2019
Conference article  Open Access

Vista: a visual analytics platform for semantic annotation of trajectories

Soares A., Rose J., Etemad M., Renso C., Matwin S.

Trajectories  Data mining  Trajectory dataset 

Most of the trajectory datasets only record the spatio-temporal position of the moving object, thus lacking semantics and this is due to the fact that this information mainly depends on the domain expert labeling, a time-consuming and complex process. This paper is a contribution in facilitating and supporting the manual annotation of trajectory data thanks to a visual-analytics-based platform named VISTA. VISTA is designed to assist the user in the trajectory annotation process in a multi-role user environment. A session manager creates a tagging session selecting the trajectory data and the semantic contextual information. The VISTA platform also supports the creation of several features that will assist the tagging users in identifying the trajectory segments that will be annotated. A distinctive feature of VISTA is the visual analytics functionalities that support the users in exploring and processing the trajectory data, the associated features and the semantic information for a proper comprehension of how to properly label trajectories.

Source: EDBT 2019 - 22nd International Conference on Extending Database Technology, pp. 570–573, Lisbon, Portugal, March 26-29, 2019


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BibTeX entry
@inproceedings{oai:it.cnr:prodotti:424184,
	title = {Vista: a visual analytics platform for semantic annotation of trajectories},
	author = {Soares A. and Rose J. and Etemad M. and Renso C. and Matwin S.},
	doi = {10.5441/002/edbt.2019.58},
	booktitle = {EDBT 2019 - 22nd International Conference on Extending Database Technology, pp. 570–573, Lisbon, Portugal, March 26-29, 2019},
	year = {2019}
}

MASTER
Multiple ASpects TrajEctoRy management and analysis


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