Towards a Reference Plant Trait Ontology for Modeling Knowledge of Plant Traits and Phenotypes

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. use terms consistently in scientific publications or standardized handbooks on quality/trait evaluations, and to search for and integrate data linked to these terms in anatomical, genetic, genomic, and other types of biological databases.

A COMPASS for VESPUCCI: A FAIR Way to Explore the Grapevine Transcriptomic Landscape

“…A term could also be a special kind of ontological term, called Blank node, that is used to connect different triples and make more expressive statements about specific conditions. Several ontologies have been used to annotate samples and genes, both generic, such as Nci thesaurus ( Ceusters et al, 2005 ) or Dbpedia 2 , and plant specific ones, such as the Plant ontology ( Jaiswal et al, 2005 ) or the Plant trait ontology ( Arnaud et al, 2012 ). SPARQL 3 (SPARQL Protocol and RDF Query Language) is the query language used to navigate relationships in RDF graph data (see Figure 2 ) through graph pattern matching, by combining simple patterns into more complex ones allowing the exploration of elaborate relationships in the data.…”

Features of a FAIR vocabulary

“…The Plant Phenotyping Experiment Ontology (PPEO) [38] implements the Minimum Information about Plant Phenotyping Experiment(MIAPPE) [39]standards and covers essential attributes to describe a MIAPPE-compliant phenotype dataset. We mapped the RDA indicators to FAIR Vocabulary Features, filtering out indicators that do not apply to vocabularies.…”

The Ontologies Community of Practice: A CGIAR Initiative for Big Data in Agrifood Systems

“…To remediate this situation and create the necessary upper-level connection between the species-specific ontologies, CO trait terms were mapped to terms, thus enabling searches of annotated data across species, using a single trait term. 14,15 As a result, Planteome Release 3.0 includes ten species-specific trait ontologies developed by the CO for the crops: cassava (Manihot esculenta), maize (Zea mays), pigeonpea (Cajanus cajan), rice (Oryza sativa), sweet potato (Ipomoea batatas), soybean (Glycine max), wheat (Triticum aestivum), lentil (Lens culinaris), sorghum (Sorghum bicolor), and yam (Dioscorea sp.). These mappings can be automatically created but still require manual curation, making them difficult to maintain considering that ontologies evolve over time.…”