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

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.