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February 10, 2019 by Gary Price

“How to Think About Data: A Conversation with Christine Borgman”

February 10, 2019 by Gary Price

From “Insights: Scholarly Work at the John W. Kluge Center (LOC):

Members of the Scholars Council are appointed by the Librarian of Congress to advise on matters related to scholarship at the Library, with special attention to the Kluge Center and the Kluge Prize. The Council includes scholars, writers, researchers, and scientists. “Insights” is featuring some of the work of this group of thinkers. Dan Turello continues the series in a conversation with Christine Borgman.

Christine L. Borgman, Distinguished Research Professor and Presidential Chair Emerita in Information Studies at UCLA, is the author of more than 250 publications in information studies, computer science, and communication. These include three books from MIT Press: “Big Data, Little Data, No Data: Scholarship in the Networked World” (2015), “Scholarship in the Digital Age: Information, Infrastructure, and the Internet” (2007), and “From Gutenberg to the Global Information Infrastructure: Access to Information in a Networked World” (2000).

DT: Christine, you have a background in mathematics. What inspired you to study libraries and data?

CB: In the 1970s, women with math degrees had two career options: teaching school or programming. Having done some of each, I sought a career that combined technology, teaching, and communication. Those were the early days of library automation, and my mother, a superlative reference librarian at Wayne State University who hated computers, recognized the profession’s dire need for my skillset. Allen Kent managed an information empire at the University of the Pittsburgh that spanned the Library and Information Science graduate program, the university library, the computer center, and his NSF and NASA-funded research group. As a project director, he hired me to be a graduate student researcher on his information retrieval grants, and as my academic advisor, he allowed me to count math and computing courses in data modeling toward my Master’s in Library Science (MLS) degree.

My MLS-information science degree was ahead of its time, and an ideal qualification to become systems analyst for the Dallas Public Library. We extended a home-grown, semi-automated, circulation system into the first online catalog of a major public library. Because the library catalog system was built on the city’s IBM mainframe (in assembler language, no less), it was a distributed system available to the branch libraries and to all City of Dallas employees who had computer terminals on their desks. Leading the library’s design team was a humbling experience, and a crash course in collaboration, metadata, human-computer interaction, programming, systems development life cycles, distributed computing, evaluation, management, and much else.

Read the Complete Conversation (approx. 2000 words)

A Few infoDOCKET Posts Featuring Presentations/Writing by Dr. Borgman:

Presentation Video and Slides: “Why Data Sharing & Reuse Are Hard To Do?”

Video Recording: “Open Data, Grey Data, and Stewardship: Universities at the Privacy Frontier” (Presentation by Christine Borgman at Harvard’s Berkman Klein Center)

New Article (Accepted For Publication Manuscript): “Open Data, Grey Data, and Stewardship: Universities at the Privacy Frontier”

Filed under: Academic Libraries, Data Files, Funding, Jobs, Libraries, Management and Leadership, News, Public Libraries, Video Recordings

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About Gary Price

Gary Price (gprice@gmail.com) is a librarian, writer, consultant, and frequent conference speaker based in the Washington D.C. metro area. He earned his MLIS degree from Wayne State University in Detroit. Price has won several awards including the SLA Innovations in Technology Award and Alumnus of the Year from the Wayne St. University Library and Information Science Program. From 2006-2009 he was Director of Online Information Services at Ask.com. Gary is also the co-founder of infoDJ an innovation research consultancy supporting corporate product and business model teams with just-in-time fact and insight finding.

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