Innovator in Residence Program

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Innovator in Residence Program


About the Residency

We’ve established a broad Innovator in Residence Program to support innovative and creative uses of our collections that showcase how the Library relates to and enriches the work, life, and imagination of the American people.

We will pay you up to $80,000 each year for a maximum of two years to do research with Library of Congress collections, produce a creative and transformative digital work for the American people, and serve as an ambassador for the Library. We anticipate the residency will take place part-time both virtually and in-person, beginning in September 2022. You will propose your own schedule for the residency as part of the application process. The unique work must be delivered within the first year. In the second year, you will promote and connect your work and Library resources with communities, continue your research, and create scaffolding materials for your work to support community interaction. Work completed in year one cannot be dependent on a second year, which is optional.

How to Apply

The Innovator in Residence application process has two phases: 1) a 3-page concept paper and 2) an invitation-only full proposal.

The Library is accepting concept papers until May 2nd, 2022 at 12pm EDT. Follow the instructions in Sections 4.1 and 5.1 of the Broad Agency Announcement External to apply. You may also wish to consult this list of Frequently Asked Questions as you prepare your application, and these collection ideas from library staff.

Past Innovators

  • 2021 Courtney McClellan – designed and curated Speculative Annotation, a dynamic website presenting items from the Library’s collections for students and teachers to have conversations with history through annotation.
  • 2020 Brian Foo – created the application Citizen Dj to enable the public to discover and create from LC free to use sound collections. Brian’s concept paper is available at [baa link] for applicants to see.
  • 2020 Benjamin Charles Lee – created a way for users to explore visual content from historic newspapers in the Chronicling America collection using machine learning.
  • 2018 Jer Thorp – applied the idea of serendipity to the scale of LC collections through the podcast “Artist in the Archive” and a suite of applications

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