Literature DB >> 26356879

Progressive Visual Analytics: User-Driven Visual Exploration of In-Progress Analytics.

Charles D Stolper, Adam Perer, David Gotz.   

Abstract

As datasets grow and analytic algorithms become more complex, the typical workflow of analysts launching an analytic, waiting for it to complete, inspecting the results, and then re-Iaunching the computation with adjusted parameters is not realistic for many real-world tasks. This paper presents an alternative workflow, progressive visual analytics, which enables an analyst to inspect partial results of an algorithm as they become available and interact with the algorithm to prioritize subspaces of interest. Progressive visual analytics depends on adapting analytical algorithms to produce meaningful partial results and enable analyst intervention without sacrificing computational speed. The paradigm also depends on adapting information visualization techniques to incorporate the constantly refining results without overwhelming analysts and provide interactions to support an analyst directing the analytic. The contributions of this paper include: a description of the progressive visual analytics paradigm; design goals for both the algorithms and visualizations in progressive visual analytics systems; an example progressive visual analytics system (Progressive Insights) for analyzing common patterns in a collection of event sequences; and an evaluation of Progressive Insights and the progressive visual analytics paradigm by clinical researchers analyzing electronic medical records.

Mesh:

Year:  2014        PMID: 26356879     DOI: 10.1109/TVCG.2014.2346574

Source DB:  PubMed          Journal:  IEEE Trans Vis Comput Graph        ISSN: 1077-2626            Impact factor:   4.579


  2 in total

1.  Chronodes: Interactive Multifocus Exploration of Event Sequences.

Authors:  Peter J Polack; Shang-Tse Chen; Minsuk Kahng; Kaya DE Barbaro; Rahul Basole; Moushumi Sharmin; Duen Horng Chau
Journal:  ACM Trans Interact Intell Syst       Date:  2018-02

2.  Visual analysis of blow molding machine multivariate time series data.

Authors:  Maath Musleh; Angelos Chatzimparmpas; Ilir Jusufi
Journal:  J Vis (Tokyo)       Date:  2022-07-11       Impact factor: 1.974

  2 in total

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