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Contextualized Analysis of Movement Events

Chen, S., Andrienko, G. ORCID: 0000-0002-8574-6295, Andrienko, N. ORCID: 0000-0003-3313-1560 , Doulkeridis, C. & Koumparos, A. (2019). Contextualized Analysis of Movement Events. In: EuroVis Workshop on Visual Analytics (EuroVA). EuroVA 2019 – International EuroVis Workshop on Visual Analytics, 3 Jun 2019, Porto, Portugal. doi: 10.2312/eurova.20191124


For understanding the circumstances, causes, and consequences of events that may happen during movement (e.g., harsh brake, sharp turn), it is necessary to analyze event context. The context includes dynamic attributes of the moving objects before and after the event and external context elements such as other moving objects, weather, terrain, etc. To explore events in context, we propose an analytical workflow including event contextualization, context pattern detection, and exploration of the spatio-temporal distribution of the detected patterns. The approach involves clustering of events based on the similarity of their contexts and interactive visual techniques for exploration of the distribution of the clusters in time, geographic space, and multidimensional attribute space. In close collaboration with domain experts, we apply our method to real-world vehicle trajectories with the purpose of identifying and investigating potentially dangerous driving behaviors.

Publication Type: Conference or Workshop Item (Paper)
Additional Information: This is the accepted version of the following article: Chen, S., Andrienko, G. , Andrienko, N. view all authors (2019). Contextualized Analysis of Movement Events. In: EuroVis Workshop on Visual Analytics (EuroVA). (pp. 49-53). Geneva, Switzerland: The Eurographics Association. ISBN 9783038680871 doi: 10.2312/eurova.20191124, which has been published in final form at This article may be used for non-commercial purposes in accordance with the Wiley Self-Archiving Policy [].
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Departments: School of Science & Technology > Computer Science > giCentre
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