AgBioData consortium recommendations for sustainable genomics and genetics databases for agriculture

Harper, L., Campbell, J., Cannon, E. K. S., Jung, S., Poelchau, M., Walls, R., Andorf, C., Arnaud, E., Berardini, T. Z., Birkett, C., Cannon, S., Carson, J., Condon, B., Cooper, L., Dunn, N., Elsik, C. G., Farmer, A., Ficklin, S. P., 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, C. J., Munoz-Torres, M. C., Naithani, S., Nelson, R., Nesdill, D., Park, C., Reecy, J., Reiser, L., Sanderson, L. A., Sen, T. Z., Staton, M., Subramaniam, S., Tello-Ruiz, M. K., Unda, V., Unni, D., Wang, L., Ware, D., Wegrzyn, J., Williams, J., Woodhouse, M., Yu, J., Main, D. (2018) AgBioData consortium recommendations for sustainable genomics and genetics databases for agriculture. Database (Oxford), 2018. ISSN 1758-0463

URL: https://www.ncbi.nlm.nih.gov/pubmed/30239679
DOI: 10.1093/database/bay088

Abstract

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.

Item Type: Paper
Subjects: bioinformatics
bioinformatics > genomics and proteomics > databases
CSHL Authors:
Communities: CSHL labs > Ware lab
Depositing User: Matthew Dunn
Date Deposited: 27 Sep 2018 14:25
Last Modified: 18 Oct 2018 13:54
PMCID: PMC6146126
Related URLs:
URI: http://repository.cshl.edu/id/eprint/37221

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