The Princeton University Library (PUL) sought support from the Latin Americanist Research Resources Project (LARRP) for digitizing an extensive hidden collection of ephemeral materials from Latin America. The proposed 3-year pilot project is an essential step in the larger process of making the digitally reformatted ephemera freely and globally available through a discovery interface which will include faceted searching and browsing. Outcomes of the 3-year project are approximately 12,800 digital objects with accompanying item-level descriptive metadata, deployment of a scalable, sustainable and replicable model for timely online disclosure of similar collections with a robust...
The project will digitize and describe 25 boxes, comprising approximately 27,000 pages, from the Fondo Real de Cholula, a one-of-a-kind collection of documents providing insight into how indigenous residents of Cholula navigated colonial judicial structures over the span of four centuries. The project partners with the Archivo Judicial del Estado de Puebla, and employs three local historians to digitize and describe the collection. Logistical and technical support, as well as long-term preservation and access infrastructure, will be provided by LLILAS Benson Latin American Studies and Collections (LLILAS Benson), in collaboration with the University of Texas Libraries (UT Libraries).
Proposal to convert and upgrade the digital collection of Mexican and Argentine presidential speeches from the 19th century orginially scanned by the Latin Americanist Research Resources Project (LARRP).
In 2000, LARRP converted over 75,000 frames of microfilmed Spanish-language government documents to digital format. The material was originally microfilmed by the Library of Congress (Argentina) and LAMP (Mexico) on LARRP's behalf. The converted materials were hosted by LANIC at the University of Texas at Austin as GIF files, with larger TIFF files available for downloading.
We propose to harvest the TIFF images from LANIC/Texas (with permission) and to re-process the files to capture full text (OCR) and related metadata.
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