Treating data as a first class research object: Data FAIRport and Discoverability

This is a presentation for the NFAIS workshop: Discovery for Scholarly Research: Evolving Needs and Services

For more, see: 

http://www.nfais.org/index.php?option=com_mc&view=mc&mcid=72&eventId=509127&orgId=nfais&recurringId=0 

There has been much talk around FAIR repositories -- making content in a repository Findable, Accessible, Interoperable, and Discoverable-- to facilitate efficiencies throughout the research workflow and allowing researchers to build on data and research that came before them. Figshare works with researchers and publishers to help bridge this gap and connect the valuable underlying data to both the article and the researcher themselves, allowing for more credit for non-traditional outputs of research to spur scientific discovery and incentivize data sharing. This presentation will show how, by providing valuable infrastructure and bringing non-traditional research outputs to the forefront, discoverability of data and data reuse can raise researcher profiles and allow publishers to provide additional value to the journal article itself.