Given that agricultural research depends basically on data and analysis, governmental agencies, publishers and science funders now require data management plans for publicly funded experiments. This, along with the sheer volume of agricultural biological data being produced today makes good data management essential.
In 2015, AgBioData - a consortium of agricultural biological databases - was formed to identify common goals relating to data set acquisition, display, user retrieval and manipulation; data (storage and sharing), software and hardware standards, and database best practices that would have the most efficient impact on agriculture (research) agendas, through more efficient database solutions.
THE OBJECTIVES OF AGBIODATA INCLUDE:
1.) to coordinate with external (to-date, 32) groups/data providers including Agbase, AgroPortal, CyVerse and scientific journals to develop standards for efficient data flow among data generators and databases,
2.) to encourage authentic, detailed, accurate and explicit communication and sharing among databases of agricultural data in order to identify common problems and collaborate on solving them, as well as to avoid duplication of work and support small research groups,
3.) to promote AgBioData database products referenced into the FAIRsharing registry <https://fairsharing.org/collection/AgBioData> in order to enhance support for more reliable insights into findable, accessible, interoperable and reusable (FAIR) datasets.
As a step toward these goals, the AgriBioData Team presents the current state of biocuration, ontologies, metadata and persistence, database platforms, programmatic (machine) access to data, communication and sustainability with regard to data curation:
The purpose of this paper is 3-fold:
1.) to document the current challenges and opportunities of GGB (genomic, genetic and breeding) databases and online resources regarding the collection, integration and provision of data in a standardized way;
2.) to outline a set of standards and best practices for GGB databases and their curators;
3.) to inform policy and decision makers about the growing importance of scientific data curation and management to the research community.
The publication is divided into seven sections and each section contains an (i) Overview, (ii) Challenges and (iii) Recommendations.
- Looking for Agricultural Science and Technology Data & Information? Discover FAO AGRIS (International Information System for the Agricultural Science and Technology) - a free of charge service that provides access and visibility to bibliographic data on research papers, reports, multimedia material, grey literature and other content types in agricultural and related sciences
- Get Full-Text content via AGORA (Access to Global Online Research in Agriculture) and other Research4Life programmes enhanced with new Country-Specific Search in Summon!
- AGROVOC Thesaurus : a BACKBONE to INTEGRATE & DISCOVER interoperable AGRICULTURAL-related DATA
Thousands of community-developed standards are available (across all disciplines)… but, do we use them? Discover VEST/AgroPortal AgriSemantics map of Data Standards, FAIRSharing, RDA IGAD ‘Landscaping the Use of Semantics to Enhance the Interoperability of Agricultural Data' … and keep coping with FAIRifying challenge!
FAOSTAT provides free access to food and agriculture data for over 245 countries and territories and covers all FAO regional groupingsfrom 1961 to the most recent year available
CGIAR Platform for Big Data in Agriculture : to Organize, Convene, Inspire
Key data categories for agriculture, datasets and data standards (Open Data Charter)
- Check Wheat Iniative: MIAPPE version 1.1, - an updated specification of the Minimal Information About a Plant Phenotyping Experiment
- Developing Data Interoperability using standards: A Wheat Community use case. The Wheat Data Interoperability Working Group (WG) - one of the WGs of the Research Data Alliance Agriculture Data Interoperability Interest Group -has developed Wheat Data Interoperability Recommendations with standards and databases referenced into the FAIRsharing website
- Free E-learning Module: Finding Research Data
How should Findable, Accessible, Interoperable and Reusable (FAIR) data work in practice? (Springer Nature post)
Unlocking the Potential of BLOCKCHAIN for AGRICULTURE (recorded GODAN webinar)
DATA-DRIVEN AGRICULTURE (Recorded Webinars; GFAR / CTA / GODAN)