Robert McDonald's presentation at the DLF panel on NSF Datanet funded projects.

1. 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

2. 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

3. 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

4. SEAD
Sustainable Environment – Actionable
Data
http://sead-data.net
@SEADdatanet
#OCI0940824

5. 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

6. SEAD PARTNERSHIP
Beth Plale
Margaret Hedstrom, PI Katy Börner
Ann Zimmerman Robert H. McDonald
Praveen James Myers
Kumar
George Alter & Bryan Beecher

7. Sustainability
Science
Science
Cooperation Technology
Policy Economics
Poverty &
Justice
7

8. Data
challenges
• Heterogeneity
of all kinds
• Multiple scales
• Multidisciplinary
• Many small
datasets

9. Provide innovative new
models and tools for
serving the long tail of
scientific research

10. 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

11. 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

12. 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

13. ACTIVE CURATION MODEL
Active Curation Social Media
Review
Workflows Rating
Data Commenting
Metadata

14. SEAD LAYERCAKE VIEW
Network of Data
Producers
 Services over an
active content layer
Web User Interface
that is backed
Active Content Repository
by/harvested into a
Services Provided
federated archive Content Curation Archival
data
Other
Mining Decisions services
infrastructure based generation
on institutional Virtual Archives
resources Institutional Repositories
Data IU RPI UIUC UM ICPSR
Conservancy
User Network

15. ACKNOWLEDGMENTS
SEAD is funded by the National Science
Foundation under cooperative agreement
#OCI0940824