International audienceThis paper describes an ontology for modeling any food processingchain. It is intended for data and knowledge integration andsharing. The proposed ontology (Onto-FP) is built based on four mainconcepts: Product, Operation, Attribute and Observation. This ontologyis able to represent food product transformations as well as temporal sequenceof food processes. The Onto-FP can be easy integrated to otherdomains due to its consistencies with DOLCE ontology. We detail anapplication in the domain of winemaking and prove that it can be easyqueried to answer questions related to data classication, food processitineraries and incomplete data identication
The key discovery problem has been recently investigated for symbolical RDF data and tested on large datasets such as DBpedia and YAGO. The advantage of such methods is that they allow the automatic extraction of combinations of properties that uniquely identify every resource in a dataset (i.e., ontological rules). However, none of the existing approaches is able to treat real world numerical data. In this paper we propose a novel approach that allows to handle numerical RDF datasets for key discovery. We test the significance of our approach on the context of an oenological application and consider a wine dataset that represents the different chemical based flavourings. Discovering keys in this context contributes in the investigation of complementary flavors that allow to distinguish various wine sorts amongst themselves.
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