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Automatic Metadata Extraction from Museum Specimen Labels

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Bookmark or cite this item: http://hdl.handle.net/2142/9138

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Title: Automatic Metadata Extraction from Museum Specimen Labels
Author(s): Heidorn, P. Bryan
Contributor(s): Wei, Qin
Subject(s): Metadata Text Processing biological informatics machine learning Darwin Core
Abstract: This paper describes the information properties of museum specimen labels and machine learning tools to automatically extract Darwin Core (DwC) and other metadata from these labels processed through Optical Character Recognition (OCR). The DwC is a metadata profile describing the core set of access points for search and retrieval of natural history collections and observation databases. Using the HERBIS Learning System (HLS) we extract 74 independent elements from these labels. The automated text extraction tools are provided as a web service so that users can reference digital images of specimens and receive back an extended Darwin Core XML representation of the content of the label. This automated extraction task is made more difficult by the high variability of museum label formats, OCR errors and the open class nature of some elements. In this paper we introduce our overall system architecture, and variability robust solutions including, the application of Hidden Markov and Naïve Bayes machine learning models, data cleaning, use of field element identifiers, and specialist learning models. The techniques developed here could be adapted to any metadata extraction situation with noisy text and weakly ordered elements.
Issue Date: 2008-09-24
Publisher: Published by the Dublin Core Metadata Initiative and Universitätsverlag Göttingen 2008
Citation Info: Proceedings of the International Conference on Dublin Core and Metadata Applications Berlin, 22-26 September 2008 DC 2008: Berlin, Germany. Edited by Jane Greenberg and Wolfgang Klas
Genre: Article
Type: Text
Language: English
URI: http://hdl.handle.net/2142/9138
ISBN: 978-3-940344-49-6
ISSN: 1939-1358
Publication Status: published or submitted for publication
Peer Reviewed: is peer reviewed
Rights Information: This work is protected by German Intellectual Property Right Law. It is also available as an Open Access version through the publisher’s homepage and the Online Catalogue of the State and University Library of Goettingen (http://www.sub.uni-goettingen.de). Users of the free online version are invited to read, download and distribute it. Users may also print a small number for educational or private use. However they may not sell print versions of the online book.
Date Available in IDEALS: 2008-10-25
 

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