Authors:
Elizabeth Arnaud
1
;
Laurel Cooper
2
;
Rosemary Shrestha
3
;
Naama Menda
4
;
Rex T. Nelson
5
;
Luca Matteis
1
;
Milko Skofic
1
;
Ruth Bastow
6
;
Pankaj Jaiswal
2
;
Lukas Mueller
4
and
Graham McLaren
7
Affiliations:
1
Bioversity International, Italy
;
2
Oregon State University, United States
;
3
Centro Internacional de Mejoramiento de Maiz y Trigo (CIMMYT), Mexico
;
4
Boyce Thompson Institute for Plant Research, United States
;
5
USDA-ARS CICGRU, United States
;
6
University of Warwick, United Kingdom
;
7
Generation Challenge Program, Mexico
Keyword(s):
Agriculture, Plant Phenotype, Plant Trait Ontology, Integrated Breeding Knowledge, Community of Practice.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Collaboration and e-Services
;
Data Engineering
;
e-Business
;
Enterprise Information Systems
;
Information Integration
;
Information Systems Analysis and Specification
;
Integration/Interoperability
;
Knowledge Engineering and Ontology Development
;
Knowledge Representation
;
Knowledge-Based Systems
;
Ontologies and the Semantic Web
;
Ontology Engineering
;
Ontology Matching and Alignment
;
Ontology Sharing and Reuse
;
Symbolic Systems
Abstract:
Ontology engineering and knowledge modeling for the plant sciences is expected to contribute to the understanding of the basis of plant traits that determine phenotypic expression in a given environment. Several crop- or clade-specific plant trait ontologies have been developed to describe plant traits important for agriculture in order to address major scientific challenges such as food security. We present three successful species and/or clade-specific ontologies which address the needs of crop scientists to quickly access a wide range of trait related data, but their scope limits their interoperability with one another. In this paper, we present our vision of a species-neutral and overarching Reference Plant Trait Ontology which would be the basis for linking the disparate knowledge domains and that will support data integration and data mining across species.