Interview
"Big data in agriculture presents an opportunity to find new ways of ending hunger and poverty"
Interview with Brian King, Coordinator of the CGIAR Platform for Big Data in Agriculture from CGIAR Platform for Big Data in Agriculture
Мы в действии
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NewsGood news for ASFA and AGROVOC users
...as ASFA and AGROVOC work together to share some infrastructure and enrich the controlled vocabularies ...
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NewsThe release for AGROVOC May 2019 is out!
FAO AGROVOC team is pleased to announce the release for AGROVOC release for May 2019. The May 2019 release brings AGROVOC to a total of 36,212 concepts up from 36,196 concepts in April 2019. ...
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AGROVOC April 2019 release is out. With 36,169 concepts!
FAO AGROVOC team takes this opportunity to inform you about the FAO AGROVOC April 2019 release. ...
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Blog PostFAIR Principles & Digital Objects: The role of METADATA
The advancement of digital science thrives on the timely sharing and accessibility of digital data, and every day research activities provide unlimited amounts of data that could have an impact on...
Blog PostOpen Source initiatives help harness the power of Data
Open source designates a broader set of values of 'the open source way'... "Open source projects, products, or initiatives embrace and celebrate principles of open exchange,...
Blog PostRESPONSIBLE DATA GUIDELINES: Managing Privacy and Personally Identifiable Information
“Data can be either useful or perfectly anonymous, but never both...” Paul Ohm – UCLA Law review 2010 57 UCLA L. Rev. 1701). ...
Blog PostAgBioData ensures Standards and Best Practices for acquisition, display and retrieval of Genomic, Genetic & Breeding Data
Given that agricultural research depends basically on data and analysis, governmental agencies, publishers and science funders now require data management plans for publicly funded...
Blog PostMETADATA for Description, Discovery & Contextualisation. Check RDA METADATA Catalog
Metadata is a part of the global conversation and is already recognized as a necessity for interoperability, discovery and contextualisation. Given that metadata is essential for data science...