A work-centered visual analytics model to support engineering design with interactive visualization and data-mining

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Citations (Scopus)

Abstract

To support the knowledge discovery and decision making from large-scale, multi-dimensional, continuous data sets, novel systems of visual analytics need the capability to identify hidden patterns in data that are critical for in-depth analysis. In this paper, we present a work-centered approach to support visual analytics of complex data sets by combining usercentered interactive visualization and data-oriented computational algorithms. We design and implement a specific system prototype, Learning-based Interactive Visualization for Engineering design (LIVE), for engineering designers to handle overwhelming information such as numerous design alternatives generated from automatic simulating software. During the exploration within a "trade space" consisting of possible designs and potential solutions, engineering designers want to analyze the data, discover hidden patterns, and identify preferable solutions. The proposed system allows designers to interactively examine large design data sets through visualization and interactively construct data models from automatic data mining algorithms. We expect that our approach can help designers efficiently and effectively make sense of large-scale design data sets and generate decisions. We also report a preliminary evaluation on our system by analyzing a real engineering design problem related to aircraft wing sizing.

Original languageEnglish (US)
Title of host publicationProceedings of the 45th Annual Hawaii International Conference on System Sciences, HICSS-45
PublisherIEEE Computer Society
Pages1845-1854
Number of pages10
ISBN (Print)9780769545257
DOIs
StatePublished - Jan 1 2012
Event2012 45th Hawaii International Conference on System Sciences, HICSS 2012 - Maui, HI, United States
Duration: Jan 4 2012Jan 7 2012

Publication series

NameProceedings of the Annual Hawaii International Conference on System Sciences
ISSN (Print)1530-1605

Other

Other2012 45th Hawaii International Conference on System Sciences, HICSS 2012
CountryUnited States
CityMaui, HI
Period1/4/121/7/12

Fingerprint

Data mining
Visualization
Data structures
Learning systems
Decision making

All Science Journal Classification (ASJC) codes

  • Engineering(all)

Cite this

Yan, X., Qiao, M., Li, J., Simpson, T. W., Stump, G. M., & Zhang, X. (2012). A work-centered visual analytics model to support engineering design with interactive visualization and data-mining. In Proceedings of the 45th Annual Hawaii International Conference on System Sciences, HICSS-45 (pp. 1845-1854). [6149110] (Proceedings of the Annual Hawaii International Conference on System Sciences). IEEE Computer Society. https://doi.org/10.1109/HICSS.2012.87
Yan, Xin ; Qiao, Mu ; Li, Jia ; Simpson, Timothy W. ; Stump, Gary M. ; Zhang, Xiaolong. / A work-centered visual analytics model to support engineering design with interactive visualization and data-mining. Proceedings of the 45th Annual Hawaii International Conference on System Sciences, HICSS-45. IEEE Computer Society, 2012. pp. 1845-1854 (Proceedings of the Annual Hawaii International Conference on System Sciences).
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abstract = "To support the knowledge discovery and decision making from large-scale, multi-dimensional, continuous data sets, novel systems of visual analytics need the capability to identify hidden patterns in data that are critical for in-depth analysis. In this paper, we present a work-centered approach to support visual analytics of complex data sets by combining usercentered interactive visualization and data-oriented computational algorithms. We design and implement a specific system prototype, Learning-based Interactive Visualization for Engineering design (LIVE), for engineering designers to handle overwhelming information such as numerous design alternatives generated from automatic simulating software. During the exploration within a {"}trade space{"} consisting of possible designs and potential solutions, engineering designers want to analyze the data, discover hidden patterns, and identify preferable solutions. The proposed system allows designers to interactively examine large design data sets through visualization and interactively construct data models from automatic data mining algorithms. We expect that our approach can help designers efficiently and effectively make sense of large-scale design data sets and generate decisions. We also report a preliminary evaluation on our system by analyzing a real engineering design problem related to aircraft wing sizing.",
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Yan, X, Qiao, M, Li, J, Simpson, TW, Stump, GM & Zhang, X 2012, A work-centered visual analytics model to support engineering design with interactive visualization and data-mining. in Proceedings of the 45th Annual Hawaii International Conference on System Sciences, HICSS-45., 6149110, Proceedings of the Annual Hawaii International Conference on System Sciences, IEEE Computer Society, pp. 1845-1854, 2012 45th Hawaii International Conference on System Sciences, HICSS 2012, Maui, HI, United States, 1/4/12. https://doi.org/10.1109/HICSS.2012.87

A work-centered visual analytics model to support engineering design with interactive visualization and data-mining. / Yan, Xin; Qiao, Mu; Li, Jia; Simpson, Timothy W.; Stump, Gary M.; Zhang, Xiaolong.

Proceedings of the 45th Annual Hawaii International Conference on System Sciences, HICSS-45. IEEE Computer Society, 2012. p. 1845-1854 6149110 (Proceedings of the Annual Hawaii International Conference on System Sciences).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Yan X, Qiao M, Li J, Simpson TW, Stump GM, Zhang X. A work-centered visual analytics model to support engineering design with interactive visualization and data-mining. In Proceedings of the 45th Annual Hawaii International Conference on System Sciences, HICSS-45. IEEE Computer Society. 2012. p. 1845-1854. 6149110. (Proceedings of the Annual Hawaii International Conference on System Sciences). https://doi.org/10.1109/HICSS.2012.87