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Conflict detection for integration of taxonomic data sources

Embury, Suzanne M., Jones, Andrew Clifford, Sutherland, Iain, Gray, William Alexander, White, R. J., Robinson, J. S., Bisby, F. A. and Brandt, S. M. 1999. Conflict detection for integration of taxonomic data sources. Presented at: Eleventh International Conference on Scientific and Statistical Database Management, Cleveland, OH, USA, 28-30 July 1999. Eleventh International Conference on Scientific and Statistical Database Management, 1999, Cleveland, OH, 28-30 Jul 1999. Los Alamitos, CA: IEEE, pp. 204-213. 10.1109/SSDM.1999.787636

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Abstract

Over recent years, international initiatives such as the 1993 UN Convention on Biological Diversity have highlighted the need for information about species diversity on a global scale. However, attempts to build global information systems by integrating smaller, independently created biodiversity databases have been hampered by differences in the sets of species names used. Some databases use different names to refer to the same species, while in other cases the same name can be applied to differing definitions of a species, or even entirely different species. The LITCHI project aims to assist biologists in the integration of databases by searching for conflicts within taxonomic checklists (i.e. lists of the species names used in a database and the relationships between them). In order to detect such conflicts, we have created a formal model of taxonomic practice, which describes (amongst other things) what it means for a checklist to be consistent and well-specified. This model has been used as the basis for a prototype tool that uses Prolog to search for naming conflicts within a relational database of checklists. We describe the background to our formal model and show how it has been used to implement the LITCHI system. Our prototype tool is already proving its worth by detecting conflicts and errors within real taxonomic checklists

Item Type: Conference or Workshop Item (Paper)
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Publisher: IEEE
ISBN: 0769500463
Related URLs:
Last Modified: 03 Feb 2022 11:59
URI: https://orca.cardiff.ac.uk/id/eprint/14603

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