Applying ontologies in the dairy farming domain for big data analysis
conference paper
In the Dutch SmartDairyFarming project, main dairy industry organizations like FrieslandCampina, AgriFirm and CRV work together on better decision support for the dairy farmer on daily questions around feeding, insemination, calving and milk production processes. This paper is concerned with the inherent semantic interoperability problem in decision support information in a variety of big data sources containing static and dynamic sensor data of individual cows. Semantic alignment is achieved using ontologies and linked data mechanisms on a large amount of sensor data, such as grazing activity, feed intake, weight, temperature and milk production of individual cows at 7 dairy farms in The Netherlands. A Common Dairy Ontology (CDO) and a specific measurement ontology have been developed and used to transform 12GB of yearly sensor data into 350GB of RDF triples, made accessible via a SPARQL interface on the Apache Jena Fuseki triplestore. A few example applications have been developed to show how the CDO can be used for decision support and historic analysis. The performance of our linked data semantic solution is acceptable for analysis queries on large sets of data. Without optimization of queries the time for answering queries ranged from a few seconds to a couple of minutes. © 2016, CEUR-WS. All rights reserved.
Topics
TNO Identifier
745912
ISSN
16130073
Publisher
CEUR-WS
Source title
Joint 3rd Stream Reasoning, SR 2016 and the 1st Semantic Web Technologies for the Internet of Things, SWIT 2016 Workshops. 17 October 2016 through 18 October 2016
Editor(s)
Krotzsch, M.
Maleshkova, M.
Verborgh, R.
Facca, F.M.
Della Valle, E.
Eiter, T.
Dell'Aglio, D.
Mrissa, M.
Maleshkova, M.
Verborgh, R.
Facca, F.M.
Della Valle, E.
Eiter, T.
Dell'Aglio, D.
Mrissa, M.
Pages
91-100
Files
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