Survey on the analysis of user interactions and visualization provenance

Xu, Kai ORCID logoORCID: https://orcid.org/0000-0003-2242-5440, Ottley, Alvitta, Walchshofer, Conny, Streit, Marc, Chang, Remco and Wenskovitch, John (2020) Survey on the analysis of user interactions and visualization provenance. Computer Graphics Forum, 39 (3) . pp. 757-783. ISSN 0167-7055 [Article] (doi:10.1111/cgf.14035)

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Abstract

There is fast-growing literature on provenance-related research, covering aspects such as its theoretical framework, use cases, and techniques for capturing, visualizing, and analyzing provenance data. As a result, there is an increasing need to identify and taxonomize the existing scholarship. Such an organization of the research landscape will provide a complete picture of the current state of inquiry and identify knowledge gaps or possible avenues for further investigation. In this STAR, we aim to produce a comprehensive survey of work in the data visualization and visual analytics field that focus on the analysis of user interaction and provenance data. We structure our survey around three primary questions: (1) WHY analyze provenance data, (2) WHAT provenance data to encode and how to encode it, and (3) HOW to analyze provenance data. A concluding discussion provides evidence-based guidelines and highlights concrete opportunities for future development in this emerging area. The survey and papers discussed can be explored online interactively at https://provenance-survey.caleydo.org.

Item Type: Article
Keywords (uncontrolled): Computer Networks and Communications
Research Areas: A. > School of Science and Technology > Computer Science
Item ID: 30220
Notes on copyright: © 2020 The Author(s)
Computer Graphics Forum © 2020 The Eurographics Association and John Wiley & Sons Ltd. Published by John Wiley & Sons Ltd.
Eurographics article page states: Except where otherwise noted, this item's license is described as Attribution 4.0 International License
Useful Links:
Depositing User: Kai Xu
Date Deposited: 22 May 2020 14:07
Last Modified: 09 Feb 2022 10:36
URI: https://eprints.mdx.ac.uk/id/eprint/30220

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