1. What We Learned From Related Projects Research-oriented Social Environment (RoSE)

2. Core Reports

3. Other Relevant Reports

4. Provide research context View how related projects treat similar concerns Analyze related projects to improve RoSE’s processes Provide research context View how related projects treat similar concerns Analyze related projects to improve RoSE’s processes Research Goals

5. Academia.edu

7. Academia.edu search by field: returns people, not documents

8. Academia.edu search: “thesis”

9. Social Book Cataloging Goodreads Visual Bookshelf LibraryThing weRead Goodreads Visual Bookshelf LibraryThing weRead

10. Social Book Cataloging Humanizing the Database Database an index of the self Cataloging no longer defines a collection, but experiences Humanizing the Database Database an index of the self Cataloging no longer defines a collection, but experiences

11. Goodreads

12. Freebase Databasing the human Reduction of online identity to statistics Users converted into data, exist in the service of data social network only in place to add to the database socially constituted only insofar as one is statistically constituted Databasing the human Reduction of online identity to statistics Users converted into data, exist in the service of data social network only in place to add to the database socially constituted only insofar as one is statistically constituted

13. Freebase - “facts,” “My topic”

14. Statistical Alternatives The “Metadata Offer New Knowledge” (MONK) Project ConceptNet The “Metadata Offer New Knowledge” (MONK) Project ConceptNet

15. The MONK Project Largest Collections Within MONK: The Text Creation Partnership (TCP) The Chadwyck-Healey 18th Century Fiction Collection The Chadwyck-Healey 19th Century Fiction Collection The Chadwyck-Healey Early American Fiction Archive The Wright American Fiction Archive Largest Collections Within MONK: The Text Creation Partnership (TCP) The Chadwyck-Healey 18th Century Fiction Collection The Chadwyck-Healey 19th Century Fiction Collection The Chadwyck-Healey Early American Fiction Archive The Wright American Fiction Archive

16. The MONK Project Tagging Collocation N-grams Tagging Collocation N-grams

17. ConceptNet Natural Language Processing Tool Emphasizes Context Parses sentences into nodes and relations Natural Language Processing Tool Emphasizes Context Parses sentences into nodes and relations

18. CommentPress

19. Zotero Collections Tags

20. Database and narrative are NOT natural enemies Database requires “curation” and the construction of “collections” Otherwise, database would be an “insane” collection in the same vein as those collections created by misers and hoarders (Susan Stewart, On Longing) Database and narrative are NOT natural enemies Database requires “curation” and the construction of “collections” Otherwise, database would be an “insane” collection in the same vein as those collections created by misers and hoarders (Susan Stewart, On Longing)

21. A Comparison of Development Platforms for Social Network Data Visualizations Salman Bakht notes that Flash “uses animation and video editing metaphors.” How are we metaphorically engaged in our task? That is, what is the language we use to describe our efforts and what are the implications of that language? What metaphors should we avoid? Which ones should we employ? Salman Bakht notes that Flash “uses animation and video editing metaphors.” How are we metaphorically engaged in our task? That is, what is the language we use to describe our efforts and what are the implications of that language? What metaphors should we avoid? Which ones should we employ?

22. Document Database Integration for RoSE RoSE database will incorporate other databases: English Broadside Ballad Archive (EBBA) Early English Books Online (EEBO) Early English Books Online - Text Creation Partnership (EEBO-TCP) The Renaissance English Knowledgebase (REKn) The Iter Bibliography RoSE database will incorporate other databases: English Broadside Ballad Archive (EBBA) Early English Books Online (EEBO) Early English Books Online - Text Creation Partnership (EEBO-TCP) The Renaissance English Knowledgebase (REKn) The Iter Bibliography

23. Open Journal Systems Reading Tools

24. Open Journal Systems Emphasis on roles and levels of access - which types of filtering should be available, if any? However - what do we do in terms of documents and dead people? Equally open access? What does it mean that certain people can restrict access to their information while others (the dead, various documents) can’t? Emphasis on roles and levels of access - which types of filtering should be available, if any? However - what do we do in terms of documents and dead people? Equally open access? What does it mean that certain people can restrict access to their information while others (the dead, various documents) can’t?

25. Collex NINES The Ambrose Bierce Project British Women Romantic Poets, 1789-1832 The Charles Chesnutt Digital Archive The Poetess Archive The Romantic Circles Praxis Series The Rosetti Archive The Swinburne Project Victorian Studies Bibliography Whitman Bibliography NINES The Ambrose Bierce Project British Women Romantic Poets, 1789-1832 The Charles Chesnutt Digital Archive The Poetess Archive The Romantic Circles Praxis Series The Rosetti Archive The Swinburne Project Victorian Studies Bibliography Whitman Bibliography

26. Lessons for RoSE Articulate the relationships between documents and people - are they equal? Is one type of relationship more important than another? Define the relationship of people to data - do people exist to add to the database or does the database exist to add to people (experiences, etc.) “Adding” to people - folksonomic approach (no limitation to information that can be added) Articulate the relationships between documents and people - are they equal? Is one type of relationship more important than another? Define the relationship of people to data - do people exist to add to the database or does the database exist to add to people (experiences, etc.) “Adding” to people - folksonomic approach (no limitation to information that can be added)

27. Lessons continued... How does RoSE construct identity? Will people become “standardized” presences? If so, what is the emphasis - research interests, publications, friends? Which kinds of data are searchable? Notes? Tags? Profiles? What are the underlying biases of RoSE? How does RoSE construct identity? Will people become “standardized” presences? If so, what is the emphasis - research interests, publications, friends? Which kinds of data are searchable? Notes? Tags? Profiles? What are the underlying biases of RoSE?