understanding shakespeare: what we've learned (so far) - rsa 2016
TRANSCRIPT
UNDERSTANDING SHAKESPEARE:WHAT WE’VE LEARNED(SO FAR)
1 April, 2016
Alex Humphreys, JSTOR Labs@abhumphreys
RSA 2016 Panel: Folger Digital Agendas II – Scholarly Conversations and Collaborations
JSTOR is a not-for-profit digital library of academic journals, books, and primary sources.
Ithaka S+R is a not-for-profit research and consulting service that helps academic, cultural, and publishing communities thrive in the digital environment.
Portico is a not-for-profit preservation service for digital publications, including electronic journals, books, and historical collections.
ITHAKA is a not-for-profit organization that helps the academic community use digital technologies to preserve the
scholarly record and to advance research and teaching in sustainable ways.
JSTOR Labs works with partner publishers, libraries and labs to create tools for researchers, teachers and students that are immediately useful – and a little bit magical.
PARTNERSHIP WITH FOLGER
• Open, collaborative partnership with Folger Shakespeare Library
• They had:- Shakespeare Quarterly- Folger Digital Texts- Scholars and students
• We had:- Full run of SQ- 2,000 more journals- A new Labs team
• Flash Build - September, 2014: - From ideation to working site- One week at the Folger in DC
labs.jstor.org/shakespeare
Understanding Shakespeare…
“...is the most exciting project in digital Shakespeare in many years, and takes a major step forward in creating a ‘living variorum’ for Shakespeare studies on the web.”
-Peter DonaldsonFord International Professor in the Humanities,
MIT
MATCHMAKERALGORITHM
1. Identify candidate set of articles from JSTOR
2. Extract quotations - quotations, not allusions - text within quotes or block-quotes
3. Run fuzzy text matching of quotations against primary text
4. Calibrate to minimize false positives and negatives - quotation length - % confidence
Usage vs. Scholarship
100% = 26,233
100% = 441,032
OPEN & PUBLIC API
labs.jstor.org/developers
Play Data(from Folger Digital
Text)
genre, play, act, scene, line, speaker, speaker_gender, on_stage
Scholarship Data(from articles on
JSTOR)
title, authors, journal, pubdate, article_type, keyterms
Quotations!play_text, match_text, similarity, match_size
WHERE DO WE GO FROM HERE?
• Apply Matchmaker to other texts - Understanding the US Constitution App - Understanding Dante - and more!
• Matchmaker API- Run Matchmaker on any text you can upload or point to - Incorporate Matchmaker links into other sites - Apply Matchmaker to other corpora
• What do you suggest?
APPENDIX(OPEN IN CASE OF NO INTERNET CONNECTION)
