research-article

Employing a Parametric Model for Analytic Provenance

Authors:

Yingjie Victor Chen,

Zhenyu Cheryl Qian,

Robert Woodbury,

Chris D. ShawAuthors Info & Claims

ACM Transactions on Interactive Intelligent Systems (TiiS), Volume 4, Issue 1

Article No.: 6, Pages 1 - 32

https://doi.org/10.1145/2591510

Published: 01 April 2014 Publication History

Abstract

We introduce a propagation-based parametric symbolic model approach to supporting analytic provenance. This approach combines a script language to capture and encode the analytic process and a parametrically controlled symbolic model to represent and reuse the logic of the analysis process. Our approach first appeared in a visual analytics system called CZSaw. Using a script to capture the analyst’s interactions at a meaningful system action level allows the creation of a parametrically controlled symbolic model in the form of a Directed Acyclic Graph (DAG). Using the DAG allows propagating changes. Graph nodes correspond to variables in CZSaw scripts, which are results (data and data visualizations) generated from user interactions. The user interacts with variables representing entities or relations to create the next step’s results. Graph edges represent dependency relationships among nodes. Any change to a variable triggers the propagation mechanism to update downstream dependent variables and in turn updates data views to reflect the change. The analyst can reuse parts of the analysis process by assigning new values to a node in the graph. We evaluated this symbolic model approach by solving three IEEE VAST Challenge contest problems (from IEEE VAST 2008, 2009, and 2010). In each of these challenges, the analyst first created a symbolic model to explore, understand, analyze, and solve a particular subproblem and then reused the model via its dependency graph propagation mechanism to solve similar subproblems. With the script and model, CZSaw supports the analytic provenance by capturing, encoding, and reusing the analysis process. The analyst can recall the chronological states of the analysis process with the CZSaw script and may interpret the underlying rationale of the analysis with the symbolic model.

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Cited By

Gadhave KCutler ZLex A(2022)Reusing Interactive Analysis WorkflowsComputer Graphics Forum10.1111/cgf.1452841:3(133-144)Online publication date: 12-Aug-2022
https://doi.org/10.1111/cgf.14528
de Oliveira WBraga RDavid JStroele VCampos FCastro G(2022)Visionary: a framework for analysis and visualization of provenance dataKnowledge and Information Systems10.1007/s10115-021-01645-664:2(381-413)Online publication date: 1-Feb-2022
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Xu KOttley AWalchshofer CStreit MChang RWenskovitch J(2020)Survey on the Analysis of User Interactions and Visualization ProvenanceComputer Graphics Forum10.1111/cgf.1403539:3(757-783)Online publication date: 18-Jul-2020
https://doi.org/10.1111/cgf.14035
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Index Terms

Employing a Parametric Model for Analytic Provenance
1. Human-centered computing
  1. Human computer interaction (HCI)

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Published In

cover image ACM Transactions on Interactive Intelligent Systems

ACM Transactions on Interactive Intelligent Systems Volume 4, Issue 1

Special Issue on Interactive Computational Visual Analytics

April 2014

181 pages

ISSN:2160-6455

EISSN:2160-6463

DOI:10.1145/2602757

Issue’s Table of Contents

Copyright © 2014 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 01 April 2014

Accepted: 01 September 2013

Revised: 01 July 2013

Received: 01 May 2012

Published in TIIS Volume 4, Issue 1

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Cited By

Gadhave KCutler ZLex A(2022)Reusing Interactive Analysis WorkflowsComputer Graphics Forum10.1111/cgf.1452841:3(133-144)Online publication date: 12-Aug-2022
https://doi.org/10.1111/cgf.14528
de Oliveira WBraga RDavid JStroele VCampos FCastro G(2022)Visionary: a framework for analysis and visualization of provenance dataKnowledge and Information Systems10.1007/s10115-021-01645-664:2(381-413)Online publication date: 1-Feb-2022
https://dl.acm.org/doi/10.1007/s10115-021-01645-6
Xu KOttley AWalchshofer CStreit MChang RWenskovitch J(2020)Survey on the Analysis of User Interactions and Visualization ProvenanceComputer Graphics Forum10.1111/cgf.1403539:3(757-783)Online publication date: 18-Jul-2020
https://doi.org/10.1111/cgf.14035
Woodbury RMohiuddin ACichy MMueller V(2017)Interactive design galleries: A general approach to interacting with design alternativesDesign Studies10.1016/j.destud.2017.05.00152(40-72)Online publication date: Sep-2017
https://doi.org/10.1016/j.destud.2017.05.001
Kodagoda NPontis SSimmie DAttfield SWong BBlandford AHankin C(2016)Using Machine Learning to Infer Reasoning Provenance From User Interaction Log DataJournal of Cognitive Engineering and Decision Making10.1177/155534341667278211:1(23-41)Online publication date: 25-Oct-2016
https://doi.org/10.1177/1555343416672782

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