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Symposium on Global Scientific Data Infrastructures Panel Two: Stakeholder Communities in the DWF Ann Wolpert, Massachusetts Institute of Technology Board.

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Presentation on theme: "Symposium on Global Scientific Data Infrastructures Panel Two: Stakeholder Communities in the DWF Ann Wolpert, Massachusetts Institute of Technology Board."— Presentation transcript:

1 Symposium on Global Scientific Data Infrastructures Panel Two: Stakeholder Communities in the DWF Ann Wolpert, Massachusetts Institute of Technology Board on Research Data and Information Policy and Global Affairs Division, National Academy of Sciences National Academy of Sciences, Washington, DC Wednesday, August 29, 2012

2 Three stakeholder perspectives University administrator – Economics of Research I institutions – Incentives University librarian – Information Science research program – Digital preservation – Getting to scale Institutional repository operator – Many media – Data management plans

3 Six broad priority changes 1.Data no longer a private preserve 2.Give credit for data communication and collaboration 3.Develop common standards for communicating data 4.Mandate “intelligent openness” for data relevant of published papers 5.Strengthen the cohort of data scientists 6.Develop new software tools to automate and simplify the creation and exploitation of data sets

4 Recommendation 2 Universities and research institutes should play a major role in supporting an open data culture 1.Value data communication as an academic criterion 2.Develop a data strategy and local capacity to curate own knowledge resources and support data needs 3.Stipulate open data as a default

5 Digital Preservation Perspective Existing international community of digital preservation practice History of & structures for collaboration; regionally, nationally, internationally Mission-based with a shared purpose Funded to support research & scholarship, and to preserve the cultural & intellectual record Interconnected projects; getting to scale Constrained by intellectual property & funding

6 Celebrate progress, consolidate lessons learned, plan for the future Six lenses/aspects of alignment: 1.Legal 2.Organizational 3.Standards 4.Technical 5.Economic 6.Education Two keys to successful collaboration: 1.Plan broad goals for collaboration 2.Build on existing relationships

7 Some elements of the existing digital preservation ecosystem National Libraries collaborations National Digital Stewardship Alliance DuraSpace HathiTrust Center for Research Libraries OCLC International Internet Preservation Consortium Digital Preservation Network (DPN) Digital Public Library of America/Europeana Linked Data Authority files (VIAF, ORCID, etc)

8 Institutional Repository Perspective Things to think about Security and integrity Privacy Life cycle management What’s “interoperability” Who pays Who benefits

9 Consider incentives that reinforce DWF mission and vision Funding agencies/foundations Primary researchers Research institutions Scholarly journal publishers Data publishers “Reusers”

10 How could DWF benefit research organizations? Reduce costs of data management and access by establishing core practices for government data producers: – Minimum and recommended practice for machine- actionable metadata, provenance, and versioning – Minimum and recommended practice for open formats, open data licenses, data access API’s – Model contracts language for subcontractors who collect and deliver data to government

11 How could DWF benefit research organizations? Reduce costs of compliance for confidential data use: – Model data usage agreements that enable data interoperability in a protected environment – Establish a data privacy expert board (e.g. under NIST) to identify safe-harbor methodologies for sharing confidential information

12 How could DWF benefit research organizations? Identify core practices for data management planning and evaluation for sponsored research: – Identify model data management plan elements and criteria for government sponsored research – Identify minimal and recommended data citation requirements and standard – Identify minimal and recommended practices for tracking compliance with data management plans and citation requirements


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