EAGER: Crowdsourcing Metadata Enhancements to Improve the Discoverability and Reusability of Scientific Data: Experimental Evaluations
This project will conduct a series of experiments with different user communities (secondary data users, students, data librarians, and other volunteers) to determine what would motivate them to contribute metadata enhancements to data that have been archived, but that are not sufficiently FAIR (Findable, Accessible, Interoperable, and Reusable). Current practice relies on the efforts of data producers and professional data curators to produce and provide metadata, including variable level data descriptors, study key words, and bibliographic citations to data-related publications. These efforts are expensive and, as a result, are often undersupplied, leaving data that has been archived and shared with the scientific community of limited value for reuse. The experiments in this project will directly inform efforts to engage the broader community in crowdsourcing enhancements to metadata so that tools and interfaces can be designed that will induce others to participate in this valuable activity, tapping into their knowledge of and interest in data in particular domains to increase data FAIRness.
National Science Foundation
Funding Period: 10/1/2018 to 9/30/2020