Enabling Semantic Web for Precision Agriculture: a showcase of agriOpenLink Project

This paper describes the agriOpenLink approach towards triplification of the production data generated by heterogeneous agricultural equipment, for their easy integration and querying within a common information context of various decision support applications. The presented approach has been developed within the running project agriOpenLink, which aims at improving agricultural production processes. Triplification is performed by equipment-specific model adapters (plugins), which translate the equipment data into RDF triples. The plugins are realized by means of semantic REST services, and triplification is a result of a workflow orchestrated "on-demand" by chaining services of appropriate data sources. In the project, we have also conceptualized, and are currently implementing a platform and tools that facilitate easy plugin development and deployment. Dealing with the problem of creating a common information context, the project designed a domain ontology taking into account existing work, experimented with triplification of existing domain knowledge, and proposed an approach for the ontology maintenance. The agriOpenLink platform is being tested and demonstrated in the precision irrigation use case and the precision dairy farming use case.