Data sharing and ontology use among agricultural genetics, genomics, and breeding databases and resources of the Agbiodata Consortium

Authors

Jennifer L. Clarke, University of Nebraska–Lincoln
Laurel D. Cooper, Oregon State University
Monica F. Poelchau, USDA, Agricultural Research Service
Tanya Z. Berardini, The Arabidopsis Information Resource and Phoenix Bioinformatic
Justin Elser, Oregon State University
Andrew D. Farmer, National Center for Genome Resources
Stephen Ficklin, Washington State University
Sunita Kumari, Cold Spring Harbor Laboratory
Marie-Angélique Laporte, Parc Scientifique Agropolis II
Rex T. Nelson, Iowa State University
Rie Sadohara, Michigan State University
Peter Selby, Cornell University
Anne E. Thessen, University of Colorado Anschutz
Brandon Whitehead, Massey University
Taner Z. Sen, USDA, Agricultural Research Service, University of California-Berkeley

Document Type

Article

Date of this Version

10-17-2023

Citation

Clarke, J.L., Cooper, L.D., Poelchau, M.F. et al. Data sharing and ontology use among agricultural genetics, genomics, and breeding databases and resources of the Agbiodata Consortium. Database (2023) Vol. 2023: article ID baad076; DOI: https://doi.org/10.1093/database/baad076

Comments

This work is written by (a) US Government employee(s) and is in the public domain in the US.

Abstract

Over the last couple of decades, there has been a rapid growth in the number and scope of agricultural genetics, genomics and breeding databases and resources. The AgBioData Consortium (https://www.agbiodata.org/) currently represents 44 databases and resources (https://www.agbiodata.org/databases) covering model or crop plant and animal GGB data, ontologies, pathways, genetic variation and breeding platforms (referred to as ‘databases’ throughout). One of the goals of the Consortium is to facilitate FAIR (Findable, Accessible, Interoperable, and Reusable) data management and the integration of datasets which requires data sharing, along with structured vocabularies and/or ontologies. Two AgBioData working groups, focused on Data Sharing and Ontologies, respectively, conducted a Consortium-wide survey to assess the current status and future needs of the members in those areas. A total of 33 researchers responded to the survey, representing 37 databases. Results suggest that data-sharing practices by AgBioData databases are in a fairly healthy state, but it is not clear whether this is true for all metadata and data types across all databases; and that, ontology use has not substantially changed since a similar survey was conducted in 2017. Based on our evaluation of the survey results, we recommend (i) providing training for database personnel in a specific data-sharing techniques, as well as in ontology use; (ii) further study on what metadata is shared, and how well it is shared among databases; (iii) promoting an understanding of data sharing and ontologies in the stakeholder community; (iv) improving data sharing and ontologies for specific phenotypic data types and formats; and (v) lowering specific barriers to data sharing and ontology use, by identifying sustainability solutions, and the identification, promotion, or development of data standards. Combined, these improvements are likely to help AgBioData databases increase development efforts towards improved ontology use, and data sharing via programmatic means.