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 micro-organisms 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 \([MS]^2O\), as a common and standardized vocabulary. Users’ requirements were defined through competency questions and the ontology was validated against these competency questions. \([MS]^2O\) 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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We are very grateful for the valuable inputs from all the domain experts partners involved in CellExtraDry French national project.
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Dibie, J., Dervaux, S., Doriot, E., Ibanescu, L., Pénicaud, C. (2016). \([MS]^2O\) – A Multi-scale and Multi-step Ontology for Transformation Processes: Application to Micro-Organisms. In: Haemmerlé, O., Stapleton, G., Faron Zucker, C. (eds) Graph-Based Representation and Reasoning. ICCS 2016. Lecture Notes in Computer Science(), vol 9717. Springer, Cham. https://doi.org/10.1007/978-3-319-40985-6_13
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