Augmenting optical character recognition (OCR) for improved digitization: Strategies to access scientific data in natural history collections

Paul, Deborah L.; Heidorn, P. Bryan

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https://hdl.handle.net/2142/39427 Copy

Description

Title

Augmenting optical character recognition (OCR) for improved digitization: Strategies to access scientific data in natural history collections

Author(s)

• Paul, Deborah L.
• Heidorn, P. Bryan

Issue Date

2013-02

Keyword(s)

• iDigBio
• OCR
• natural language
• information analysis
• machine language
• information organization
• information services
• research methods
• information retrieval
• qualitative data analysis

Abstract

The Augmenting OCR Working Group (A-OCR WG) at Integrated Digitized Biocollections (iDigBio) seeks to improve community OCR strategies and algorithms for faster, better parsing of OCR output derived from valuable data on natural history collection specimen labels. This task is exceedingly difficult because museum labels are often annotated, and vary in content, form and font. Under the National Science Foundation's (NSF) Advancing Digitization of Biological Collections (ADBC) program, iDigBio is building a cyberinfrastructure to aggregate quality data from museum specimens housed in collections across the United States for use by researchers, educators, environmentalists and the public. Since March of 2012, the A-OCR WG formed from community consensus to begin its role in this endeavor, defining reachable goals including setting up a hackathon concurrent with iConference 2013. This paper reports on the definition of some key problems identified by the A-OCR WG since these science problems will drive research and cyberinfrastructure development.

Publisher

iSchools

Type of Resource

text

Language

en

Permalink

http://hdl.handle.net/2142/39427

DOI

https://doi.org/10.9776/13266

Copyright and License Information

Copyright © 2013 is held by the authors. Copyright permissions, when appropriate, must be obtained directly from the authors.

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