Digging into Data Challenge Award Winners Announced

Fri, 2009-12-11 13:21 -- Anonymous (not verified)

By Brett Bobley, Chief Information Officer, Director, Office of Digital Humanities (http://www.neh.gov/ODH/) National Endowment for the Humanities
Washington, DC Research into the unique characteristics and issues around stewardship of large amounts of humanities data was recently highlighted at an awards ceremony honoring the winners of the NEH 2009 Digging into Data (DiD) Challenge. Participants in the Challenge included many libraries and archives that made their collections available to the researchers.  The awardees included 8 winning projects.
Each DiD project is composed of an international team of scholars and scientists. Each team selected one institution to be the awardee of record for each granting agency. However, many other institutions played critical roles in each project.  Below, we will list both the awardees of record as well as other key team members.
Structural Analysis of Large Amounts of Music Information
Awardees:  Stephen Downie, University of Illinois at Urbana-Champaign, NSF; David De Roure, University of Southhampton, JISC; Ichiro Fujinaga, McGill University, SSHRC.
Additional Key Participants:  The Internet Archive, Indiana University, Anthology of Recorded Music (DRAM), and the British Broadcasting Corporation.
Description:  This project will gather approximately 23,000 hours of digitized music representing a wide range of styles, regions and time periods. The goal is to develop tools to tag and analyze the underlying structures of this music, resulting in a body of world music that will provide music scholars with interactive access to previously unavailable analysis and insights.
Digging into the Enlightenment: Mapping the Republic of Letters
Awardees: Dan Edelstein, Stanford University, NEH; Chris Weaver, University of Oklahoma, NSF; Robert McNamee, University of Oxford, JISC.
Additional Key Participants:  The National Publication of the Works of Antonio Vallisneri, Princeton University, Uppsala University, Utrecht University, Bard Graduate Center, International Center for the History of Universities and Science, University of California at Berkeley, Rutgers University, and the French National Center for Scientific Research.
Description: This project will focus on a body of 53,000 18th-century letters, and analyze the degree to which the effects of the Enlightenment can be observed in the letters of people of various occupations.
Using Zotero and TAPoR on the Old Bailey Proceedings: Data Mining with Criminal Intent
Awardees: Dan Cohen, George Mason University, NEH; Tim Hitchcock, University of Hertfordshire, JISC; Geoffrey Rockwell, University of Alberta, SSHRC.
Additional Key Participants:  The National Archives (United Kingdom), McMaster University, the Open University, Amherst College, University of Sheffield, Trent University, and the University of Western Ontario.
Description: This project will create an intellectual exemplar for the role of data mining in an important historical discipline – the history of crime – and illustrate how the tools of digital humanities can be used to wrest new knowledge from one of the largest humanities data sets currently available: the Old Bailey Online.
Towards Dynamic Variorum Editions
Awardees: Gregory Crane, Tufts University, NEH; John Darlington, Imperial College, London, JISC; Bruce Robertson, Mount Allison University, SSHRC.
Additional Key Participants: The University of Massachusetts, Amherst, University of Leipzig, Cairo University, Humboldt University, Berlin.
Description: The creation of a framework to produce “dynamic variorum” editions of classics texts that enable the reader to automatically link not only to variant editions but also to relevant citations, quotations, people, and places that are found in a digital library of over one million primary and secondary source texts.
Digging into Image Data to Answer Authorship Related Questions
Awardees: Dean Rehberger, Michigan State University, NEH; Peter Bajcsy, University of Illinois at Urbana-Champaign, NSF; Peter Ainsworth, University of Sheffield, JISC.
Additional Key Participants: The Alliance for American Quilts.
Description: This project will pursue research using advanced computational techniques to explore humanities themes related to the authorship of large collections of cultural heritage materials, namely 15th century manuscripts, 17th and 18th century maps, and 19th and 20th century quilts.
Harvesting Speech Datasets for Linguistic Research on the Web
Awardees: Mats Rooth, Cornell University, NSF; Michael Wagner, McGill University, SSHRC.
Description: This project will harvest audio and transcribed data from podcasts, news broadcasts, public and educational lectures and other sources to create a massive corpus of speech. Tools will then be developed to analyze the different uses of prosody (rhythm, stress and intonation) within spoken communication.
Railroads and the Making of Modern America—Tools for Spatio-Temporal Correlation, Analysis, and Visualization
Awardees: William Thomas, University of Nebraska-Lincoln, NEH; Richard Healey, University of Portsmouth, JISC
Additional Key Participants: The University of Victoria, McGill University, Paris One University, University of Lancaster, Middlebury College, and Stanford University.
Description: This project will integrate a vast collection of textual, geographical and numerical data to allow for the visual presentation of the railroads and its impact on society over time, concentrating initially on the Great Plains and Northeast United States.

Mining a Year of Speech

Awardees: Mark Liberman, University of Pennsylvania, NSF; John Coleman, University of Oxford, JISC.
Additional Key Participants:  The British Library.
Description: This project focuses on large scale data analysis of audio — specifically the spoken word.  This project will create tools to enable rapid and flexible access to over 9,000 hours of spoken audio files, containing a wide variety of speech, drawn from some of the leading British and American spoken word corpora, allowing for new kinds of linguistic analysis.

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