Semantic modelling information systems, such as a those required for the development of Space Systems, may results in large conceptual models, involving hundreds or thousands of fact types, of business rules. Moreover, these models need to satisfy semantic interoperability requirements, due to the integration of many (potentially very large) conceptual models. Ensuring the overall quality and integrity of each model (global and locals) and of the Space System Ontology (i.e. the result of integrating several semantic models for ensuing the interoperability at semantic level) is the task of a semantic-based reasoner.
Within this activity we have assessed positively the feasibility to develop a semantic reasoner for FAMOUS and demonstrated its adequacy to support the assessment of the quality of conceptual models produced with FAMOUS, in its current state, i.e. reusing NORMA.
A first version of the semantic reasoner, called ORMiE, has been developed and integrated to the professional version of NORMA. ORMiE is deployed as an extension to Microsoft Visual Studio 2019.
ORMiE (ORM inference Engine) is an extension of NORMA and NORMA Pro, which enable ORM fact-based conceptual modelling in Microsoft Visual Studio 2019. ORMiE activates automated reasoning over ORM models (including derivation rules) providing an interface where mistakes, redundancies or more in general new inferred constraints are shown.