A conceptual framework and taxonomy of techniques for analyzing movement
Movement data link together space, time, and objects positioned in space and time. They hold valuable and multifaceted information about moving objects, properties of space and time as well as events and processes occurring in space and time. We present a conceptual framework that describes in a sys...
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| Published in | Journal of visual languages and computing Vol. 22; no. 3; pp. 213 - 232 |
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| Main Authors | , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier Ltd
01.06.2011
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1045-926X 1095-8533 1095-8533 |
| DOI | 10.1016/j.jvlc.2011.02.003 |
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| Abstract | Movement data link together space, time, and objects positioned in space and time. They hold valuable and multifaceted information about moving objects, properties of space and time as well as events and processes occurring in space and time. We present a conceptual framework that describes in a systematic and comprehensive way the possible types of information that can be extracted from movement data and on this basis defines the respective types of analytical tasks. Tasks are distinguished according to the type of information they target and according to the level of analysis, which may be elementary (i.e. addressing specific elements of a set) or synoptic (i.e. addressing a set or subsets). We also present a taxonomy of generic analytic techniques, in which the types of tasks are linked to the corresponding classes of techniques that can support fulfilling them. We include techniques from several research fields: visualization and visual analytics, geographic information science, database technology, and data mining.
We expect the taxonomy to be valuable for analysts and researchers. Analysts will receive guidance in choosing suitable analytic techniques for their data and tasks. Researchers will learn what approaches exist in different fields and compare or relate them to the approaches they are going to undertake. |
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| AbstractList | Movement data link together space, time, and objects positioned in space and time. They hold valuable and multifaceted information about moving objects, properties of space and time as well as events and processes occurring in space and time. We present a conceptual framework that describes in a systematic and comprehensive way the possible types of information that can be extracted from movement data and on this basis defines the respective types of analytical tasks. Tasks are distinguished according to the type of information they target and according to the level of analysis, which may be elementary (i.e. addressing specific elements of a set) or synoptic (i.e. addressing a set or subsets). We also present a taxonomy of generic analytic techniques, in which the types of tasks are linked to the corresponding classes of techniques that can support fulfilling them. We include techniques from several research fields: visualization and visual analytics, geographic information science, database technology, and data mining.
We expect the taxonomy to be valuable for analysts and researchers. Analysts will receive guidance in choosing suitable analytic techniques for their data and tasks. Researchers will learn what approaches exist in different fields and compare or relate them to the approaches they are going to undertake. |
| Author | Kisilevich, S. Keim, D. Andrienko, G. Bak, P. Wrobel, S. Andrienko, N. |
| Author_xml | – sequence: 1 givenname: G. surname: Andrienko fullname: Andrienko, G. email: gennady.andrienko@ais.fraunhofer.de organization: Fraunhofer Institute IAIS – Intelligent Analysis and Information Systems Schloss Birlinghoven, Sankt-Augustin, D-53754, Germany – sequence: 2 givenname: N. surname: Andrienko fullname: Andrienko, N. organization: Fraunhofer Institute IAIS – Intelligent Analysis and Information Systems Schloss Birlinghoven, Sankt-Augustin, D-53754, Germany – sequence: 3 givenname: P. surname: Bak fullname: Bak, P. organization: IBM Haifa Research Lab, Mount Carmel, IL-31905, Israel – sequence: 4 givenname: D. surname: Keim fullname: Keim, D. organization: University of Konstanz, Universitätsstraße 10, Konstanz, Germany – sequence: 5 givenname: S. surname: Kisilevich fullname: Kisilevich, S. organization: University of Konstanz, Universitätsstraße 10, Konstanz, Germany – sequence: 6 givenname: S. surname: Wrobel fullname: Wrobel, S. organization: Fraunhofer Institute IAIS – Intelligent Analysis and Information Systems Schloss Birlinghoven, Sankt-Augustin, D-53754, Germany |
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| Keywords | Moving object Trajectory Movement data Visual analytics |
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| Title | A conceptual framework and taxonomy of techniques for analyzing movement |
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