The Data Curation Network will enable data repositories to better support researchers that are faced with a growing number of requirements to ethically share their research data in ways that make it findable, accessible, interoperable and reusable (FAIR).
Data curation enables data discovery and retrieval, maintains data quality, adds value, and provides for re-use over time through activities including authentication, archiving, metadata creation, digital preservation, and transformation.
Data curation skills span a wide variety of data types and discipline-specific data formats such as spatial data, code, databases, chemical spectra, 3D images, and genomic sequencing data. Each repository alone cannot reasonably account for all the curation expertise needed. Sharing our staff enables data repositories to collectively, and more effectively, curate research data in ways that are measurably of greater value than non-curated data.
The Data Curation Network (DCN) serves as the “human layer” in the data repository stack and seamlessly connects local data sets to expert data curators via a cross-institutional shared staffing model. Our vision for a fully operational DCN is to:
- provide expert data curation services for Network partners and (forthcoming) end users,
- create and openly share data curation procedures and best practices,
- support training and development opportunities for an emerging data curator professional community.
The Data Curation Network is supported by grants from the Alfred P. Sloan Foundation (Primary Award: G-2018-10072; Planning Award: G-2016-7044) and the Institute of Museum and Library Services (Workshop Series: RE-85-18-0040-18).