Project Timeline
UPDATE (March 22, 2018): The Implementation Phase was just approved for funding by the Alfred P. Sloan Foundation for a three-year launch phase that will put our Model for Implementing the Data Curation Network into action. 


June 2018 - May 2021
The University of Minnesota, in partnership with Cornell University, Dryad Data Repository, Duke University, Johns Hopkins University, Pennsylvania State University, University of Michigan, and the University of Illinois, Urbana-Champaign, will engage in a three-year project (June 1, 2018 - May 30, 2021) to expand and launch a cross-institutional staffing model for curating research data. The project was awarded $526,438 in support from the Alfred P. Sloan Foundation to build a valuable new service that will benefit researchers, their disciplines, and users of research data world-wide. During the three-year implementation phase, members of the Data Curation Network will work to add new partners and build the network into a sustainable model. Implementation Phase Grant Narrative (3-pager)

August 2017-May 2018
The Data Curation Network recruited three new institutional partner to join the implementation phase: Duke University, Johns Hopkins University, and the Dryad Data Repository. We presented internationally on our  Model for Implementing the Data Curation Network and worked on building the proposal for the next phase implementation phase.

May 2016-July 2017
The planning phase was competed between May 2016-June 2017 and the project output, A Model for Implementing the Data Curation Network is posted for comment to our Publications page. During the planning phase, project personnel researched and defined the workflows and mechanisms for the Data Curation Network through structured team meetings and virtual collaboration, building on our experiences and expertise. Over the duration of the one-year planning grant, we: 
  • Established metrics and monitor the effort (e.g., cost, time, expertise) involved with curating data at each of our six institutions (Univ Minnesota, Cornell Univ, Penn State Univ, Univ of Illinois, Univ of Michigan, and Washington Univ St. Louis)
  • Sought input from researchers to better understand how data curation services fit into their research workflow and data management needs through informal engagement activities held in parallel on each of our campuses. 
  • Developed a model for sharing staff across institutions to provide data curation services detailing the projected staffing, costs, skills sets, and demand necessary for implementation. 
Our resulting Data Curation Network model describes how a cross-institutional staffing model for data curation across a cohort of partner institutions can be implemented, assessed, and sustained. 


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