OntoSamsei: Interactive ontology modeling for supporting simulation-based training in Medicine
| Autor: | Baghernezhad-Tabasi, Shadi, Rousset, Marie-Christine, Jouanot, Fabrice, Druette, Loïc, Meurger, Céline |
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| Přispěvatelé: | ScaLable Information Discovery and Exploitation [Grenoble] (SLIDE ), Laboratoire d'Informatique de Grenoble (LIG), Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), SAMSEI, Université de Lyon, ANR-16-DUNE-0002,SIDES 3.0,Système Intelligent d'Enseignement en Santé(2016), ANR-11-IDFI-0034,SAMSEI,Stratégies d'Apprentissage des Métiers de Santé en Environnement Immersif(2011) |
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: | |
| Zdroj: | 11th International Conference on Knowledge Engineering and Ontology Development, Doctoral Consortium 11th International Conference on Knowledge Engineering and Ontology Development, Doctoral Consortium, Sep 2019, Vienne, Austria |
| Popis: | International audience; Medical simulation is now a central thread in the fabric of medical education and as an integrative strat- egy to bridge theory to practice has been identified as a need in medical education in the future. Due to the recency of simulation-based training in medicine and the scarcity of available documentation and modelisation, current information retrieval and data mining approaches are not effective in understanding the context of simulation-based training content. The overall objectives of our research are to develop an interactive and incremental ontology modeling approach in order to model ill-defined domains such as some sub-domains related to pedagogy. We propose building an ontology for simulation-based medical education domain, called ONTOSAMSEI. The main contribution includes a new tool to automatically generate pre-filled forms guided by the ontology in order to share the acquired knowledge with the domain experts, and collect new information from them to enrich the ontology. |
| Databáze: | OpenAIRE |
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