New Research Tools from JSTOR Labs
•Download as PPTX, PDF•
1 like•297 views
This document summarizes new research tools from JSTOR Labs including the JSTOR Understanding Series, Understanding Shakespeare project, and plans for future projects. The Understanding Series allows users to see all articles and chapters quoting a selected text passage. The Understanding Shakespeare project tested using a primary text as a portal for secondary scholarship. Future plans include adding more texts to the Understanding Series, incorporating copyrighted works, and expanding the Interview Archive project to make more documentary interviews accessible for education.
Recommended
More Related Content
Similar to New Research Tools from JSTOR Labs
Similar to New Research Tools from JSTOR Labs (20)
Recently uploaded
Recently uploaded (20)
New Research Tools from JSTOR Labs
- 1. New Research Tools from JSTOR Labs Jessica Keup jessica.keup@ithaka.org
- 2. 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.
- 3. THE JSTOR UNDERSTANDING SERIES November 2018 www.jstor.org/understand Pick a text and pick a passage. Instantly see all the articles and chapters in JSTOR quoting that passage. With an ever- expanding roster of primary texts, the JSTOR Understanding Series is a powerful new way to research cultural and historical texts.
- 4. UNDERSTANDING SHAKESPEARE • An early Labs project to test the hypothesis/value of using a primary text as a portal into secondary scholarship • A collaborative effort with the Folger Shakespeare Library • Launched in Fall 2014 and saw steady usage until it was decommissioned in 2019
- 5. MORE DISCOVERY AND PROTOTYPING • Understanding the U.S. Constitution IOS/Android mobile app • Poetry Annotations collaboration with Hypothes.is, the Poetry Foundation, and UT Austin • Experiments with other works, including Aeneid, Divine Comedy, Walden, Middlemarch, King James Bible, etc.
- 8. These matches are identified via fuzzy-text matching. We’ve created a “Quotations Database” of approx. 340 million quotations in JSTOR articles and chapters. These links stored as W3C- compliant annotations.
- 9. WHAT’S NEXT FOR THE JSTOR UNDERSTANDING SERIES? • Intern just started – adding more texts • We’ve heard concern about diversity of texts and canon reinforcement • Proxy capabilities to get works in copyright • Adding features (article length and reading level filters are highly requested)
- 10. INTERVIEW ARCHIVE June 2019 labs.jstor.org/interview Documentarians are only often able to use only a small percentage of the interviews they capture. In this collaboration with Kunhardt Film Foundation, we will explore making full video interviews with historically significant figures made available for educational purposes.
- 11. BACKGROUND Kunhardt Film Foundation’s King in the Wilderness documentary • Partnered with us to make sure the excess interview footage of those who watched – and made - civil rights history were accessible and appreciated • We saw a need to avoid video as ”informational cul-de-sac” and instead make video an interconnected step in students’ research journeys
- 15. WHAT’S NEXT FOR THE INTERVIEW ARCHIVE? • Test the adoption in classroom settings • Seek partnerships from other documentary makers or oral history collectors • Based on how those go, potentially add additional documentary interviews or oral histories
- 16. Thank you Jessica Keup User Experience Prototyper, JSTOR Labs ITHAKA https://labs.jstor.org @jaithica jessica.keup@ithaka.org
Editor's Notes
- “What about Moby Dick, Walden, Middlemarch, [pick your favorite work]?” Can this be done for that? But it only links to JSTOR articles… It would be more useful if other content could be linked. It would be great if there was an open API for querying the match data. Combining this with other tools (such as a general purpose annotation tool) would improve its utility for teaching and learning It doesn’t work so hot on mobile devices. The match data is still pretty noisy. Improving the algorithms and providing a way to leverage community expertise in validating/correcting will be important as we move from a proof of concept