期刊
JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION
卷 -, 期 -, 页码 -出版社
WILEY
DOI: 10.1111/1752-1688.13153
关键词
decision support systems; information management; public participation; water resources management; streamflow; user-interface; UX design
The open data movement is a major advancement in water management, requiring data to be findable, accessible, interoperable, and reusable. However, there is a lack of accessibility and usability case studies and guidelines for water resources decision making. This commentary highlights knowledge gaps and discusses a general usability testing method that can be applied to any water resources decision support product.
The open data movement represents a major advancement for informed water management. Data that are findable, accessible, interoperable, and reusable-or FAIR-are now prerequisite to responsible data stewardship. In contrast to FAIR, accessibility and usability case studies and guidelines designed around human access and understanding are lacking in the literature, especially for water resources. Such decision support guidelines are critical because (i) inherent visual design trade-offs are not best made using intuition or feedback (perceived preference), and (ii) choosing designs requires a nuanced understanding of why and how the design works (revealed effectiveness). Thus, the goal of this commentary is to highlight knowledge gaps and discuss a general usability testing method which can be applied to any water resources decision support product. The user-testing approach includes (i) interviews about visualization goals, audiences, and the uses and decisions made with the data products, (ii) diagnosis of usability challenges, and (iii) redesign of decision support products given best practices and control versus treatment with intended end-user audiences. We illustrate the method using high-profile U.S. Geological Survey water science products. In sum, optimizing and testing for usability and understandability are as central to stakeholder use as FAIR standards are, and warrant being part of the development of data products and geovisualizations.
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