time monitoring for proactive decision-making and improved operations.
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Project title:
SANE: Visual Analytics für Ereignisdiffusion in Netzwerken: I 6635-N (FWF - Österr. Wissenschaftsfonds) ArtVis: Dynamische Netzwerk für die digitale Kunstgeschichte: P35767-N (FWF - Österr. Wissenschaftsfonds)
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Research Areas:
Visual Computing and Human-Centered Technology: 100%