A datahub for semantic interoperability in data-driven integrated greenhouse systems
In this paper, we deal with the challenge of semantic alignment of different data sources in the horticultural sector. In this sector, greenhouses are used to grow vegetables and plants and the main goal for a greenhouse grower is to control the climate such that crop is optimally cultivated against the lowest cost. Combining available data sources to extract trends and patterns via data analysis is important to better support growing decisions. We developed a Common Greenhouse Ontology (CGO) and used it in Datahub to make data sources accessible via RDF and a SPARQL interface on top of an Apache Jena Fuseki triplestore. We applied the Datahub in a trial use case in which three data sources where made accessible for a linear regression component that derived patterns between nutrients used and crop growth. We learned that the use of a common ontology very well supports the aligned use of data in analysis and thus better decision support.
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Buildings and Infrastructures
Efita Conference 27-29 June 2019, Rhodes Island, Griekenland