TimeSets: temporal sensemaking in intelligence analysis
Xu, Kai 
ORCID: https://orcid.org/0000-0003-2242-5440, Salisu, Saminu, Nguyen, Phong H., Walker, Rick, Wong, B. L. William ORCID: https://orcid.org/0000-0002-3363-0741, Wagstaff, Adrian, Phillips, Graham and Biggs, Mike
(2020)
TimeSets: temporal sensemaking in intelligence analysis.
IEEE Computer Graphics and Applications, 40
(3)
.
pp. 83-93.
ISSN 0272-1716
[Article]
(doi:10.1109/MCG.2020.2981855)
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Abstract
TimeSets is a temporal data visualization technique designed to reveal insights into event sets, such as all the events linked to one person or organization. In this paper we describe two TimeSets-based visual analytics tools for intelligence analysis. In the first case, TimeSets is integrated with other visual analytics tools to support open-source intelligence analysis with Twitter data, particularly the challenge of finding the right questions to ask. The second case uses TimeSets in a participatory design process with analysts that aims to meet their requirements of uncertainty analysis involving fake news. Lessons learned are potentially beneficial to other application domains.
| Item Type: | Article |
|---|---|
| Research Areas: | A. > School of Science and Technology > Computer Science |
| Item ID: | 30222 |
| Notes on copyright: | © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
| Useful Links: | |
| Depositing User: | Kai Xu |
| Date Deposited: | 22 May 2020 14:39 |
| Last Modified: | 29 Nov 2022 18:28 |
| URI: | https://eprints.mdx.ac.uk/id/eprint/30222 |
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