An extensible framework for provenance in human terrain visual analytics

Walker, Rick, Slingsby, Aidan, Dykes, Jason, Xu, Kai ORCID logoORCID:, Wood, Jo, Nguyen, Phong H., Stephens, Derek, Wong, B. L. William ORCID logoORCID: and Zheng, Yongjun (2013) An extensible framework for provenance in human terrain visual analytics. IEEE Transactions on Visualization and Computer Graphics, 19 (12) . pp. 2139-2148. ISSN 1077-2626 [Article] (doi:10.1109/TVCG.2013.132)

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We describe and demonstrate an extensible framework that supports data exploration and provenance in the context of Human Terrain Analysis (HTA). Working closely with defence analysts we extract requirements and a list of features that characterise data analysed at the end of the HTA chain. From these, we select an appropriate non-classified data source with analogous features, and model it as a set of facets. We develop ProveML, an XML-based extension of the Open Provenance Model, using these facets and augment it with the structures necessary to record the provenance of data, analytical process and interpretations. Through an iterative process, we develop and refine a prototype system for Human Terrain Visual Analytics (HTVA), and demonstrate means of storing, browsing and recalling analytical provenance and process through analytic bookmarks in ProveML. We show how these bookmarks can be combined to form narratives that link back to the live data. Throughout the process, we demonstrate that through structured workshops, rapid prototyping and structured communication with intelligence analysts we are able to establish requirements, and design schema, techniques and tools that meet the requirements of the intelligence community. We use the needs and reactions of defence analysts in defining and steering the methods to validate the framework.

Item Type: Article
Research Areas: A. > School of Science and Technology
A. > School of Science and Technology > Computer Science
Item ID: 11446
Notes on copyright: © 2013 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: Kai Xu
Date Deposited: 12 Aug 2013 05:09
Last Modified: 30 Nov 2022 00:04

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