Findingphenotypeassociationsacrossmultipleplantspecies, annotation strategies, and environments has become more di cult as the amount of annotated data has continued to increase. By associating annotations with ontologies as metadata, we can provide a structured, inferrable, and standardized context in which to improve our ability to mine data by more accurately defining our own data.
To this end, the Planteome project (http://planteome.org) ingests over
20 database sources, 80 taxa, and 2 million bioentities (genes, germplasm, QTL). Over 17 million bioentities are annotated to defined ontology terms in a standardized manner. With this infrastructure in place, Planteome provides a browsable resource for multiple reference ontologies for plants such as Plant Ontology (PO) describing anatomy and growth and de- velopmental stages, Plant Trait Ontology (TO) describing phenotype traits, Gene Ontology (GO) describing molecular function, biological process and cellular components, Phenotype and Attribute Trait On- tology (PATO) and the Application ontologies that are species-specific Crop Ontology (CO). The database also allows for an ontology-based, faceted, cross-species search of plant phenomic and genomic data anno- tated with the reference ontologies. Data is denormalized using the GOlr infrastructure (http://wiki.geneontology.org/index.php/GOlr), built on top of the Solr search platform, providing quick and meaningful querying capabilities.
Work is currently underway to allow adopt a standardized Biolink web-
services API (https://github.com/biolink/biolink-api) that, with GOlr,
has already been adopted by the Monarch Initiative (https://monarchinitiative.org), an ontology-based tool for search and aggregation service focused on hu-
man disease through analysis of cross-species annotations.