Interactive Visual Analytics Application for Spatiotemporal Movement Data VAST Challenge 2017 Mini-Challenge 1: Award for Actionable and Detailed Analysis

• Main Authors: GUAN, Yifei, KAM, Tin Seong
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2017
• Subjects: Spatiotemporal visualisation; Movement Analysis; User interaction; Tableau; MITB student; Databases and Information Systems; Data Science
• Online Access: https://ink.library.smu.edu.sg/sis_research/3852; https://ink.library.smu.edu.sg/context/sis_research/article/4854/viewcontent/Example5_VAST_Challenge_2017_Mini_Challenge_1_Award_for_Actionable_and_Detailed_Analysis.pdf
• Institution: Singapore Management University

The Visual Analytics Science and Technology (VAST) Challenge 2017 Mini-Challenge 1 dataset mirrored the challenging scenarios in analysing large spatiotemporal movement tracking datasets. The datasets provided contains a 13-month movement data generated by five types of sensors, for six types of vehicles passing through the Boonsong Lekagul Nature Preserve. We present an application developed with the market leading visualisation software Tableau to provide an interactive visual analysis of the multi-dimensional spatiotemporal datasets. Our interactive application allows the user to perform an interactive analysis to observe movement patterns, study vehicle trajectories and identify movement anomalies while allowing them to customise the preferred visualisation configurations.