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In recent years, a large number of research efforts aimed at the developmentof machine learning models to predict complex spatial-temporal mobilitypatterns and their impact on road traffic and infrastructure. However, theutility of these models is often diminished due to the lack of accessible userinterfaces to view and analyse prediction results. In this paper, we presentthe Traffic Analytics Dashboard ( TA-Dash), an interactive dashboard thatenables the visualisation of complex spatial-temporal urban traffic patterns.We demonstrate the utility of TA-Dash at the example of two recently proposedspatial-temporal models for urban traffic and urban road infrastructureanalysis. In particular, the use cases include the analysis, prediction andvisualisation of the impact of planned special events on urban road traffic aswell as the analysis and visualisation of structural dependencies within urbanroad networks. The lightweight TA-Dash dashboard aims to address non-expertusers involved in urban traffic management and mobility service planning. TheTA-Dash builds on a flexible layer-based architecture that is easily adaptableto the visualisation of new models.

TA-Dash: An Interactive Dashboard for Spatial-Temporal Traffic Analytics -- Demo Paper