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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

ISBN: 978-989-8565-30-3

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.

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Paper citation in several formats:
Arnaud, E.; Cooper, L.; Shrestha, R.; Menda, N.; Nelson, R.; Matteis, L.; Skofic, M.; Bastow, R.; Jaiswal, P.; Mueller, L. and McLaren, G. (2012). Towards a Reference Plant Trait Ontology for Modeling Knowledge of Plant Traits and Phenotypes.In Proceedings of the International Conference on Knowledge Engineering and Ontology Development - Volume 1: KEOD, (IC3K 2012) ISBN 978-989-8565-30-3, pages 220-225. DOI: 10.5220/0004138302200225

@conference{keod12,
author={Elizabeth Arnaud. and Laurel Cooper. and Rosemary Shrestha. and Naama Menda. and Rex T. Nelson. and Luca Matteis. and Milko Skofic. and Ruth Bastow. and Pankaj Jaiswal. and Lukas Mueller. and Graham McLaren.},
title={Towards a Reference Plant Trait Ontology for Modeling Knowledge of Plant Traits and Phenotypes},
booktitle={Proceedings of the International Conference on Knowledge Engineering and Ontology Development - Volume 1: KEOD, (IC3K 2012)},
year={2012},
pages={220-225},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004138302200225},
isbn={978-989-8565-30-3},
}

TY - CONF

JO - Proceedings of the International Conference on Knowledge Engineering and Ontology Development - Volume 1: KEOD, (IC3K 2012)
TI - Towards a Reference Plant Trait Ontology for Modeling Knowledge of Plant Traits and Phenotypes
SN - 978-989-8565-30-3
AU - Arnaud, E.
AU - Cooper, L.
AU - Shrestha, R.
AU - Menda, N.
AU - Nelson, R.
AU - Matteis, L.
AU - Skofic, M.
AU - Bastow, R.
AU - Jaiswal, P.
AU - Mueller, L.
AU - McLaren, G.
PY - 2012
SP - 220
EP - 225
DO - 10.5220/0004138302200225

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