DocumentCode
3093717
Title
Conflict detection for integration of taxonomic data sources
Author
Embury, Suzanne M. ; Jones, Andrew C. ; Sutherland, Iain ; Gray, W. Alex ; White, Richard J. ; Robinson, John S. ; Bisby, Frank A. ; Brandt, Sue M.
Author_Institution
Dept. of Comput. Sci., Cardiff Univ., UK
fYear
1999
fDate
36373
Firstpage
204
Lastpage
213
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
Keywords
PROLOG; biology computing; classification; relational databases; scientific information systems; LITCHI project; Prolog; biologists; checklists; conflict detection; formal model; global information systems; global scale; independently created biodiversity databases; international initiatives; naming conflicts; relational database; species diversity; species names; taxonomic checklists; taxonomic data source integration; taxonomic practice; Biodiversity; Biological system modeling; Biology; Computer science; Databases; Environmental factors; Informatics; Information systems; Prototypes; Systematics;
fLanguage
English
Publisher
ieee
Conference_Titel
Scientific and Statistical Database Management, 1999. Eleventh International Conference on
Conference_Location
Cleveland, OH
Print_ISBN
0-7695-0046-3
Type
conf
DOI
10.1109/SSDM.1999.787636
Filename
787636
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