Hip Hop and Human-Computer Interaction Focus of 2020 Innovators in Residence at the Library of Congress
The Library of Congress today announced the arrival of its 2020 Innovators in Residence, who will break new ground at the intersections of technology and hip hop, historic newspapers and classic illustrations.
Established in 2017 to invite creative people to develop research concepts and projects that connect the American people with the Library’s vast collections, the Innovator in Residence program brings some of the most creative and bold thinkers in-house at the largest library in the world.
The Innovators in Residence for 2020 are Brian Foo and Benjamin Charles Germain Lee.
Brian Foo has over two decades of computer science and design experience and has worked in cultural heritage institutions for the past seven years. His work includes the design and development of a dynamic exhibit about climate change at the American Museum of Natural History, as well as Data-Driven DJ, a 10 song album produced entirely from public datasets and open source software to be exhibited in the Museum of the City of New York later this year.
During his time as an Innovator in Residence at the Library, Foo will create “Citizen DJ,” an application enabling anyone with a web browser to create hip hop music with public domain audio and video materials from the Library’s collections. “The goal of my project is to use the library’s public domain audio as source material for hip hop music production,” said Foo. “By embedding these materials in hip hop music, listeners can discover items in the library’s vast collections that they likely would never have known existed.”
Ben Lee is a Ph.D. student in computer science and engineering at the University of Washington, where he studies machine learning and its applications to information access. He has previously served as the inaugural Digital Humanities Associate Fellow at the United States Holocaust Memorial Museum, Visiting Fellow in Harvard’s History Department, and is currently a National Science Foundation Graduate Research Fellow.
Lee’s work as an Innovator in Residence will focus on using machine learning to extract photographs and illustrations from historic newspapers in the “Chronicling America” collection to make them searchable and accessible. He will also create a search interface that will allow users to browse the collection at scale. “A primary motivation behind my project is to encourage innovation by demonstrating the power of machine learning applied to library collections,” said Lee. “The appeal of this research cuts three ways: first, it allows users to experience the Library’s digital collections in an engaging way; second, it enables cultural heritage practitioners to ask new research questions; and third, it allows computer scientists to better understand how people are using the systems they build.”
Library of Congress Labs established the Innovator in Residence program to leverage the expertise of outside experts to help spur technical creativity through short-term, high-impact projects. Data artist and educator Jer Thorp served as the first Innovator in Residence, where he produced the podcast “Artist in the Archive” and the “Serendipity Engine” project, a collection of proof of concept applications that upend traditional paradigms of search, supporting generally curious users to engage with large cultural heritage collections without specific research questions in mind. All of Thorp’s works are available on the LC Labs website.
About Gary Price
Gary Price (email@example.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.