Source  The landscape of agri-food data standards: From ontologies to messages
Christopher Brewster; Data Science Group, TNO, Soesterberg, The Netherlands
In EFITA WCCA 2017 Conference, Montpellier Supagro, Montpellier, France, July 2-6, 2017.
This entry provides a short overview of a recently published article  presenting some community agreements (i.e. standards including vocabularies and ontologies) serving information-, knowledge- and data management issues in agri-food (including crop research, farming, food supply chain and food retail purposes) and related sectors.
“In the present era of Big Data the demand for developing efficient information processing techniques for different applications is expanding steadily”, - Automatic Relationship Extraction from Agricultural Text for Ontology Construction.
"Access to these data can help us understand all aspects of food production: soil conditions, land use, the dynamics of the value chain and to identify gaps in data [that] can create comprehensive, accurate and cost-efficient knowledge bases to support food security", - The Horizon 2020 CAPSELLA project : Collective Awareness PlatformS for Environmentally-sound Land management.
The research reported in the  paper is part of a wider attempt [under the ICT-AGRI 2 project] at developing a strategic analysis of the standards providing support to reliable and continuous semantic access to agricultural and related data. In this frame, the article identifies overlapping standards, provides an evaluation (both objective and subjective) of the quality and utility of the standards available, as well as presents barriers for their greater integration.
According to this paper, besides the AGROVOC thesaurus, the most widely used and best known examples of standards are :
- The ISOBUS (ISO 11783-11:2011) standard for agricultural machinery data, and
- The GS1 EPCIS standard for product data encoded in barcodes and RFIDs.
The paper also briefly discusses:
- GACS [see a proposal for an integration of AGROVOC with the CABI and NAL],
- Crop Ontology : mainly used for collection of research data/ plant breeding domain,
- EDIFACT : used for data concerning the supply chain community,
- AgroRDF : used to describe farm operations,
- ISOagriNET : used for data feeds relevant to sensors, automated feeders, milking machinery and equipment in animal husbandry,
- EFSA : used to describe food samples in order to track the prevalence of biological risks, contaminants and chemical residues;
- VEST Registry (= GODAN “Map of Data Standards”) of agri-food DATA STANDARDS and Ontologies,
- AGROPORTAL : that brings together all Vocabularies and Ontologies for the agri-food domain.
With the growth of the current generation of information technology and the development of data driven innovation in the agri-food sector (see: Big Data in Smart Farming – A review), there is a fundamental need for a more joined up approach to the integration of the agrifood sector, its data streams and consequently the data standards which underpin these data flows.
Among the main barriers to greater integration of agri-food data standards, the paper mentions: (1) lack of awareness and communication, (2) lack of business cases, (3) cultural isolation and quite simple competition.
The growing demand for more detailed information about food grown sold, - both from regulators and consumers, - means that the relatively light-weight standards may need to be augmented with the kind of rich data fields found in the ontological standards.
RELATED CONTENT :
The AGROVOC thesaurus – – coordinated by FAO of the UN, and maintained by an international community of experts and institutions active in the area of agriculture and related domains – – is available as an SKOS-XL concept scheme, and is also published as a Linked Open Data (LOD) set composed of 34,000+ concepts available in up to 30 languages.
By means of LD, AGROVOC is aligned to 18 open datasets related to agriculture. The advantage of having a thesaurus like AGROVOC published as LD is that once different Knowledge Organisation Systems are linked, the resources they index are linked as well.
AGROVOC is widely used in specialized libraries as well as digital libraries (read: Applications of Thesaurus in Digital Libraries) and repositories to index content and for the purpose of text mining. It is also used as a specialized tagging resource for knowledge and content organization by FAO and other third-party stakeholders.
AGROVOC was the most cited dataset published in the dedicated track of Semantic Web Journal (SWJ) in 2016 (read: Dataset Reuse: An Analysis of References in Community Discussions, Publications and Data).
More about AGROVOC:
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