Improved Retrieval: The National Archives (NARA) Catalog Adds OCR (Optical Character Recognition) For Some Records
With more than 92 million pages of digitized records available to search in the National Archives Catalog, we are always working on ways to improve search results to better help you find what you’re looking for.
OCR converts images that contain typed, handwritten, or printed text into text that can be read and searched by a computer.
Previously, records in the Catalog were only searchable based on the titles, descriptions, and other fields entered by archivists, or by tags and transcriptions entered by citizen archivists. Now, with OCR capability, text from some images in the Catalog can be extracted, making that text searchable and more likely to come up in your search results.
Currently, the Catalog’s new OCR engine is applied to records in either JPG or PDF format added to the Catalog since June 2019. NARA is exploring how to retroactively process records from before that point, but right now this feature applies to millions of pages!
NARA’s new OCR engine is powered by the open source Tesseract software. As records are added to NARA’s Amazon Web Services (AWS) S3 cloud storage, it is run through image processing powered by a series of AWS Lambda functions.
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.