A provenance task abstraction framework

Bors, Christian, Wenskovitch, John, Dowling, Michelle, Attfield, Simon ORCID logoORCID: https://orcid.org/0000-0001-9374-2481, Battle, Leilani, Endert, Alex, Kulyk, Olga and Laramee, Robert (2019) A provenance task abstraction framework. IEEE Computer Graphics and Applications, 39 (6) . pp. 46-60. ISSN 0272-1716 [Article] (doi:10.1109/MCG.2019.2945720)

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Visual analytics tools integrate provenance recording to externalize analytic processes or user insights. Provenance can be captured on varying levels of detail, and in turn activities can be characterized from different granularities. However, current approaches do not support inferring activities that can only be characterized across multiple levels of provenance. We propose a task abstraction framework that consists of a three stage approach, composed of (1) initializing a provenance task hierarchy, (2) parsing the provenance hierarchy by using an abstraction mapping mechanism, and (3) leveraging the task hierarchy in an analytical tool. Furthermore, we identify implications to accommodate iterative refinement, context, variability, and uncertainty during all stages of the framework. A use case describes exemplifies our abstraction framework, demonstrating how context can influence the provenance hierarchy to support analysis. The paper concludes with an agenda, raising and discussing challenges that need to be considered for successfully implementing such a framework.

Item Type: Article
Keywords (uncontrolled): Task analysis, data visualization, visualization, cognition, analytical models, history
Research Areas: A. > School of Science and Technology > Computer Science
Item ID: 28661
Notes on copyright: © 2019 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.
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Depositing User: Simon Attfield
Date Deposited: 07 Jan 2020 10:44
Last Modified: 29 Nov 2022 18:43
URI: https://eprints.mdx.ac.uk/id/eprint/28661

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