@conference {IT407, title = {IT407: Annotating germplasm to Planteome reference ontologies}, booktitle = {International Conference on Biomedical Ontology and BioCreative (ICBO BioCreative 2016)}, series = {Proceedings of the Joint International Conference on Biological Ontology and BioCreative (2016)}, year = {2016}, month = {11/30/16}, publisher = {CEUR-ws.org Volume 1747}, organization = {CEUR-ws.org Volume 1747}, abstract = {

An expected use case of plant phenotype ontologies will be the identification of germplasm containing particular traits of interest. If phenotype data from experiments is annotated using ontologies, it makes sense to include annotations to that germplasm source. A lack of standardized data formatting reduces the utility of these data. Standardizing germplasm data, including links to germplasm databases, or distribution locations improves collaboration, and benefits both researchers and the scientific community as a whole. All plant traits contained in the Planteome reference ontologies are searchable, and interconnected through relationships in the ontology. All data annotated to these reference ontologies will be displayed, shareable, and computable through the Planteome website (www.planteome.org) and APIs. This manuscript will discuss the advantages of standardizing germplasm trait annotation, and the semi-automated process developed to achieve such standardization.

}, url = {http://ceur-ws.org/Vol-1747/IT407_ICBO2016.pdf}, author = {Austin Meier and Laurel Cooper and Justin Elser and Pankaj Jaiswal and Marie-Ang{\'e}lique Laporte} } @conference {IT406, title = {IT406-IP35: The Planteome Project}, booktitle = {International Conference on Biomedical Ontology and BioCreative (ICBO BioCreative 2016)}, series = {Proceedings of the Joint International Conference on Biological Ontology and BioCreative (2016)}, year = {2016}, month = {11/30/16}, publisher = {CEUR-ws.org Volume 1747}, organization = {CEUR-ws.org Volume 1747}, abstract = {

The Planteome project is a centralized online plant informatics portal which provides semantic integration of widely diverse datasets with the goal of plant improvement. Traditional plant breeding methods for crop improvement may be combined with next-generation analysis methods and automated scoring of traits and phenotypes to develop improved varieties. The Planteome project (www.planteome.org) develops and hosts a suite of reference ontologies for plants associated with a growing corpus of genomics data. Data annotations linking phenotypes and germplasm to genomics resources are achieved by data transformation and mapping species-specific controlled vocabularies to the reference ontologies. Analysis and annotation tools are being developed to facilitate studies of plant traits, phenotypes, diseases, gene function and expression and genetic diversity data across a wide range of plant species. The project database and the online resources provide researchers tools to search and browse and access remotely via APIs for semantic integration in annotation tools and data repositories providing resources for plant biology, breeding, genomics and genetics.

}, url = {http://ceur-ws.org/Vol-1747/IT406-IP35_ICBO2016.pdf}, author = {Laurel Cooper and Austin Meier and Justin Elser and Justin Preece and Xu Xu and Ryan Kitchen and Botong Qu and Eugene Zhang and Sinisa Todorovic and Pankaj Jaiswal and Marie-Ang{\'e}lique Laporte and Elizabeth Arnaud and Seth Carbon and Chris Mungall and Barry Smith and Georgios Gkoutos and John Doonan} } @conference {IT205, title = {IT205: Data-driven Agricultural Research for Development: A Need for Data Harmonization Via Semantics}, booktitle = {International Conference on Biomedical Ontology and BioCreative (ICBO BioCreative 2016)}, series = {Proceedings of the Joint International Conference on Biological Ontology and BioCreative (2016)}, year = {2016}, month = {11/30/16}, publisher = {CEUR-ws.org Volume 1747}, organization = {CEUR-ws.org Volume 1747}, abstract = {

Addressing global challenges to agricultural productivity and profitability increasingly requires access to data from a variety of disciplines, and the ability to easily combine and analyze related data sets. Innovation in agricultural research for development must therefore be mediated by reliable and consistently annotated information resources across disciplinary domains. Leveraging semantics ensures this consistency and ease of reuse, and the global CGIAR Consortium that includes 15 agricultural research for development Centers is attempting to harness this promise through efforts such as its Open Access, Open Data Initiative. CGIAR{\texttrademark}s Crop Ontology project plays a key role in this, and will soon be enhanced by an Agronomy Ontology (AgrO). AgrO is being built to represent traits identified by agronomists and the simulation model variables of the International Consortium for Agricultural Systems Applications (ICASA). Further, it will coordinate its semantics with existing ontologies such as the Environment Ontology (ENVO), Unit Ontology (UO), and Phenotype And Trait Ontology (PATO). Once stable, it is anticipated to address one of the domains temporarily represented in the Sustainable Development Goals Interface Ontology (SDGIO), pertaining to multiple SDGs such as the elimination of hunger and poverty. AgrO will complement existing crop, livestock, and fish ontologies to enable harmonized approaches to data collection, facilitating data sharing and reuse. Further, AgrO will power an Agronomy Management System and fieldbook, similar to the Crop Ontology-based Integrated Breeding Platform (IBP) and fieldbook. There is substantial interest from agronomists and modelers in such a fieldbook to standardize agronomic data collection, and the ontology itself as a means of facilitating hitherto missing linkages with breeding and other data, and enabling wider sharing and reuse of agronomic research data.

}, url = {http://ceur-ws.org/Vol-1747/IT205_ICBO2016.pdf}, author = {Medha Devare and C{\'e}line Aubert and Marie-Ang{\'e}lique Laporte and L{\'e}o Valette and Elizabeth Arnaud and Pier Luigi Buttigieg} } @conference {IT204, title = {IT204: A sustainable approach to knowledge representation in the domain of sustainability: bridging SKOS and OWL}, booktitle = {International Conference on Biomedical Ontology and BioCreative (ICBO BioCreative 2016)}, series = {Proceedings of the Joint International Conference on Biological Ontology and BioCreative (2016)}, year = {2016}, month = {11/30/16}, publisher = {CEUR-ws.org Volume 1747}, organization = {CEUR-ws.org Volume 1747}, abstract = {n/a}, url = {http://icbo.cgrb.oregonstate.edu/}, author = {Chris Mungall and Mark Jensen and Marie-Ang{\'e}lique Laporte and Pier Buttigieg} } @conference {IP17, title = {IP17: Comparison of ontology mapping techniques to map plant trait ontologies}, booktitle = {International Conference on Biomedical Ontology and BioCreative (ICBO BioCreative 2016)}, series = {Proceedings of the Joint International Conference on Biological Ontology and BioCreative (2016)}, year = {2016}, month = {11/30/16}, publisher = {CEUR-ws.org Volume 1747}, organization = {CEUR-ws.org Volume 1747}, abstract = {

Crop specific ontologies for phenotype annotations in breeding have proliferated over the last 10 years. Across-crop data interoperability involves linking those ontologies together. For this purpose, the Planteome project is mapping the Crop Ontology traits (www.cropontology.org) to the reference ontology for plant traits, Trait Ontology (TO). Manual mapping is time-consuming and not sustainable in the long-run as ontologies keep on evolving and multiplicating. We are thus working on developing reliable automated mapping techniques to assist curators in performing semantic integration. Our study shows the benefit of the ontology matching technique based on formal definitions and shared ontology design patterns, compared to standard automatic ontology matching algorithm, such as AML (AgreementMakerLight).

}, url = {http://ceur-ws.org/Vol-1747/IP17_ICBO2016.pdf}, author = {Marie-Ang{\'e}lique Laporte and L{\'e}o Valette and Laurel Cooper and Chris Mungall and Austin Meier and Pankaj Jaiswal and Elizabeth Arnaud} }