Abstract
With the prevalence of mobile computing systems and location based services, the research interest on spatiotemporal data has significantly increased, as evidenced by the collection of huge amounts of movement data. Consequently, this type of data raises several issues, namely in the research area of geographic information visualization. Despite the existence of several visual analysis techniques for the exploration of movement data, it is still unclear how usable and useful these techniques are, how can they be improved, and for which situations are these techniques most suitable. In this paper, we present current open challenges on the visual analysis of movement data, and the Ph.D work in progress aiming to address these problems. Our work will explore several factors that may affect the users' performance, and, based on those factors we will propose a taxonomy and an evaluation framework covering different tasks and techniques.
Links
BibTeX (Download)
@inproceedings{goncalves2013visual,
title = {Visual analysis of mobility data},
author = { Tiago Gonçalves and Ana Paula Afonso and Bruno Martins},
url = {http://dx.doi.org/10.1109/MDM.2013.56},
isbn = {978-1-4673-6068-5},
year = {2013},
date = {2013-01-01},
booktitle = {Mobile Data Management (MDM), 2013 IEEE 14th International Conference on},
volume = {2},
pages = {7--10},
organization = {IEEE},
abstract = {With the prevalence of mobile computing systems and location based services, the research interest on spatiotemporal data has significantly increased, as evidenced by the collection of huge amounts of movement data. Consequently, this type of data raises several issues, namely in the research area of geographic information visualization. Despite the existence of several visual analysis techniques for the exploration of movement data, it is still unclear how usable and useful these techniques are, how can they be improved, and for which situations are these techniques most suitable. In this paper, we present current open challenges on the visual analysis of movement data, and the Ph.D work in progress aiming to address these problems. Our work will explore several factors that may affect the users' performance, and, based on those factors we will propose a taxonomy and an evaluation framework covering different tasks and techniques.},
keywords = {Data Visualisation, Geographic Information Systems, Mobile Computing},
pubstate = {published},
tppubtype = {inproceedings}
}