UC Multi-Campus Research Group (MRG)

1. Transliteracies ProjectResearch in the Technological, Social, and Cultural Practices of Online Reading UC Multi-Campus Research Group (MRG) • Seed grant ($350,000 from UC Office of the President and UCSB) • 2005-2010 • Faculty and graduate students from 7 UC campuses (in humanities, media arts, social sciences, computer science)

2. » Launch UCSB Conversation Roundtables on Online Reading, June 2005 Sue Thomas’s report on the conference: www.english.heacademy.ac.uk/explore/publications/newsletters/newsissue9/thomas.htm

3. » Discovery • ResearchClearinghouse • “Objects for Study” • Research Reports • Research Papers

4. » Analysis • History of Reading Group (HORG) • Directors: 2006-2008, William Warner (English, UCSB); 2008-2009, James Kearney (English, UCSB)

5. » Analysis • New Reading Interfaces Group • Director: Rita Raley (English, UCSB) • Examples of research directions Warren Sack’s Agnostics Bradford Paley’s Textarc

6. » Analysis • Social Computing Group • Co-leaders: • Kevin Almeroth (CS, UCSB) • Jennifer Earl (Sociology, UCSB) • Andrew Flanagin (Comm, UCSB) • James Frew (Bren School, UCSB) • Alan Liu (English, UCSB) • Miriam Metzger (Comm, UCSB) • Graduate-student “Bluesky” group NSF IGERT Pre-proposal for social-computing research/curricular program

7. » Direction From Reading to Social Computing

8. RoSEResearch-oriented Social Environment An experimental project by Transliteracies beta site: spectrum.mat.ucsb.edu:3000 about:transliteracies.english.ucsb.edu/category/researchproject/rose

9. RoSE Developer Team (current Transliteracies “Bluesky” group) Transliteracies Project CoordinatorsAnne Cong-Huyen, English, UCSB Chris Hagenah, English, UCSB Lindsay Thomas, English, UCSB (Former coordinators: Lisa Swanstrom, Comp. Lit., UCSB Kimberly Knight, English, UCSB) Programmer GroupIvanaAndjelkovic, Media Arts & Technology, UCSB Salman Bakht, Media Arts & Technology, UCSB Rama Hoetzlein, Media Arts & Technology, UCSB Pehr Hovey, Media Arts & Technology, UCSB Aaron McLeran, Media Arts & Technology, UCSB Visualization GroupIvanaAndjelkovic, Media Arts & Technology, UCSB Salman Bakht, Media Arts & Technology, UCSB Rama Hoetzlein, Media Arts & Technology, UCSB Lilly Nguyen, Information Studies, UCLA Metadata GroupDir: David Kim, Information Studies, UCLA Charlotte Becker, English, UCSB Eric Chuk, Information Studies, UCLA Rama Hoetzlein, Media Arts & Technology, UCSB Early Modern Data GroupDir:Jeremy Snow, History, UCSC Charlotte Becker, English, UCSB Eric Nebeker, English, UCSB 19th-20th Century Data GroupDir:Chris Hagenah, English, UCSB David Kim, Information Studies, UCLA Julia Panko, English, UCSB Greg Pollock, Literature, UCSC Arden Stern, Visual Studies, UCI Contemporary Data GroupDir:Lindsay Thomas, English, UCSB Eric Chuk, Information Studies, UCLA Anne Cong-Huyen, English, UCSB Renee Hudson, English, UCLA Research Reports GroupDir:Renee Hudson, English, UCLA Former dir:Salman Bakht, Media Arts & Technology, UCSB [Many others contributed Transliteracies research reports]

10. RoSE Design Charrette (February 26, 2010)

11. RoSE is being developed at a seed-funding level as a working platform stocked with a representative set of data/metadata and a sample set of interfaces, data visualizations, and other end-user experiences. • It is a conceptual demo -- robust enough to suggest what is possible, but still malleable enough to be open to critique and revision.  • It is a hands-on platform for thinking about some of the combined philosophical and technical issues that would need to be confronted if RoSE were to be implemented as a production-scale system. • These issues include (the topics of breakout sessions at the RoSE design charrette on Feb. 26th, 2010): • Expertise and networked public knowledge • Data-mining and visualization of social networks • Information credibility • Fluid ontologies and metadata for social and historical research • Online reading and research environments. RoSEResearch-oriented Social Environment

12. RoSE creates a convergence between • and • knowledge RoSEResearch-oriented Social Environment document-centric socially-networked

13. Document-centric Approach Journal published through Open Journal Systems (OJS) http://pkp.sfu.ca/?q=ojs

14. Document-centric Approach Collex (Collection View) http://nines.org/

15. Document-centric Approach U. Victoria PReE (and REKn) Project (functional demo), Ray Siemens et al. (Electronic Textual Cultures Lab)

16. Document-centric Approach CommentPress pre-print publication of Noah Wardrip-Fruin’sExpressive Processing on Grand Text Auto in 2008 http://grandtextauto.org/2008/01/22/expressive-processing-an-experiment-in-blog-based-peer-review/

17. Document-centric Approach WorldCat Identities http://www.worldcat.org/identities/

18. Document-centric Approach “On the Margins of Scholarship: Repositories, Web 2.0 and Some Scholarly Precedents” Richard M. Davis, U. London Computer Centre http://pubs.or08.ecs.soton.ac.uk/2/2/OR08_Presentation_Richard_Davis.pdf

19. Social Network Approach Academia.edu http://www.academia.edu/

20. Social Network Approach LibraryThing Visual Bookshelf in Facebook See Transliteracies Research Paper: “Social Book Cataloging: Humanizing Databases” by Renee Hudson and Kimberly Knight

21. Document-centric Approach Social Network Approach + ConceptVista www.geovista.psu.edu/ConceptVISTA Mark Gahegan, et al., "Connecting GEON: Making Sense of the Myriad Resources, Researchers and Concepts that Comprise a Geoscience Cyberinfrastructure," Computers and Geosciences 35 (2009): 836-54

22. RoSE's Premise »People seeking knowledge do not necessarily want to go to either a document (a "document-centric" approach) or a person (a "social- network" approach) as their first point of access--though they will take either. »More ideal is an online environment that allows users to seek out documents and people in the context of relationships between the two (e.g., of authorship, reception, affiliation, recommendation, sponsorship, commentary, rebuttal, etc.). »In such an online environment, there would be no documents sitting in virtual “libraries” as opposed to people joining “communities.” Instead, documents, authors, editors, publishers, readers, annotators, etc. will be interlinked in combined orbits of knowledge—i.e., an integrated “social-document graph.”

23. Unique Features of RoSE »RoSE allows for fine-grained relationship types. Not every person or every document is just a "friend.” »RoSE's social network includes historical or "dead" people, who have their own profile pages. After all, the nature of true research is that it does not respect a natural divide between the living and the dead. Its "longitudinal" horizon is much more extensive. »In RoSE, some documents will have profile pages. »Though not possible without implementation-scale funding (or partnering with other projects), RoSE envisions using data-mining to simulate agency on the profile pages and "walls" of historical people (and influential documents). »Imagine, for instance, that Shakespeare's page could be refreshed with content drawn from his writings or those of his followers, scholars, etc., in response to breaking new research or recent news events. »Or imagine that the U.S. Constitution had its own profile page and wall, so that the latest Supreme Court decision could trigger on the Constitution’s page--through data-mining and algorithmic processes that summon up utterances by the Founding Fathers or past “learned commentators”—the Constitution’s own opinion about that decision.

24. Fine-grained Relationships

25. Historical People

26. Document Profile Pages

27. Visualization Possibilities

28. Future Challenges • Input • Partnering with full-text repositories • Algorithmic harvesting • “Expert” vs “folksonomic” input • Ontologies • Scale “Knowledge” • Output • Visualizations (informational & “poetic”) • Metadata “Narrative” • Exposure of XML, RDF datapaths for third party data-analytics and visualization • Metrics • Annotation and Authoring

29. RoSEResearch-oriented Social Environment »You want to know something. You look in RoSE to spot a cluster of evolving relationships (whether of authorship, trust, influence, controversy, etc.) between the people and the documents that seems to have defined the current knowledge-scape on that topic. So you go there--to that hive of knowledge relationships--to learn. »If you want, you can move the time slider back and forward to see how the relationships looked then and now. »Then it comes clear: what you know and still do not know, and who or what next to research, to read.