Patterns of life visualisations for intelligence analysis: exploring animation with POLAR

Attfield, Simon ORCID logoORCID:, Selvaraj, Nallini, Kodagoda, Neesha, Passmore, Peter J. ORCID logoORCID: and Duncker-Gassen, Elke ORCID logoORCID: (2019) Patterns of life visualisations for intelligence analysis: exploring animation with POLAR. 2019 International Carnahan Conference on Security Technology (ICCST). In: 2019 International Carnahan Conference on Security Technology (ICCST), 1-3 Oct 2019, Chennai, India. e-ISBN 9781728115764. ISSN 1071-6572 [Conference or Workshop Item] (doi:10.1109/CCST.2019.8888410)

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POLAR is a prototype data visualisation system developed for use by Intelligence Analysts conducting Patterns-of-Life (PoL) analysis. PoL analysis involves exploring data to identify behaviour patterns of individuals or groups. POLAR began with a series of requirements interviews with an ex-military analyst. The design process revealed a series of design alternatives that were explored. One of these related to whether, contrary to suggestions in the literature, animation might provide an advantage to the analyst. We report the design of the system and an evaluation study to assess the effect of animation on users. Whilst animation didn’t result in significant improvements in performance, the use of animation with trails did result in significantly better usability assessments and higher user-engagement ratings. Post task interviews with analysts suggested where animation might offer a performance advantage.

Item Type: Conference or Workshop Item (Paper)
Keywords (uncontrolled): computer animation, data visualisation, POLAR, prototype data visualisation system, intelligence analysts, PoL analysis, animation, intelligence analysis, life visualiation, patterns-of-life analysis, Animation, Visualization, Image color analysis, Task analysis, Interviews, Computer science, Data visualization, Patterns of Life, Intelligence Analysis, Coordinated Multiple Views, Animation, Evaluation
Research Areas: A. > School of Science and Technology > Computer Science
Item ID: 28662
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Depositing User: Simon Attfield
Date Deposited: 07 Jan 2020 10:12
Last Modified: 11 Jan 2020 01:02

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