Making Research "Social" using LDAP

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Making Research "Social" using LDAP

  1. 1. Making research « social » with LDAP Stephan Fabel Logo
  2. 2. Aloha :-) 2 Logo
  3. 3. Situation  University of Hawaii System: – 10 campuses  UH Manoa campus 20,000 students  Budget cuts across the entire UH System  UHM alone >$24M in 2013   Budget 2014 for the first time 51% based on student tuition 2014 Budget for Colleges « data informed » 3 Logo
  4. 4. Challenge for our College How do we capture key performance metrics for faculty and staff to support our case? 4 Logo
  5. 5. COE and Symas OpenLDAP (1)   Symas OpenLDAP crucial to College infrastructure services Pre-2011: – user accounts (College-specific) – groups (College-specific)  2011-2012: – pass-through authentication to central IT – groups (POSIX and groupOfNames) local – authentication and groups in every application rolled out at the College 5 Logo
  6. 6. COE and Symas OpenLDAP (2)  2013: – Publications (100%) – Grants (specification done) – Service (currently being specified)  No teaching activity stored in our directory – data available through Banner (Oracle) – but it's on the list  We run our own Student Information System which helps 6 Logo
  7. 7. Capturing Research    « pet project » originally aimed at marketing efforts through public website idea was to present college research to interested third parties – Legislature – General public – Prospective students – Other researchers 7 Logo
  8. 8. Public Website (1) 8 Logo
  9. 9. Public Website (2) 9 Logo
  10. 10. Aloha :-) 10 Logo
  11. 11. Schema 11 Logo
  12. 12. publications.schema ?  Dublin Core Schema: http://tools.ietf.org/html/draft-hamilton-dcxl-02  We implemented it  We didn't like it: – Distinction between authors, contributors, editors not clear enough – Everything a DirectoryString – Goal was to be able to generate APA-style citations: not possible using Dublin Core 12 Logo
  13. 13. publications.schema (1)  26 attributes capturing: – Title Information, Author(s), Abstract, Type, Publisher, Volume, Pages, Owner, Venue, Location, Organization, Editor, Series, Edition, Chapter Information, Thumbnail, PDF, Month and Year – Keywords, Flag for outstanding research  8 object classes (pubObject) – Conference Proceedings, Journal Article, Book, Book Chapter, Presentation, Research Report and Multimedia Contribution 13 Logo
  14. 14. publications.schema (2)   classes are auxiliary meant to be used in conjunction with the document structural object class – documentIdentifier – documentAuthor – documentLocation  For the most part, tried to keep logical attributes away from pubObject – with few exceptions 14 Logo
  15. 15. Determining Author- and Ownership pubObject documentAuthor : uid=firstAuthor documentAuthor : uid=secondAuthor cn : [uidNumberFirstAuthor]XXX pubOwner : uid=firstAuthor Goal : - determine authorization to edit - only first author gets rw, all others only get r - thankfully first author never changes XXX is incrementing number Yes It's redunant :-/ Show all work from uid=sfabel : (pubOwner=uid=sfabel) Show all work where uid=sfabel was involved : (documentAuthor=uid=sfabel) Logo
  16. 16. Document Identifier   cn locally unique documentIdentifier supposed to be globally unique – DOI - http://dx.doi.org/ – ISBN - http://books.google.com/   We don't want to save the publications themselves (copyright issues) We link them based on DOI through our library → paywall if not part of our system, otherwise direct access Logo
  17. 17. Lessons learned / Still todo   Capture organizations as DN How to organize this in hierarchical fashion across multiple, distributed servers – Change – Federated access  Other things we're not aware of 17 Logo
  18. 18. Aloha :-) 18 Logo
  19. 19. Reporting API 19 Logo
  20. 20. Reporting API  Written in PHP  ReST based queries (HTTP)  Binds to LDAP server and executes search  Returns data in – XML, JSON, PDF, CSV – Net file  Currently no authentication layer – Looking at possibly using OAuth 2.0 20 Logo
  21. 21. Publications by Person (1) 21 Logo
  22. 22. Publications by Person (2) 22 Logo
  23. 23. Publications by Person (3) 23 Logo
  24. 24. By Person → By Department  Using groupOfNames  Using slapo-memberof(5)   First Author is member of department → publications can be aggregated Relationship is dynamic (author moves to different department, so do his/her publications) 24 Logo
  25. 25. Publications by Department (1) 25 Logo
  26. 26. Publications by Department (2) 26 Logo
  27. 27. Publications by Department (3) 27 Logo
  28. 28. Publications by Department (4) Bonus ! 28 Logo
  29. 29. Expert Search  Goal is to find the person with the highest caliber in publications around a given topic  Based on pubKeyword attribute values  Output is people (not publications!)  Ranking is performed by – Publication count, type, # of collaborators – Whether person was first author or not 29 Logo
  30. 30. Keyword Search (1) 30 Logo
  31. 31. Keyword Search (2) Person claims « autism » as area of interest, which guarantees being listed, but we have no publications in our system to indicate any value of his contribution. 31 Logo
  32. 32. Aloha :-) 32 Logo
  33. 33. So, how is it « social »? 33 Logo
  34. 34. What is « social » ?  Social media: – share information with networks of people – interaction based on that shared information – goal: create « virtual community » 34 Logo
  35. 35. What makes research « social » ?  Social research: – topically bounded interaction based on shared information – networks emerge through work – communities « pre-defined »: • • • • fellow researchers prospective students public/legislature administration 35 Logo
  36. 36. Collaboration ↔ Interaction  Collaboration Report: – Find author pairs, calculate their “weight” – Create score based on these weights   Total relevance score average of all co-authors importance Scoped by keyword or global 36 Logo
  37. 37. Collaboration Report (1) 37 Logo
  38. 38. Collaboration Report (2) 38 Logo
  39. 39. Collaboration Networks   Combination of expert and collaboration search Undirected graph: – Nodes people, size indicating weight – Vertices collaborative relationship, size indicating strength of collaborative efforts (number of publications, kinds of publications, number of other collaborators, etc.) 39 Logo
  40. 40. Collaborative Network (example) 40 Logo
  41. 41. Outlook / Future Work     Comprehensive Dashboard in planning Additional institutional research / business intelligence based on further analysis of collaboration networks Web-enabled search interfaces available to public Q1 2014 Internal reporting to be made available to all colleges, aggregation of LDAP servers to provide campus-level reporting 41 Logo
  42. 42. Outlook / Future Work  Organizations: – Common thread between publications, grants, awards and service data – Will be central in future reporting  Portal for researchers: – Finding other people that you haven't collaborated with – Leveraging success of grant applications through collaboration – Providing orientation for new hires 42 Logo
  43. 43. Aloha :-) 43 Logo
  44. 44. Thanks! Logo

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