Automatic Metadata Extraction from Museum Specimen Labels

Heidorn, P. Bryan

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https://hdl.handle.net/2142/9138 Copy

Description

Title

Automatic Metadata Extraction from Museum Specimen Labels

Author(s)

Heidorn, P. Bryan

Contributor(s)

Wei, Qin

Issue Date

2008-09-24

Keyword(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.

Publisher

Published by the Dublin Core Metadata Initiative and Universitätsverlag Göttingen 2008

ISSN

1939-1358

Type of Resource

text

Language

en

Permalink

http://hdl.handle.net/2142/9138

Copyright and License 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.

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