The Prometheus Description Model: an examination of the taxonomic description-building process and its representation

Pullan, Martin R.; Armstrong, Kate E.; Paterson, Trevor; Cannon, Alan; Kennedy, Jessie B.; Watson, Mark F.; McDonald, Sarah M; Raguenaud, C�dric

Abstract

A model for representing taxonomic descriptive data is presented. The model has been developed in response to the growing requirement for the global exchange of descriptive data. Meaningful exchange of data requires that data be represented in a form that can be consistently parsed and interpreted, requiring a common data model and the constrained and explicitly defined use of descriptive terms. The model presented here is divided into two parts that address both of these issues. A new data model for the representation and storage of taxonomic descriptive data is proposed that builds on and extends the best features of current descriptive data models and formats. An ontology-based model for defining and constraining the use of descriptive terms is also presented. The model is based on an analysis of current taxonomic working practices and the processes involved in generating a description. The model takes a specimen-oriented approach allowing descriptive data to be represented through a range of levels of abstraction from actual measurements of structures on a specimen to abstract descriptions of the features expected to be found on a specimen that is a member of a particular taxon. A comparison and discussion of the important aspects of the new model relative to existing models is presented.

• Journal Article Type: Article
• Publication Date: Aug 1, 2005
• Deposit Date: May 22, 2008
• Publicly Available Date: May 16, 2017
• Journal: Taxon
• Print ISSN: 0040-0262
• Peer Reviewed: Peer Reviewed
• Volume: 54
• Issue: 3
• Pages: 751-765
• DOI: https://doi.org/10.2307/25065431
• Keywords: Botanical Taxonomy; Descriptions; Prometheus Description Model; Taxonomic descriptive data; Ontology
• Public URL: http://researchrepository.napier.ac.uk/id/eprint/1794
• Contract Date: May 16, 2017