Explaining cognitive breakpoints to chunk visual analytic actions for transparency in sensemaking

Islam, Junayed, Xu, Kai ORCID logoORCID: https://orcid.org/0000-0003-2242-5440 and Wong, B. L. William ORCID logoORCID: https://orcid.org/0000-0002-3363-0741 (2022) Explaining cognitive breakpoints to chunk visual analytic actions for transparency in sensemaking. IEEE Computer Graphics and Applications . ISSN 0272-1716 [Article] (Accepted/In press)

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Abstract

Sensemaking is inherently a fluid activity involving transitions between mental and interaction states but may create a gap between them due to lack of accuracy and precision into adopted visualization techniques. We have found through this research that detection and explanation of those transition points can bridge that gap and maintain transparency in sensemaking visual analytic activities. We have defined those transition points as ‘Breakpoints’ and developed machine learning models to contextualize streams of analytic actions for inferring those at micro analytic level. We also have presented visual explanations by unfolding black box calculations for transparent validation of all machine produced results in terms of reliability, accuracy and relevance.

Item Type: Article
Additional Information: Special Issue on Human-Centered Visualization Approaches to AI Explainability, Interpretability, Understanding, and Ethics
Research Areas: A. > School of Science and Technology > Computer Science
Item ID: 34941
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Depositing User: Junayed Islam
Date Deposited: 25 Apr 2022 12:05
Last Modified: 09 Sep 2022 11:01
URI: https://eprints.mdx.ac.uk/id/eprint/34941

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