Human Factors in Streaming Data Analysis: Challenges and Opportunities for Information Visualization: Human Factors in Streaming Data Analysis

Dasgupta, Aritra; Arendt, Dustin L.; Franklin, Lyndsey R.; Wong, Pak Chung; Cook, Kristin A.

doi:10.1111/cgf.13264

Title: Human Factors in Streaming Data Analysis: Challenges and Opportunities for Information Visualization: Human Factors in Streaming Data Analysis

Journal Article · Fri Sep 01 00:00:00 EDT 2017 · Computer Graphics Forum

DOI:https://doi.org/10.1111/cgf.13264· OSTI ID:1457598

Dasgupta, Aritra ^[1]; Arendt, Dustin L. ^[1]; Franklin, Lyndsey R. ^[1]; Wong, Pak Chung ^[1]; Cook, Kristin A. ^[1]

Pacific Northwest National Laboratory, Richland Washington USA

State-of-the-art visual analytics models and frameworks mostly assume a static snapshot of the data, while in many cases it is a stream with constant updates and changes. Exploration of streaming data poses unique challenges as machine-level computations and abstractions need to be synchronized with the visual representation of the data and the temporally evolving human insights. In the visual analytics literature, we lack a thorough characterization of streaming data and analysis of the challenges associated with task abstraction, visualization design, and adaptation of the role of human-in-the-loop for exploration of data streams. We aim to fill this gap by conducting a survey of the state-of-the-art in visual analytics of streaming data for systematically describing the contributions and shortcomings of current techniques and analyzing the research gaps that need to be addressed in the future. Our contributions are: i) problem characterization for identifying challenges that are unique to streaming data analysis tasks, ii) a survey and analysis of the state-of-the-art in streaming data visualization research with a focus on the visualization design space for dynamic data and the role of the human-in-the-loop, and iii) reflections on the design-trade-offs for streaming visual analytics techniques and their practical applicability in real-world application scenarios.

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Research Organization:: Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)

Sponsoring Organization:: USDOE

DOE Contract Number:: AC05-76RL01830

OSTI ID:: 1457598

Report Number(s):: PNNL-SA-115628

Journal Information:: Computer Graphics Forum, Vol. 37, Issue 1; ISSN 0167-7055

Publisher:: Wiley

Country of Publication:: United States

Language:: English

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