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Article Dans Une Revue Artificial Intelligence in Medicine Année : 2019

OntoSIDES: Ontology-based student progress monitoring on the national evaluation system of French Medical Schools

Résumé

We introduce OntoSIDES, the core of an ontology-based learning management system in Medicine, in which the educational content, the traces of students’ activities and the correction of exams are linked and related to items of an official reference program in a unified RDF data model. OntoSIDES is an RDF knowledge base comprised of a lightweight domain ontology that serves as a pivot high-level vocabulary of the query interface with users, and of a dataset made of factual statements relating individual entities to classes and properties of the ontology. Thanks to an automatic mapping-based data materialization and rule-based data saturation, OntoSIDES contains around 8 millions triples to date, and provides an integrated access to useful information for student progress monitoring, using a powerful query language (namely SPARQL) allowing users to express their specific needs of data exploration and analysis. Since we do not expect end-users to master the raw syntax of SPARQL and to express directly complex queries in SPARQL, we have designed a set of parametrized queries that users can instantiate through a user-friendly interface.
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Dates et versions

hal-02089318 , version 1 (17-04-2019)

Identifiants

Citer

Olivier Palombi, Fabrice Jouanot, Nafissetou Nziengam, Behrooz Omidvar-Tehrani, Marie-Christine Rousset, et al.. OntoSIDES: Ontology-based student progress monitoring on the national evaluation system of French Medical Schools. Artificial Intelligence in Medicine, 2019, 96, pp.59-67. ⟨10.1016/j.artmed.2019.03.006⟩. ⟨hal-02089318⟩
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