Using topological analysis to support event-guided exploration in urban data
- Submitting institution
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The University of Warwick
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 5907
- Type
- D - Journal article
- DOI
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10.1109/TVCG.2014.2346449
- Title of journal
- IEEE Transactions on Visualization and Computer Graphics
- Article number
- -
- First page
- 2634
- Volume
- 20
- Issue
- 12
- ISSN
- 1077-2626
- Open access status
- Out of scope for open access requirements
- Month of publication
- December
- Year of publication
- 2014
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
4
- Research group(s)
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D - Data Science, Systems and Security
- Citation count
- 35
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Published in the top journal in the field of visualisation, this work set the foundations for event-based topological analysis of urban data. It was the first paper to develop event detection algorithms on large scale spatiotemporal urban data streams through topological analysis of the underlying graphs. It has led to significant subsequent work by international groups in visualisation (e.g. Sonyc work from NYU, TPFlow from Bosch Research) and in machine learning (Trend filtering on Graphs, JMLR 2016), as well as by the authors of this paper (ACM SIGMOD 2016, winner of the Most Reproducible Paper Award).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -