[MS]²O: A Multi-scale and Multi-step Ontology for Transformation Processes: Application to Micro-Organisms

Abstract : This paper focuses on the knowledge representation for an interdisciplinary project concerning transformation processes in food science. The use case concerns the production of stabilized microorganisms performed at INRA (French National Institute for Agricultural Research). Experimental observations are available for some inputs of the production processes, at different steps and at a certain scale. Available data sets are described using different vocabularies and are stored in different formats. Therefore there is a need to define an ontology, called [M S] 2 O, as a common and standardized vocabulary. Users' requirements were defined through competency questions and the ontology was validated against these competency questions. [M S] 2 O ontology aims to play a key role as the representation layer of the querying and simulation systems of the project. This leads to the possibility of comparing different production scenarios and suggesting improvements.
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Juliette Dibie, Stéphane Dervaux, Estelle Doriot, Liliana Ibanescu, Caroline Pénicaud. [MS]²O: A Multi-scale and Multi-step Ontology for Transformation Processes: Application to Micro-Organisms. 22nd International Conference on Conceptual Structures, Jul 2016, Annecy, France. pp.163-176, ⟨10.1007/978-3-319-40985-6_13⟩. ⟨hal-01357749⟩

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