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Robert McDonald's presentation at the DLF panel on NSF Datanet funded projects.
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GETTING THE MOST OUT OF DATANET: A PANEL DISCUSSION OF THE NSF FUNDED DATANET PARTNERSHIPS
Robert H. McDonald – SEAD – Indiana University
Catherine Fitch – TerraPop – Minnesota Population Center
Richard Marciano – Datanet Federation Consortium – University of North Carolina
Sayeed Choudhury – Data Conservancy – Johns Hopkins University
William Michener – DataOne – University of New Mexico
NSF DATANET PROGRAM- OFFICE OF CYBERINFRASTRUCTURE
DATANET ONLINE & TWITTER
Twitter @SEADdatanet @dataconservancy @DateONEorg
Web http://www.sead-data.net http://www.pop.umn.edu http://dataconservancy.org http://www.dataone.org
Tagging #dlfforum #datanet
NSF DATANET PROGRAM
• DataNet efforts effectively balance:• Production infrastructure for operational data
curation services• Research to create next generation data
cyberininfrastructure• DataNet awards are partnerships:• Responsive to user communities to define
their meaningful and useful scope• Form a coordinated network to provide
national, interdisciplinary data models and infrastructure
SEADSustainable Environment – Actionable Datahttp://sead-data.net@SEADdatanet
#OCI0940824
SEAD TEAM
University of Michigan: Margaret Hedstrom (UM PI), Ann Zimmerman (Co-PI and Project Manager), George Alter, Bryan Beecher, Charles Severance, Karen Woollams, Jude Yew. Indiana University: Beth Plale (IU PI), Katy Borner, Robert H. McDonald, Kavitha Chandrasekar, Robert Ping, Stacy Kowalczyk, Robert Light. University of Illinois: Praveen Kumar (UIUC PI), Rob Kooper, Luigi Marini, Terry McLaren. Rensselaer Polytechnic Institute: Jim Myers (RPI PI), Ram Prasanna Govind Krishnan, Lindsay Todd, Adam Wilson.
#OCI0940824
SEAD PARTNERSHIP
Margaret Hedstrom, PIAnn Zimmerman
Beth PlaleKaty BörnerRobert H. McDonald
Praveen Kumar
James Myers
George Alter & Bryan Beecher
7
Sustainability Science
Science
Technology
Economics
Poverty & Justice
Policy
Cooperation
Data challenges• Heterogeneity
of all kinds• Multiple scales• Multidisciplinar
y• Many small
datasets
Provide innovative new models and tools for serving the long tail of scientific research
SEAD’S GOALS
Provide data services that address the pressing needs of researchers working toward sustainability
Integrate these services into an generalizable “Active and Social Curation” infrastructure well-suited to the social structure and economics of long-tail research communities
Develop capabilities to package and migrate datasets to a federated repository infrastructure for long-term preservation
Education, outreach, & training, to maximize value and disseminate SEAD’s contributions to other projects and communities
SEAD’S STRATEGY
Move data curation upstream in the data life cycle• Involve domain scientists in setting
priorities for evolution of data and services
• Use a wide variety of mechanisms to remain resilient in a dynamic research and technology environment
ACTIVE AND SOCIAL CURATION
• Engage researchers during projects, not at the end
• Use information that is automatically captured or generated through tools to reduce the costs of metadata collection and to capture its value in actionable form
• Further reduce costs by re-engineering curation processes to leverage this rich metadata and volunteered effort
ACTIVE CURATION MODEL
Active Curation Social Media
Data
Metadata
WorkflowsReviewRatingCommenting
SEAD LAYERCAKE VIEW
Services over an active content layer that is backed by/harvested into a federated archive infrastructure based on institutional resources
Institutional Repositories
Network of Data Producers
Web User Interface
Active Content Repository
Services Provided
Virtual Archives
User Network
Data Conservancy
IU ICPSR
Content Mining
Curation Decisions
Archival data
generation
Other services
RPI UIUC UM
ACKNOWLEDGMENTS
SEAD is funded by the National Science Foundation under cooperative agreement #OCI0940824