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[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 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[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[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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https://hal.inrae.fr/hal-02801472
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Submitted on : Friday, June 5, 2020 - 8:54:45 PM
Last modification on : Friday, August 6, 2021 - 3:24:03 PM

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Juliette Dibie, Stephane Dervaux, Estelle Doriot, Liliana Ibanescu, Caroline Pénicaud. [MS]^2O – A Multi-scale and Multi-step Ontology for Transformation Processes: Application to Micro-Organisms. Graph-Based Representation and Reasoning : 22nd International Conference on Conceptual Structures, ICCS 2016, Annecy, France, July 5-7, 2016, Proceedings, 9717, Springer International Publishing, 2016, Lecture Notes in Computer Science, 978-3-319-40984-9. ⟨10.1007/978-3-319-40985-6_13⟩. ⟨hal-02801472⟩

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