|Title||AgBioData consortium recommendations for sustainable genomics and genetics databases for agriculture.|
|Publication Type||Journal Article|
|Year of Publication||2018|
|Authors||Harper, L, Campbell, J, Cannon, EKS, Jung, S, Poelchau, M, Walls, R, Andorf, C, Arnaud, E, Berardini, TZ, Birkett, C, Cannon, S, Carson, J, Condon, B, Cooper, L, Dunn, N, Elsik, CG, Farmer, A, Ficklin, SP, Grant, D, Grau, E, Herndon, N, Hu, Z-L, Humann, J, Jaiswal, P, Jonquet, C, Laporte, M-A, Larmande, P, Lazo, G, McCarthy, F, Menda, N, Mungall, CJ, Munoz-Torres, MC, Naithani, S, Nelson, R, Nesdill, D, Park, C, Reecy, J, Reiser, L, Sanderson, L-A, Sen, TZ, Staton, M, Subramaniam, S, Tello-Ruiz, MKarey, Unda, V, Unni, D, Wang, L, Ware, D, Wegrzyn, J, Williams, J, Woodhouse, M, Yu, J, Main, D|
|Journal||Database : the journal of biological databases and curation|
|Date Published||2018 01 01|
|Keywords||Agriculture, Breeding, Databases, Gene Ontology, Genetic, Genomics, Metadata, Surveys and Questionnaires|
The future of agricultural research depends on data. The sheer volume of agricultural biological data being produced today makes excellent data management essential. Governmental agencies, publishers and science funders require data management plans for publicly funded research. Furthermore, the value of data increases exponentially when they are properly stored, described, integrated and shared, so that they can be easily utilized in future analyses. AgBioData (https://www.agbiodata.org) is a consortium of people working at agricultural biological databases, data archives and knowledgbases who strive to identify common issues in database development, curation and management, with the goal of creating database products that are more Findable, Accessible, Interoperable and Reusable. We strive to promote authentic, detailed, accurate and explicit communication between all parties involved in scientific data. As a step toward this goal, we present the current state of biocuration, ontologies, metadata and persistence, database platforms, programmatic (machine) access to data, communication and sustainability with regard to data curation. Each section describes challenges and opportunities for these topics, along with recommendations and best practices.