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SEAD
    Sustainable Environment –
    Actionable Data
                                                              CNI Fall Members Meeting
Margaret Hedstrom            Robert H. McDonald                     Arlington, VA
SEAD PI/Project Director     SEAD Sr. Personnel                       12/12/2011
Professor & Associate Dean   Assoc. Dean/Associate Director
UM School of Information     Indiana University
NSF DataNet Program
• new types of organizations that integrate library & archival
  sciences, cyberinfrastructure, computer & information sciences, &
  domain science expertise
• provide reliable digital preservation, access, integration, and
  analysis capabilities for science and/or engineering data over a
  decades-long timeline;
• continuously anticipate and adapt to changes in technologies and in
  user needs and expectations;
• engage in research to drive the leading edge forward
• serve as component elements of an interoperable data preservation
  and access network

http://www.nsf.gov/funding/pgm_summ.jsp?pims_id=503141
• SEAD’s Unique
Partners
             Contributions
             – Address domain-driven
               needs & requirements
             – Serve scientists and
               researchers in the “long tail”
             – Integrate existing
               technologies, tools &
               services (rather than build
               new from scratch)
Sustainability
        Science

               Science


Cooperation               Technology




  Policy                  Economics

              Poverty &
               Justice




                                       4
Data challenges
•   Heterogeneity of
    all kinds
•   Multiple scales
•   Multidisciplinary
•   Many small
    datasets
The long tail of scientific research


• Small and derived data sets
• Heterogeneous data
• Multiple sources of data
• Short-lived data with long-term
  value
• Value of data grows when combined
  & integrated
SEAD’s Goals
• Provide data services that address the needs of
  researchers working toward sustainability
• Integrate these services into an generalizable “Active and
  Social Curation” infrastructure suited to the social
  structure and economics of long-tail research
  communities
• Develop capabilities to package and migrate the most
  valuable datasets to a federated repository
  infrastructure for long-term preservation
• Education, outreach, & training to disseminate SEAD‟s
  contributions to other projects & communities
SEAD’s Strategy

• Leverage social media for discovery of
  data, interest, and expertise
• Move data curation upstream in the data life
  cycle
• Involve domain scientists in setting priorities
  for evolution of data and services
• Take advantage of existing infrastructures
  (Institutional Repositories, ICPSR) for long-
  term preservation
Active and Social Curation
• Engage researchers during projects, not at the
  end
• Automatically capture metadata as defined by
  the data producers
• Provide facilities for
  commentary, recommendations, and mark-up
  of data
• Further reduce costs by re-engineering
  curation processes to leverage this rich
  metadata and volunteered effort
Active Curation Model
Active Curation                     Social Media

Workflows
                             Data                  Review
                                                   Rating
                                                   Commenting




                  Metadata
SEAD Status

                 Phase 1                Phase 2
                Months 1-18            Years 3-5
                                     Grow SEAD
                 Develop
                                    users, data, an
                 Prototype          d functionality



                   SEAD start date: 10/1/2011


    In other words, SEAD is not ready to accept your data!
SEAD Personnel
•   Margaret Hedstrom, PI (Michigan)
•   Praveen Kumar, co-PI (Illinois)
•   Jim Myers, co-PI (RPI)
•   Beth Plale, co-PI (Indiana)
•   Ann Zimmerman, co-PI/Project Manager
    (Michigan)
•   George Alter (ICPSR)
•   Bryan Beecher (ICPSR)
•   Katy Börner (Indiana)
•   Robert McDonald (Indiana)
•   Jude Yew, Post-doc (Michigan)
•    + many more to come
http://sead-data.net
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.
SEAD Cyberinfrastructure
• An international resource
  for sustainability science
• Novel technical and
  business approaches to
  supporting the long-tail
  of research data
• Lifecycle support:
  actionable data services
  integrated with curation
  and preservation
  infrastructure
Key Challenges for SEAD
Cyberinfrastructure
 • Managed Data storage and services are expensive!
 • Begging for metadata doesn‟t work!
 • Curation and preservation are time consuming!
 • The long-tail is not standardized!
 • Data collections are always missing something
   valuable!
 • Data models evolve!
 • Cyberinfrastructure is obsolete by the time you build
   it!
 • Building Community as you leverge
   cyberinfrastructure
SEAD: Social Networking
•   Co-authorship
•   Co-funding
•   Micro-citation
•   Shared project repositories
•   Shared tags
•   Threaded discussions
•   Quoting, forwarding, …
Linked Data and Repositories
•   Tag and annotate data
•   Overlay it with reference data
•   Organize it in domain terminology
•   Link it to
    people, papers, projects, conversations…
Using Science of Science to Link
Repositories
KEY SEAD Questions
• What could SEAD capture when?
• How can SEAD provide direct value
  to data producers, users, and
  curators?
• How can robust web-services and
  social computing lower barriers and
  reduce/realign costs?
SEAD: Active Content Repository
• With the „Big Picture‟ graph in-hand, curators
  can:
 ▫ Focus on what to curate and when,
 ▫ Automate parts of the process
 ▫ Use existing/emerging technologies for packaging
   and preserving datasets
 ▫ Better manage federated repositories
SEAD: Leveraging Existing Resources
• Cyberinfrastructure
 ▫ IU Data Capacitor/HPC Capabilities
 ▫ UIUC/NCSA HPC Capabilities
 ▫ Rensselaer CCNI Capabilities
• Repositories
 ▫   UM Deep Blue
 ▫   IU ScholarWorks
 ▫   ICPSR Repository
 ▫   UIUC IDEALS
SEAD LayerCake View
• Services over an
                                               Network of Data
                                                 Producers

  active content layer
  that is backed
  by/harvested into a                         Web User Interface

  federated archive                        Active Content Repository


  infrastructure based
                                                Services Provided
                                   Content     Curation      Archival      Other
                                                               data       services
                                   Mining      Decisions
  on institutional                                          generation


                                                Virtual Archives
  resources                                  Institutional Repositories

                        Data          IU          RPI        UIUC         UM         ICPSR
                     Conservancy


                                                 User Network
CI Technical Approach
    Active and Social Curation                                 OAIS Repository Federation
                                        Curation Boundary
                                                                Automated
                                                                 Curation
    Data          Metadata                                     Workflow/Rule
Acquisition,     Management                                       Engine
Analysis and             DDI3.
                                                                  Operates on
 Simulation      METS, PREMIS, MODS
                                                               Metadata, Content          Scholarly
                                                               Objects and Trigger
                 , DC, SensorML, OGC,
                           …                                         Events             Communication

                                   Ingest scripts:
                                                                             Ingest, AIPs
                       Appraisal fixity, integrity, a
                                                                       Compound Objects - OAI-ORE
VIVO/                    and CI Technical Approach
                                  uthentication, tr
Linked     Active      Selection   ansformation
 Data     Content                                                  Digital Repository Federation
                                                                     (OAIS compliant)
         Repositor                                                                           Preservation
                                                                                               Actions
             y
                                                                          Dissemination Packages

                                 Wide-Area File System

 Search, Brows
       e,
                                                              Migration
                                                                 and                 Access Mechanisms
 Annotation, V    Use, Reuse, R
                                                                                     and E-Scholarship
  isualization     epurposing                                 Emulation
                                           Contributor User                               Services
     Tools            Tools                                     Tools
Toward PetaScale Data




• Internet2 upgrade:
  ▫ Total bandwidth from 100 Gbps to 8.8 Tbps
  ▫ Moving a petabyte of data will go from from 10 days to 25 hrs
SEAD 18 Month Prototype Targets for
Cyberinfrastructure
• Active and Social Content Curation
 ▫ Pilot Active Content Repository, VIVO deployments
 ▫ Exemplar services for Data Ingest, Discovery, Re-
   use, Curation
• CI for Long-term Access
 ▫ Data model, protocol design/development
 ▫ Pilot Federated Repository infrastructure
SEAD CI QuickView
• SEAD will quickly build a repository and data services infrastructure
  for sustainability research that can be responsively adapted based on
  community feedback – Community Agile Development
• SEAD will leverage existing tools and emerging practices to
  dramatically enhance the interactions of researchers and data
  librarians – Active Curation
• SEAD‟s focus on the long-tail will force an emphasis on ease-of-use
  and low costs that is critical for long-term sustainability – Leverage
  Existing Institution Resources for Long-term Access
• SEAD will leverage experiences in the sustainability research
  community to provide guidance for other long-tail communities
  making the transition to an interdisciplinary, systems-oriented
  approach to research – Sustainability and Resource Growth
  Partnership and Collaboration
Acknowledgments
SEAD is funded by the National Science
Foundation under cooperative agreement
#OCI0940824

• For more on SEAD go to:
• http://sead-data.net

• Follow us on Twitter
  @SEADdatanet



                            http://sead-data.net

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CNI Fall 2011 Meeting Presentation Margaret Hedstrom & Robert McDonald (Dec. 2011)

  • 1. SEAD Sustainable Environment – Actionable Data CNI Fall Members Meeting Margaret Hedstrom Robert H. McDonald Arlington, VA SEAD PI/Project Director SEAD Sr. Personnel 12/12/2011 Professor & Associate Dean Assoc. Dean/Associate Director UM School of Information Indiana University
  • 2. NSF DataNet Program • new types of organizations that integrate library & archival sciences, cyberinfrastructure, computer & information sciences, & domain science expertise • provide reliable digital preservation, access, integration, and analysis capabilities for science and/or engineering data over a decades-long timeline; • continuously anticipate and adapt to changes in technologies and in user needs and expectations; • engage in research to drive the leading edge forward • serve as component elements of an interoperable data preservation and access network http://www.nsf.gov/funding/pgm_summ.jsp?pims_id=503141
  • 3. • SEAD’s Unique Partners Contributions – Address domain-driven needs & requirements – Serve scientists and researchers in the “long tail” – Integrate existing technologies, tools & services (rather than build new from scratch)
  • 4. Sustainability Science Science Cooperation Technology Policy Economics Poverty & Justice 4
  • 5. Data challenges • Heterogeneity of all kinds • Multiple scales • Multidisciplinary • Many small datasets
  • 6. The long tail of scientific research • Small and derived data sets • Heterogeneous data • Multiple sources of data • Short-lived data with long-term value • Value of data grows when combined & integrated
  • 7. SEAD’s Goals • Provide data services that address the needs of researchers working toward sustainability • Integrate these services into an generalizable “Active and Social Curation” infrastructure suited to the social structure and economics of long-tail research communities • Develop capabilities to package and migrate the most valuable datasets to a federated repository infrastructure for long-term preservation • Education, outreach, & training to disseminate SEAD‟s contributions to other projects & communities
  • 8. SEAD’s Strategy • Leverage social media for discovery of data, interest, and expertise • Move data curation upstream in the data life cycle • Involve domain scientists in setting priorities for evolution of data and services • Take advantage of existing infrastructures (Institutional Repositories, ICPSR) for long- term preservation
  • 9. Active and Social Curation • Engage researchers during projects, not at the end • Automatically capture metadata as defined by the data producers • Provide facilities for commentary, recommendations, and mark-up of data • Further reduce costs by re-engineering curation processes to leverage this rich metadata and volunteered effort
  • 10. Active Curation Model Active Curation Social Media Workflows Data Review Rating Commenting Metadata
  • 11. SEAD Status Phase 1 Phase 2 Months 1-18 Years 3-5 Grow SEAD Develop users, data, an Prototype d functionality SEAD start date: 10/1/2011 In other words, SEAD is not ready to accept your data!
  • 12. SEAD Personnel • Margaret Hedstrom, PI (Michigan) • Praveen Kumar, co-PI (Illinois) • Jim Myers, co-PI (RPI) • Beth Plale, co-PI (Indiana) • Ann Zimmerman, co-PI/Project Manager (Michigan) • George Alter (ICPSR) • Bryan Beecher (ICPSR) • Katy Börner (Indiana) • Robert McDonald (Indiana) • Jude Yew, Post-doc (Michigan) • + many more to come
  • 14. 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.
  • 15. SEAD Cyberinfrastructure • An international resource for sustainability science • Novel technical and business approaches to supporting the long-tail of research data • Lifecycle support: actionable data services integrated with curation and preservation infrastructure
  • 16. Key Challenges for SEAD Cyberinfrastructure • Managed Data storage and services are expensive! • Begging for metadata doesn‟t work! • Curation and preservation are time consuming! • The long-tail is not standardized! • Data collections are always missing something valuable! • Data models evolve! • Cyberinfrastructure is obsolete by the time you build it! • Building Community as you leverge cyberinfrastructure
  • 17. SEAD: Social Networking • Co-authorship • Co-funding • Micro-citation • Shared project repositories • Shared tags • Threaded discussions • Quoting, forwarding, …
  • 18. Linked Data and Repositories • Tag and annotate data • Overlay it with reference data • Organize it in domain terminology • Link it to people, papers, projects, conversations…
  • 19. Using Science of Science to Link Repositories
  • 20. KEY SEAD Questions • What could SEAD capture when? • How can SEAD provide direct value to data producers, users, and curators? • How can robust web-services and social computing lower barriers and reduce/realign costs?
  • 21. SEAD: Active Content Repository • With the „Big Picture‟ graph in-hand, curators can: ▫ Focus on what to curate and when, ▫ Automate parts of the process ▫ Use existing/emerging technologies for packaging and preserving datasets ▫ Better manage federated repositories
  • 22. SEAD: Leveraging Existing Resources • Cyberinfrastructure ▫ IU Data Capacitor/HPC Capabilities ▫ UIUC/NCSA HPC Capabilities ▫ Rensselaer CCNI Capabilities • Repositories ▫ UM Deep Blue ▫ IU ScholarWorks ▫ ICPSR Repository ▫ UIUC IDEALS
  • 23. SEAD LayerCake View • Services over an Network of Data Producers active content layer that is backed by/harvested into a Web User Interface federated archive Active Content Repository infrastructure based Services Provided Content Curation Archival Other data services Mining Decisions on institutional generation Virtual Archives resources Institutional Repositories Data IU RPI UIUC UM ICPSR Conservancy User Network
  • 24. CI Technical Approach Active and Social Curation OAIS Repository Federation Curation Boundary Automated Curation Data Metadata Workflow/Rule Acquisition, Management Engine Analysis and DDI3. Operates on Simulation METS, PREMIS, MODS Metadata, Content Scholarly Objects and Trigger , DC, SensorML, OGC, … Events Communication Ingest scripts: Ingest, AIPs Appraisal fixity, integrity, a Compound Objects - OAI-ORE VIVO/ and CI Technical Approach uthentication, tr Linked Active Selection ansformation Data Content Digital Repository Federation (OAIS compliant) Repositor Preservation Actions y Dissemination Packages Wide-Area File System Search, Brows e, Migration and Access Mechanisms Annotation, V Use, Reuse, R and E-Scholarship isualization epurposing Emulation Contributor User Services Tools Tools Tools
  • 25. Toward PetaScale Data • Internet2 upgrade: ▫ Total bandwidth from 100 Gbps to 8.8 Tbps ▫ Moving a petabyte of data will go from from 10 days to 25 hrs
  • 26. SEAD 18 Month Prototype Targets for Cyberinfrastructure • Active and Social Content Curation ▫ Pilot Active Content Repository, VIVO deployments ▫ Exemplar services for Data Ingest, Discovery, Re- use, Curation • CI for Long-term Access ▫ Data model, protocol design/development ▫ Pilot Federated Repository infrastructure
  • 27. SEAD CI QuickView • SEAD will quickly build a repository and data services infrastructure for sustainability research that can be responsively adapted based on community feedback – Community Agile Development • SEAD will leverage existing tools and emerging practices to dramatically enhance the interactions of researchers and data librarians – Active Curation • SEAD‟s focus on the long-tail will force an emphasis on ease-of-use and low costs that is critical for long-term sustainability – Leverage Existing Institution Resources for Long-term Access • SEAD will leverage experiences in the sustainability research community to provide guidance for other long-tail communities making the transition to an interdisciplinary, systems-oriented approach to research – Sustainability and Resource Growth Partnership and Collaboration
  • 28. Acknowledgments SEAD is funded by the National Science Foundation under cooperative agreement #OCI0940824 • For more on SEAD go to: • http://sead-data.net • Follow us on Twitter @SEADdatanet http://sead-data.net

Editor's Notes

  1. How may people in this audience have an institutional repository? Are you using it to publish data?