In the context of Research Data, the use of vocabularies play a key role in managing, sharing and publishing data. Vocabularies enhance the quality of the interoperability and effectiveness of data exchange, thus facilitating the re-usage of data by others and in the process adding value to the local researcher.

This section focuses on vocabularies, their benefits and current situation in the context of Wheat Research Data. The aim is to provide a tool to support researchers in the selection of vocabularies to adopt according to the Wheat Data Interoperability Guidelines.

What type of vocabularies exist in the context of the Wheat Initiative?

There are different types of vocabularies like ontologies, thesauri, classification systems, controlled lists, syntax encoding standards, authority data, controlled vocabularies, taxonomies, glossaries, etc.

Why are vocabularies important for the Wheat Initiative?

The Wheat Initiative  aims to encourage and support the development of a vibrant global public-private research community sharing resources, capabilities, data and ideas to improve wheat productivity, quality and sustainable production around the world. Data sharing and data publishing play a critical role, and it is through the use of common tools, standards and vocabularies that this goal can be achieved.

An example of applications that use vocabularies is AGRIS (FAO). AGRIS (International System for Agricultural Science and Technology) is a global public database providing access to bibliographic information on agricultural science and technology, which includes Wheat bibliographic information. In addition to this, the AGRIS website combines data from multiple sources using Linked Open Data methodology in order to provide as much information as possible about a given bibliographic reference. All these data are thus accessible and organized through a simple user interface. All this was made possible by the use of vocabularies to describe data and by the links that exist between the different vocabularies. The data are reused in a different way from which they were first published contributing to new breakthroughs.

Example of a Wheat bibliographic reference in AGRIS.

What benefits can vocabularies bring to your daily work as a researcher?

They are many, including:

  • research visibility
  • research usage
  • research uptake
  • research applications
  • research impact
  • research productivity
  • research progress
  • research funding
  • research manageability
  • research accessibility
  • research efficiency
  • research interoperability


Why are the Semantic Web Technologies relevant for the Wheat Initiative?

Semantic Web technologies support the research community to enhance re-use and access to data. Even though currently these tools and standards are not widely used in the context of the Wheat Initiative, a first step is to recommend and encourage the use of common vocabularies.

What are currently the most used and relevant vocabularies in the context of Wheat Initiative?

From December to 2014 to January 2015 the editorial team conducted a survey “Towards a Comprehensive Overview of Ontologies and Vocabularies for Research on Wheat”. The objective was to collect information about the visibility, interoperability, domain, content and other technical aspects of relevant ontologies and vocabularies. As a result, in February 2015 a report (link) was published, and also a list of vocabularies listed as follows:

  2. Biorefinery
  3. CAB Thesaurus (CABT)
  4. Cell Ontology (CL)
  5. Chemical Entities of Biological Interest  (ChEBI)
  6. Crop Ontology (CO)
  7. Crop Research Ontology – part of Crop Ontology (CO_715)
  8. Environment Ontology (ENVO)
  9. Experimental Factor Ontology (EFO)
  10. Feature Annotation Location Description Ontology (FALDO)
  11. NAL Thesaurus (NALT)
  12. Phenotype And Trait Ontology (PATO)
  13. Plant Experimental Conditions Ontology (Plant Environment Ontology, EO, may be changing to PECO)
  14. Plant Ontology (PO)
  15. Plant Trait Ontology (TO)
  16. Population and Community Ontology (PCO)
  17. Protein Ontology (PRO)
  18. Sequence Ontology (SO)
  19. Variation Ontology (VariO)
  20. Wheat Ontology INRA (WIPO)
  21. Wheat Anatomy and Development Ontology – part of Crop Ontology (CO_121)
  22. Wheat Trait Ontology: Embedded in Crop Ontology (CO_321)
  23. Wheat Phenotype (phenotypes and traits in Wheat)

See also the wheat related ontologies repository in Agroportal