Conflict Detection for Integration of Taxonomic Data Sources

  • Authors:
  • Suzanne M. Embury;Andrew C. Jones;Iain Sutherland;W. Alex Gray;Richard J. White;John S. Robinson;Frank A. Bisby;Sue M. Brandt

  • Affiliations:
  • -;-;-;-;-;-;-;-

  • Venue:
  • SSDBM '99 Proceedings of the 11th International Conference on Scientific and Statistical Database Management
  • Year:
  • 1999

Quantified Score

Hi-index 0.00

Visualization

Abstract

Over recent years, international initiatives such as the 1993 U.N. 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. In this paper, 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.