Reusing Scientific Data: How Earthquake Engineering Researchers Assess the Reusability of Colleagues’ Data
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Investments in cyberinfrastructure and e-Science initiatives are motivated by the desire to accelerate scientific discovery. Always viewed as a foundation of science, data sharing is appropriately seen as critical to the success of such initiatives, but new technologies supporting increasingly data-intensive and collaborative science raise significant challenges and opportunities. Overcoming the technical and social challenges to broader data sharing is a common and important research objective, but increasing the supply and accessibility of scientific data is no guarantee data will be applied by scientists. Before reusing data created by others, scientists need to assess the data’s relevance, they seek confidence the data can be understood, and they must trust the data. Using interview data from earthquake engineering researchers affiliated with the George E. Brown, Jr. Network for Earthquake Engineering Simulation (NEES), we examine how these scientists assess the reusability of colleagues’ experimental data for model validation.
Key wordsdata reuse data sharing data quality trust scientific data collections data repositories e-Science cyberinfrastructure
We want to thank John L. King, Stephanie Teasley, Elizabeth Yakel, and the reviewers and editors at CSCW for their feedback on early versions of this work. We also want to thank Martha Gukeisen for her help during data collection. This research is based on work supported by the National Science Foundation, Award number CMMI-0714116 to the University of Michigan. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.
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