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Visual analytics tools for analysis of movement data
Author(s) -
Gennady Andrienko,
Natalia Andrienko,
Stefan Wrobel
Publication year - 2007
Publication title -
acm sigkdd explorations newsletter
Language(s) - English
Resource type - Journals
eISSN - 1931-0153
pISSN - 1931-0145
DOI - 10.1145/1345448.1345455
Subject(s) - computer science , visual analytics , analytics , interactive visual analysis , movement (music) , data science , embedding , human–computer interaction , global positioning system , cultural analytics , data analysis , visualization , artificial intelligence , data mining , semantic analytics , semantic computing , semantic web , telecommunications , philosophy , aesthetics
With widespread availability of low cost GPS devices, it is becoming possible to record data about the movement of people and objects at a large scale. While these data hide important knowledge for the optimization of location and mobility oriented infrastructures and services, by themselves they lack the necessary semantic embedding which would make fully automatic algorithmic analysis possible. At the same time, making the semantic link is easy for humans who however cannot deal well with massive amounts of data. In this paper, we argue that by using the right visual analytics tools for the analysis of massive collections of movement data, it is possible to effectively support human analysts in understanding movement behaviors and mobility patterns. We suggest a framework for analysis combining interactive visual displays, which are essential for supporting human perception, cognition, and reasoning, with database operations and computational methods, which are necessary for handling large amounts of data. We demonstrate the synergistic use of these techniques in case studies of two real datasets

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