FAO PROJECTS

  • Focus on AGRIS multilingual search - Multilingual search is an advanced feature that allows users to query the AGRIS database in their own native language, retrieving also results in different languages. This article explains the AGRIS multilingual search to avoid confusion about its usage and to highlight its strength.

  • SemaGrow Recommender System - SemaGrow Recommender System is a piece of software - entirely based on JAVA - that computes meaningful combinations between some datasets federated by SemaGrow, and generates a new triplestore: the "Recommender Database". Recommender System was funded by SemaGrow FP7 EU Project. It computes meaningful combinations between two or more datasets federated by SemaGrow: the computation of combinations is based on the matching of AGROVOC URIs between datasets.

  • INTERVIEW - Friends of Agro-Know

  • AgroTagger - a Java application for web documents indexing, creating RDF triples that link a web URL to some URIs of a SKOS thesaurus. This application can be used together with a web crawler: the crawler discovers URLs, the AgroTagger assigns AGROVOC URIs to those URLs. In addition to that, titles and descriptions of Web resources can be extracted.

  • INTERVIEW - AGRIS 2.0: meeting the global agricultural information need

  • OPENAGRIS - A linked open data application that aims to be the hub of agrigultural information




agInfra

http://aginfra.eu/en/the-project/description

The Vision of agINFRA is the following: “To develop an infrastructure for scientific agricultural data and to improve service deployment for data by transferring scientific and technological results from the agricultural field into real outcomes. Moreover agINFRA is proposing to create a high interoperability between agricultural and other data resources”.



SemaGrow

http://www.semagrow.eu/

The Vision of SemaGrow is the following: “SemaGrow envisages to develop the scalable, efficient, and robust data services needed to take full advantage of the data-intesive and inter-disciplinary Science of 2020 and to re-shape the way that data analysis techniques are applied to the heterogeneous data cloud.”.