Towards a product design assessment of visual analytics in decision support applications: a systematic review

Ovo Adagha (), Richard M. Levy () and Sheelagh Carpendale ()
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Ovo Adagha: University of Calgary
Richard M. Levy: University of Calgary
Sheelagh Carpendale: University of Calgary

Journal of Intelligent Manufacturing, 2017, vol. 28, issue 7, No 9, 1623-1633

Abstract: Abstract There is currently an increasing effort to develop visual analytics (VA) tools that can support human analytical reasoning and decision making. In the last decade, advances in this field has allowed the application of various kinds of VA systems in real-world settings. While this represents a promising start from a product design perspective, part of the challenge to the research community is that current VA tools have evolved without due consideration of standardized design criteria and processes. Accordingly, some questions remain to be addressed on what are the useful, underlying attributes of effective VA tools and how their impact can be measured in human-product interaction. These considerations indicate a need to identify a specific range of VA tools and assess their capabilities through state-of-the-art empirical analysis. To address these issues, we conducted a systematic review of 470 VA papers published between 2006 and 2012. We report on the bibliometric techniques, the evaluation attributes and the metrics that were used to sample and analyze the body of literature. The analysis focused mainly on 26 papers that implemented visual analytics decision support tools. The results are presented in the form of six inductively derived design recommendations that, when taken together, uniquely contribute to the fields of product design and visual analytics.

Keywords: Visual analytics; Decision support; Product design; User experience; Design evaluation; Product development (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1007/s10845-015-1118-5

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