Publication Type
Conference Proceeding Article
Version
acceptedVersion
Publication Date
10-2017
Abstract
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.
Keywords
Spatiotemporal visualisation, Movement Analysis, User interaction, Tableau, MITB student
Discipline
Databases and Information Systems | Data Science
Research Areas
Data Science and Engineering
Publication
2017 IEEE Conference on Visual Analytics Science and Technology (VAST): October 3-6, Phoenix, AZ: Proceedings
First Page
195
Last Page
196
ISBN
9781538631638
Identifier
10.1109/VAST.2017.8585564
Publisher
IEEE
City or Country
Piscataway, NJ
Citation
GUAN, Yifei and KAM, Tin Seong.
Interactive Visual Analytics Application for Spatiotemporal Movement Data VAST Challenge 2017 Mini-Challenge 1: Award for Actionable and Detailed Analysis. (2017). 2017 IEEE Conference on Visual Analytics Science and Technology (VAST): October 3-6, Phoenix, AZ: Proceedings. 195-196.
Available at: https://ink.library.smu.edu.sg/sis_research/3852
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1109/VAST.2017.8585564