AGRIS is the International System for Agricultural Science and Technology. It is supported by a large community of data providers, partners and users. AGRIS is a database that aggregates bibliographic data, and through this core data, related content across online information systems is retrieved by taking advantage of Semantic Web capabilities. AGRIS is a global public good and its vision is to be a responsive service to its user needs by facilitating contributions and feedback regarding the AGRIS core knowledgebase, AGRIS’s future and its continuous development. Periodic AGRIS e-consultations, partner meetings and user feedback are assimilated to the development of the AGRIS application and content coverage. This paper outlines the current AGRIS technical set-up, its network of partners, data providers and users as well as how AGRIS’s responsiveness to clients’ needs inspires the continuous technical development of the application. The paper concludes by providing a use case of how the AGRIS stakeholder input and the subsequent AGRIS e-consultation results influence the development of the AGRIS application, knowledgebase and service delivery.

Abstract. The AGRIS Network is an international initiative based on a collaborative network of institutions, whose aim is to promote free access to information on science and technology in agriculture and related subjects. The paper illustrates how the Open Access (OA) and the Open Archive Initiative (OAI) models can be used within the AGRIS Network as a means of solving the problems of dissemination and exchange of agricultural research outputs. The lack of adequate information exchange possibilities between researchers in agricultural sciences and technology represents a significant weakness limiting their ability to properly address the issues of agricultural development. The OA model promotes the dissemination of research output at international, national and regional levels thus removing the restrictions placed by the traditional scientific publishing model. This paper presents the possibility to address the accessibility, availability and interoperability issues of exchanging agricultural research output.

In this article, we present a joint effort of the wheat research community, along with data and ontology experts, to develop wheat data interoperability guidelines. Interoperability is the ability of two or more systems and devices to cooperate and exchange data, and interpret that shared information. Interoperability is a growing concern to the wheat scientific community, and agriculture in general, as the need to interpret the deluge of data obtained through high-throughput technologies grows. Agreeing on common data formats, metadata, and vocabulary standards is an important step to obtain the required data interoperability level in order to add value by encouraging data sharing, and subsequently facilitate the extraction of new information from existing and new datasets. During a period of more than 18 months, the RDA Wheat Data Interoperability Working Group (WDI-WG) surveyed the wheat research community about the Discuss this article (2) CommentsWorking Group (WDI-WG) surveyed the wheat research community about the use of data standards, then discussed and selected a set of recommendations based on consensual criteria. The recommendations promote standards for data types identified by the wheat research community as the most important for the coming years: nucleotide sequence variants, genome annotations, phenotypes, germplasm data, gene expression experiments, and physical maps. For each of these data types, the guidelines recommend best practices in terms of use of data formats, metadata standards and ontologies. In addition to the best practices, the guidelines provide examples of tools and implementations that are likely to facilitate the adoption of the recommendations. To maximize the adoption of the recommendations, the WDI-WG used a community-driven approach that involved the wheat research community from the start, took into account their needs and practices, and provided them with a framework to keep the recommendations up to date. We also report this approach's potential to be generalizable to other (agricultural) domains.

AGROVOC is the multilingual thesaurus managed and published by the Food and Agriculture Organization of the United Nations (FAO). Its content is available in more than 40 languages and covers all the FAO’s areas of interest. The structural basis is a resource description framework (RDF) and simple knowledge organization system (SKOS). More than 39,000 concepts identified by a uniform resource identifier (URI) and 800,000 terms are related through a hierarchical system and aligned to knowledge organization systems. This paper aims to illustrate the recent developments in the context of AGROVOC and to present use cases where it has contributed to enhancing the interoperability of data shared by different information systems.

In this article, we present a joint effort of the wheat research community, along with data and ontology experts, to develop wheat data interoperability guidelines. Interoperability is the ability of two or more systems and devices to cooperate and exchange data, and interpret that shared information. Interoperability is a growing concern to the wheat scientific community, and agriculture in general, as the need to interpret the deluge of data obtained through high-throughput technologies grows. Agreeing on common data formats, metadata, and vocabulary standards is an important step to obtain the required data interoperability level in order to add value by encouraging data sharing, and subsequently facilitate the extraction of new information from existing and new datasets. During a period of more than 18 months, the RDA Wheat Data Interoperability Working Group (WDI-WG) surveyed the wheat research community about the use of data standards, then discussed and selected a set of recommendations based on consensual criteria. The recommendations promote standards for data types identified by the wheat research community as the most important for the coming years: nucleotide sequence variants, genome annotations, phenotypes, germplasm data, gene expression experiments, and physical maps. For each of these data types, the guidelines recommend best practices in terms of use of data formats, metadata standards and ontologies. In addition to the best practices, the guidelines provide examples of tools and implementations that are likely to facilitate the adoption of the recommendations. To maximize the adoption of the recommendations, the WDI-WG used a community-driven approach that involved the wheat research community from the start, took into account their needs and practices, and provided them with a framework to keep the recommendations up to date. We also report this approach’s potential to be generalizable to other (agricultural) domains.