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Transforming text into discovery: OCR enrichment of digital collections in the University of Galway Library

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Název: Transforming text into discovery: OCR enrichment of digital collections in the University of Galway Library
Autoři: Dereza, Oksana, Rouget, Marie-Louise, Egwu, Chidi, Joy, Cillian
Přispěvatelé: Department of Tourism, Culture, Arts, Gaeltacht, Sport and Media, Ireland, Carnegie Corporation, University of Galway Research Repository
Informace o vydavateli: IEEE, 2025.
Rok vydání: 2025
Témata: OCR, Collections as Data, IIIF, Optical Character Recognition, OCR workflow, Digital Collections, Heritage Collections
Popis: The University of Galway Library has been working on an Optical Character Recognition (OCR) pipeline to transform scanned archival materials into machine-readable text at scale. This significantly enhances the accessibility and searchability of the University’s digitised heritage collections, supporting diverse areas of research interest and fostering deeper engagement with the Library’s holdings. The paper discusses key aspects of building an OCR pipeline, including the performance of available OCR software on heritage data, pre-processing of digitised images, quality assurance, and converting the OCR engine outputs for DAMS upload and seamless IIIF integration. The pipeline aims at balancing automation with quality control for successful extraction of printed, typewritten and handwritten text. We believe that our experience may help other GLAM institutions that are considering incorporating automatic text extraction into their digital collections workflow.
Druh dokumentu: Conference object
Popis souboru: application/pdf
Jazyk: English
Přístupová URL adresa: https://hdl.handle.net/10379/19264
Rights: CC BY NC ND
Přístupové číslo: edsair.od......1513..b9b4b0aa475f3749048b58b51a73c881
Databáze: OpenAIRE
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  Data: Transforming text into discovery: OCR enrichment of digital collections in the University of Galway Library
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  Data: <searchLink fieldCode="AR" term="%22Dereza%2C+Oksana%22">Dereza, Oksana</searchLink><br /><searchLink fieldCode="AR" term="%22Rouget%2C+Marie-Louise%22">Rouget, Marie-Louise</searchLink><br /><searchLink fieldCode="AR" term="%22Egwu%2C+Chidi%22">Egwu, Chidi</searchLink><br /><searchLink fieldCode="AR" term="%22Joy%2C+Cillian%22">Joy, Cillian</searchLink>
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  Data: Department of Tourism, Culture, Arts, Gaeltacht, Sport and Media, Ireland<br />Carnegie Corporation<br />University of Galway Research Repository
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  Data: IEEE, 2025.
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  Data: 2025
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  Data: <searchLink fieldCode="DE" term="%22OCR%22">OCR</searchLink><br /><searchLink fieldCode="DE" term="%22Collections+as+Data%22">Collections as Data</searchLink><br /><searchLink fieldCode="DE" term="%22IIIF%22">IIIF</searchLink><br /><searchLink fieldCode="DE" term="%22Optical+Character+Recognition%22">Optical Character Recognition</searchLink><br /><searchLink fieldCode="DE" term="%22OCR+workflow%22">OCR workflow</searchLink><br /><searchLink fieldCode="DE" term="%22Digital+Collections%22">Digital Collections</searchLink><br /><searchLink fieldCode="DE" term="%22Heritage+Collections%22">Heritage Collections</searchLink>
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  Data: The University of Galway Library has been working on an Optical Character Recognition (OCR) pipeline to transform scanned archival materials into machine-readable text at scale. This significantly enhances the accessibility and searchability of the University’s digitised heritage collections, supporting diverse areas of research interest and fostering deeper engagement with the Library’s holdings. The paper discusses key aspects of building an OCR pipeline, including the performance of available OCR software on heritage data, pre-processing of digitised images, quality assurance, and converting the OCR engine outputs for DAMS upload and seamless IIIF integration. The pipeline aims at balancing automation with quality control for successful extraction of printed, typewritten and handwritten text. We believe that our experience may help other GLAM institutions that are considering incorporating automatic text extraction into their digital collections workflow.
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      – Text: English
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        Type: general
      – SubjectFull: Collections as Data
        Type: general
      – SubjectFull: IIIF
        Type: general
      – SubjectFull: Optical Character Recognition
        Type: general
      – SubjectFull: OCR workflow
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      – SubjectFull: Digital Collections
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            NameFull: Department of Tourism, Culture, Arts, Gaeltacht, Sport and Media, Ireland
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              M: 06
              Type: published
              Y: 2025
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