Poster: Improving the Character of Optical Recognition (OCR)

TitlePoster: Improving the Character of Optical Recognition (OCR)
Publication TypePR Materials
Year of Publication2012
AuthorsAnglin, Robert, Best Jason, Figueiredo Renato, Gilbert Edward, Gnanasambandam Nathan, Gottschalk Stephen, Haston Elspeth, P. Heidorn Bryan, Lafferty Daryl, Lang Peter, Nelson Gil, Paul Deborah L., Ulate William, Watson Kimberly, and Zhang Qianjin
Keywordseducation, machine language, Natural Language Processing, NLP, optical character recognition, Outreach, poster
AbstractThere are an estimated 2 – 3 billion museum specimens world – wide (OECD 1999, Ariño 2010). In an effort to increase the research value of their collections, institutions across the U. S. have been seeking new ways to cost effectively transcribe the label information associated with these specimen collections. Current digitization methods are still relatively slow, labor-intensive, and therefore expensive. New methods, such as optical character recognition (OCR), natural language processing, and human-in-the-loop assisted parsing are being explored to reduce these costs. The National Science Foundation (NSF), through the Advancing Digitization of Biodiversity Collections (ADBC) program, funded Integrated Digitized Biocollections (iDigBio) in 2011 to create a Home Uniting Biodiversity Collections (HUB) cyberinfrastructure to aggregate and collectively integrate specimen data and find ways to digitize specimen data faithfully and faster and disseminate the knowledge of how to achieve this. The iDigBio Augmenting OCR Working Group is part of this national effort. - speed up the overall digitization process, - lower the cost, - improve overall efficiency, - assure digitized data is fit-for-use (NIBA 2010, Chapman 2005), and - provide the resulting digitized data records to researchers more quickly. The iDigBio Augmenting OCR (A-OCR) working group is actively engaged in identifying opportunities for collaboration to leverage OCR tools and technologies that are successful (both within and outside of the biology digitization domain) and disseminate these tools to the public or seek funding for development.
Poster accepted and published at iConference 2012. See for publication details.