1. NSDL 2.0: Creating a collaborative digital library Dean Krafft, Cornell University dean@cs.cornell.edu

2. Structure of the Talk  Project Overview and NSDL 1.0  The Fedora-based NSDL Data Repository (NDR) and NSDL 2.0  Inspiring Contribution and Collaboration: ExpertVoices, Soft Matter Wiki, etc.  IS Challenges for NSDL  Q&A

3. What is the NSDL?  An NSF-funded $20 million/year program in Science, Technology, Engineering and Mathematics (STEM) education  A digital library describing nearly two million carefully selected online STEM resources from well over 100 collections (at http://nsdl.org)  A core integration team (Cornell, UCAR, Columbia) working with 9 “pathways” portals and over 200 NSF grantees  A large community of researchers, librarians, content providers, developers, students, and teachers

4. Portals to the NSDL

5. NSDL 1.0  A “Union Catalog”  OAI-PMH Harvesting  Central Metadata Database  OAI Server for catalog  Search index of metadata/content  Initial K-Gray Portal: nsdl.org

6. Infrastructure overview: NSDL 1.0 STEM Collections on the Web Central Metadata Repository Search Service Archive Service Collection Registration System NSDL.org Portal Protocol: OAI-PMH HTTP REST SQL

7. NSDL 1.0 Lessons  Metadata Repository was quick to implement using known technologies, but  Limited model  Metadata-centric orientation  No content – only metadata  Limited relationships – collection/item  Limits on context, structure, and access  Severe limits on contribution and collaboration  One-way data flow: NSDL → Users

8. Photo by Jon Crispin

9. NSDL 2.0  Create an NSDL that guides not just resource discovery, but:  Supports creating “context” for resources  Presents resources in context: linked to related concepts; with user ratings; with codes and data  Enables community tools for selecting, organizing, evaluating, annotating, contributing, and collaborating  Provides two-way data flow: NSDL ↔ users  Goal: Create a dynamic, living library

10. In Architectural terms, create an NSDL Data Repository that  Supports storing both content and metadata  Allows arbitrary relationships among resource and metadata objects: organization, annotation, citation  Accessible through web service architecture of remixable data sources and transformations

11. The Fedora Vision: A Repository for Rich Information Networks

12. Fedora: the NDR middleware  A Flexible, Extensible Digital Object Repository Architecture (http://www.fedora.info)  Open source project with $2.2 million in Mellon funding 2002-2007  Collaboration of Cornell and Univ. of Virginia  Key funded users include:  eSciDoc project (collaboration of the Max Planck Society and FIZ Karlsruhe)  Public Library of Science (Topaz Foundation)  VTLS Corp., Harris Corp., Library of Congress  Australian Research Repositories Online to the World  Royal Library Denmark, National Library, and DTU

13. What is Fedora?  An architecture, toolkit, and implementation: middleware, not a vertical application  Stores arbitrary internal and external digital objects, disseminations (transformations and combinations), relationships among objects  Entirely SOAP/REST based, disseminations are URLs  XML data store; RDBMS cache; RDF triplestore supports relationship queries

14. NSDL Data Repository (NDR)  References to roughly 2 million selected STEM resources on the web  Sourced metadata statements about those resources  A REST API to allow authenticated access by Pathways and providers  Support for annotation, aggregation, and other relationships

15. Sample NDR Objects & Relationships Publication Resource Data Set Metadata Publication Metadata Data Set Resource Code Resource Cites Metadata for Member of Metadata Provider MatForge Collection Soft Matter Collection Member of Cites Metadata for Cornell CCMR MatDL Pathway Selector for Selector for

16. Draft NDR API Characteristics  Uses REST calls for all interactions; uses handles (DOIs) for all external references  Ensures external applications can’t violate the NDR model constraints  Disseminations allow combining metadata from multiple sources, or related content  Authentication: Requests signed with private key associated with an agent  Authorization: Agent can become a metadata provider or aggregator; can create resources

17. An Information Network Overlay  Think of the NDR as a lens for viewing science content on the net  Content can be:  Local: stored directly in the NDR  Remote: accessed through a URL  Computed: derived from a database or web service  Archived: an older version stored at SDSC  It all has a repository-based URL

18. Network Overlay View User View API/UI Repository View with Relations & Annotations Resources on the Web

19. NSDL 2.0 Technical Challenges  Scaling the RDF triple-store past 200 million triples  Constraining RDF queries to be reasonably computable  Building meaningful search indices on explicit metadata, annotations, resource content, and relationships

20. Applying the NDR  The NDR provides powerful capabilities for:  Creating context around resources  Enabling the NSDL community to directly contribute resources and context  Representing a web of relationships among science resources and information about those resources  How do we use it? Here’s one specific example …

21. ExpertVoices

22. What is Expert Voices?  A multi-user blogging tool  Topic-based discussions (e.g. forensics) with pointers to related resources  An outreach tool to explain and document NSF-funded research  A way for NSDL community members to become NSDL contributors: of resources, questions, reviews, annotations, metadata  A question/answer and discussion forum: scientist ↔ teacher ↔ student ↔ librarian

23. What isn’t EV?  Expert Voices ≠ LiveJournal  Contributors are carefully selected, contributions are about science, the process of science, and education Comic by Michael Lalonde/orneryboy.com

24. Hurricane Floyd/Photo by NASA

25. Photo by Jon Crispin

26. Broadening Participation: An Expert Voices Learning Scenario  “Hurricane Season Blog” run by a National Weather Service hurricane expert, an Earth Science teacher, and a school media specialist familiar with NSDL  Expert creates an entry for Hurricane Gertrude  “On track to hit Ft. Lauderdale in 72 hours”  “Currently undergoing eyewall replacement cycle”  “Expecting 15 foot storm surge”  Media specialist adds links to NSDL resources: Hurricane Hunters site, latest satellite photos, and USGS flooding and flood plain web page  Teacher makes connections to relevant standards and appropriate pedagogy for use by other teachers  Students experience engaging real-time, real-world applications of science lessons

27. Expert Voices Implementation  Open source multi-user blogging system  Published entries become NSDL resources  Owner controls publication of entries and visibility of comments  Entries can contain linked references to NSDL resources, references to URLs that should become resources, and new resource metadata  Integrated with NSDL Shibboleth-based community sign-on

30. But Expert Voices is just the beginning…

31. Soft Matter Wiki: Planned NDR Integration  Community of approved contributors (e.g. teachers, librarians, materials scientists) are granted edit access to Soft Matter wiki  New resources and metadata are created as wiki pages and reflected into the NDR  Relevant non-wiki-based NDR resources and metadata are displayed as read-only wiki pages, subject to comment and linking  User and project pages organize NDR resources

33. NDR Entry for Soft Matter Wiki Wiki Entry New Metadata New Audience MD Referenced New Resource 1 Referenced Existing Resource 2 Annotates Metadata for Member of Metadata Provider Metadata Provider Existing Collection Soft Matter Wiki Member of Inferred relationship between resources

34. MyNSDL: NDR-integrated tagging, bookmarking, and recommendation  Based on Connotea open-source folksonomic tagging/bookmarking system  Tags and bookmarking structure are reflected back into the NDR  Authorized users can “automatically” recommend new NSDL resources simply by tagging them  Gives user a personal view of NSDL resources

36. NDR Application: Content Assignment Tool  Developed by Anne Diekema, Elizabeth Liddy, et al. at the Syracuse University Center for Natural Language Processing  Uses text analysis and machine learning to suggest Educational Standards alignment for resources  Content expert assigns standard, and system learns from the assignment  Standalone tool available now; standards associated with resources in the NDR 4Q06

38. Other applications in development  Automated grade-level assignment based on vocabulary analysis (San Diego Supercomputer Center)  OnRamp – multi-user, multi-project NDR- integrated content management system  Instructional Architect: Lesson plan development for K12 teachers (Utah State)  iVia-based Expert-Guided crawl: Tool for Pathways and others to turn websites into resource collections (in development at UC Riverside)

39. Other proposed applications  Moodle Course Management System – courses integrated with NSDL resources  Electronic lab notebook – integrating lab notes with code, data sets, and reference materials within the library archival framework

40. … NSDL 2.0 Ecosystem Protocol: OAI-PMH HTTP REST NDR API STEM Collections Search Service Archive Service Fedora- based NDR

41. What are the Information Science challenges?

42. Trust Photo © 2005 Reuters

43. Contribution

44. Trust and reputation in NSDL  We brand NSDL as a source of “trusted” resources  What is our trust mechanism?  Transitive trust approval  Community rating/filtering/reputation  Trusted vs. complete “views”  What is the right balance of trust vs. community contribution?

45. Community Formation  Build the tools and they will come?  What can we learn from Wikipedia, MySpace, Flickr, and YouTube?  How do we leverage existing societies and groupings (NSTA, ACM, AAPT, AAAS)?  Is there an NSDL community, or are there many small communities?

46. Courtesy Kathy Sierra/WickedlySmart.com

47. Creating Passionate Users  How do we help NSDL users “kick ass”?  What can we learn from game design?  Motivating goal  Challenging interaction  Meaningful payoff  Multiple levels  Can we use fun, emotion, seduction, surprise, and visuals – and still be academics?

48. Courtesy Kathy Sierra/WickedlySmart.com

49. Photo by Jon Crispin

50. Challenges of ubiquity  Should we target NSDL materials at limited devices (iPods, cell phones)?  How does ubiquitous NSDL access change teacher/student interactions?  Should we build tools to capture field data from these devices?

51. Other IS Challenges  Personalization: SDI, automated activity analysis, targeted user views  Visualizing the library: alternatives to text search for discovery and context  Location awareness: specializing library views by physical location

52. Summary  NSDL 2.0 and its tools allow scientists, mathematicians, teachers, engineers, librarians, and students to create a unique web of context, contribution, and collaboration around the high-quality STEM education resources at the core of the NSDL.  NSDL CI needs solve the IS problems needed to turn Capability into Reality.

53. Acknowledgements  NSDL NSF Program Officers  Lee Zia  David McArthur  NSDL Core Integration Team  UCAR: Kaye Howe, PI and Executive Director  Cornell: Dean Krafft, PI  Columbia: Kate Wittenberg, PI  Fedora Development Team  Cornell: Sandy Payette & Carl Lagoze  Univ. of Virginia: Thornton Staples

54. Apology Courtesy Kathy Sierra/WickedlySmart.com

55. Questions?

56. Contact Information Dean B. Krafft Cornell Information Science 301 College Ave. Ithaca, NY 14850 USA dean@cs.cornell.edu This work is licensed under the Creative Commons Attribution-NoDerivs 2.5 License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nd/2.5/ or send a letter to Creative Commons, 543 Howard Street, 5th Floor, San Francisco, California, 94105, USA.http://creativecommons.org/licenses/by-nd/2.5/