An international team of scientists and informatics experts has been awarded a grant from the Belmont Forum (PARSEC), to address challenges with Data Sharing and Credit and develop leading practices in active collaboration with science-driven use cases planned across six countries. Part of the grant builds on the work of the Enabling FAIR Data project as well as work by RDA’s Sharing Rewards and Credit (SHARC) Interest Group (IG), Data Usage Metrics IG, and Scholix IG.

During this one-hour overview of the grant we will discuss the grant objectives and their connection to the work of RDA and ESIP, the next steps for the grant, and ways your organization can benefit from the efforts of the grant.

The overall objective of the grant's data strand is to increase the number of properly cited data sets, provide credit and attribution, and accurately track data reuse. To do this we propose to:
A. Work with ORCID, DataCite, ESIP and RDA, specifically RDA’s Sharing Rewards and Credit (SHARC) Interest Group (IG) to robustly connect identifiers across papers, people, and repositories. Currently, even if these identifiers are included, the necessary linking to allow tracking is not fully implemented.
B. Conduct outreach and adoption campaigns on the importance of persistent identifiers and their infrastructure to all relevant stakeholders—these include the data repositories, publishers, researchers, and the key groups that set standards for publishers for reference tagging.
C. Promote and extend data usage metrics generated by RDA’s Data Usage Metrics Working Group and data citations generated by RDA’s Scholix Working Group that demonstrate the increase in citations and usage based on efforts such as AGU’s Enabling FAIR Data project and others.
D. By working with the grant's science-synthesis team and the selected project teams from our partners we will improve ways to optimize data reuse as well as data deposition of generated data for possible reuse. Demonstrate that through collaboration and better understanding of the value of data sharing when researchers follow the FAIR Data Principles, data are better prepared for others to understand, reuse increases, and discovery is improved.
E. Promote the work of integrated guidance in RDA's SHARC IG that will address recommendations (generic and specific to the ecological/biodiversity community) to improve each step of the processes of data sharing, reuse, credit and reward for researchers and repositories.