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Data visualization and digital humanities research:  a survey of available data sets and tools

Data visualization and digital humanities research:  a survey of available data sets and tools . LITA National Forum 2011 St. Louis, MO Friday, September 30, 2011 Erik Mitchell, University of Maryland Susan Sharpless Smith, Wake Forest University. Motivation.

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Data visualization and digital humanities research:  a survey of available data sets and tools

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  1. Data visualization and digital humanities research:  a survey of available data sets and tools LITA National Forum 2011 St. Louis, MO Friday, September 30, 2011 Erik Mitchell, University of Maryland Susan Sharpless Smith, Wake Forest University

  2. Motivation “Digital humanities needs gateway drugs. Kudos to the pushers on the Google Books team.” - Dan Cohen http://www.dancohen.org/2010/12/19/ “Linked open data could have the same leveraging effect that the World Wide Web had on computing, said Micki McGee, an assistant professor of sociology at Fordham University” -Steve Kolowich, The Promise of Digital Humanities, Inside HigherEd

  3. Birth of a word “Imagine if you could record your life, everything you said, everything you did available in a perfect memory store at your finger tips. “ - Deb Roy – The Birth of a Word http://www.ted.com/

  4. Overview • Discuss examples of data-focused research tools • Explore tools • Consider roles for librarians • Wrap-up/Q & A

  5. Taxonomy of uses

  6. Searching and Discovery Examples: BYU Corpuahttp://corpus.byu.edu/ WOK Citation Mapping WOK

  7. Visualization Free Visualization Tools

  8. Analysis and publishing NodeXLhttp://nodexl.codeplex.com/

  9. Tool Comparison - linguistics

  10. Tool exploration • Discover / Search • What kinds of discovery tools exist and how common are the discovery features across different datasets / systems? • Visualization • What visualization features exist, are there products that are easy to use, are the skills transferable? • Analysis / Annotation • What analytical tools are included, what analysis techniques are common?

  11. Perseus http://www.perseus.tufts.edu

  12. JSTOR Data For Research http://dfr.jstor.org

  13. Wordseer AditiMuralidharan Marti Hearst http://bebop.berkeley.edu/wordseer

  14. Google’s Ngram Viewerbooks.google.com/ngramsculturomics.org But here's the rub. Google Books, as others point out, wasn't really built for research. . . That means Google Books didn't come with the interfaces scholars need for vast data manipulation . . . http://chronicle.com/article/The-Humanities-Go-Google/65713/

  15. Ted talk on Google NGRAM viewer http://www.ted.com/talks/what_we_learned_from_5_million_books.html

  16. Concordancing Eric Lease Morgan - http://dh.crc.nd.edu/sandbox/cyl/catalog/

  17. Google’s public data explorer http://www.google.com/publicdata/

  18. Data analysis - NodeXL http://nodexl.codeplex.com/ Analyzing Social Media Networks with NodeXL: Insights from a Connected World

  19. Data cleaning – Google Refine http://code.google.com/p/google-refine

  20. Data visualization – Google Fusion Tables http://google.com/fusiontables http://www.google.com/fusiontables/DataSource?dsrcid=332788

  21. Research/teaching need • Researcher needs vary from advanced linguistic analysis and IT support to need for basic digital content/infrastructure Corpus-based research

  22. Librarian contributions • Domain specific, tool-type specific comparisons • IT and research support – data analysis, data curation, tool/data sources identification • Shift from “reference” to “research” in sync with move from resource discovery to thematic analysis

  23. Next steps • Build new skills, develop new systems • Create tutorials guides • Explore connections between data/curation and publishing and these tools – so is there a connection • Explore role of library discovery systems and consider new feature implementation.

  24. Sites of interest

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