TY - GEN
T1 - Designing and Evaluating Scientific Workflows for Big Data Interactions
AU - Etemadpour, Ronak
AU - Bomhoff, Matthew
AU - Lyons, Eric
AU - Murray, Paul
AU - Forbes, Angus
N1 - Funding Information:
ACKNOWLEDGMENT: Our research was supported by the USDA Agriculture and Food Research Initiative (AFRI), Grant #2013-67015-21231.
Publisher Copyright:
© 2015 IEEE.
PY - 2015/10/30
Y1 - 2015/10/30
N2 - This paper explores the specialized nature of research-oriented web applications that enable interactions with and the visual analysis of ''Big Data,'' i.e., large, heterogeneous scientific datasets. We introduce a pragmatic methodology for the design and evaluation of scientific workflows in research-oriented web applications. Through an in-depth usability study of the CoGe web application, a system that provides a rich set of tools for exploring genomic datasets, we demonstrate: how to identify bottlenecks in multi-step tasks; how to analyze these bottlenecks in order to provide effective solutions for improving user experience; and how these solutions may more generally apply to similar research-oriented websites in other scientific domains that also enable scientific workflows. Specifically, we provide details regarding: our user interviews, the visualization system we created to analyze complex tasks associated with scientific workflows, and how this analysis directly leads to suggestions for improvements in the current implementation of the CoGe web application. A follow-up study was carried out which indicates that our suggestions improved the ability of CoGe users to navigate and complete custom workflows, leading us to believe that our approach could also be applied to other research-oriented web applications that utilize scientific datasets.
AB - This paper explores the specialized nature of research-oriented web applications that enable interactions with and the visual analysis of ''Big Data,'' i.e., large, heterogeneous scientific datasets. We introduce a pragmatic methodology for the design and evaluation of scientific workflows in research-oriented web applications. Through an in-depth usability study of the CoGe web application, a system that provides a rich set of tools for exploring genomic datasets, we demonstrate: how to identify bottlenecks in multi-step tasks; how to analyze these bottlenecks in order to provide effective solutions for improving user experience; and how these solutions may more generally apply to similar research-oriented websites in other scientific domains that also enable scientific workflows. Specifically, we provide details regarding: our user interviews, the visualization system we created to analyze complex tasks associated with scientific workflows, and how this analysis directly leads to suggestions for improvements in the current implementation of the CoGe web application. A follow-up study was carried out which indicates that our suggestions improved the ability of CoGe users to navigate and complete custom workflows, leading us to believe that our approach could also be applied to other research-oriented web applications that utilize scientific datasets.
KW - Big Data
KW - Scientific workflows
KW - user evaluation
KW - visual analytics
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U2 - 10.1109/BDVA.2015.7314290
DO - 10.1109/BDVA.2015.7314290
M3 - Conference contribution
AN - SCOPUS:84962302538
T3 - 2015 Big Data Visual Analytics, BDVA 2015
BT - 2015 Big Data Visual Analytics, BDVA 2015
A2 - Engelke, Ulrich
A2 - Bednarz, Tomasz
A2 - Heinrich, Julian
A2 - Klein, Karsten
A2 - Nguyen, Quang Vinh
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - Big Data Visual Analytics, BDVA 2015
Y2 - 22 September 2015 through 25 September 2015
ER -