Ongoing PhDs
Funding: MIAI Institute
Directors: Marie-Christine Rousset
The goal of this PhD is to investigate the privacy and security vulnerabilities of Semantic Web data and to propose solutions for mitigating them.
Funding: SIDES 3.0 project
Directors: Marie-Christine Rousset
co-supervisor: Fabrice Jouanot
The goal of the PhD work is to design and implement an OBDA infrastructure to support the storage, semantic enrichment and the on-demand analysis of large amounts of educational data. Ontology-based Data Access (OBDA) is a novel paradigm at the crossroad of Artificial Intelligence and Databases that has recently received an increasing interest because it enables end-users to ask their own (possibly complex) queries using a domain vocabulary they are familiar with. OBDA systems have a three-level architecture, constituted by an ontology, data sources, and mappings between the two. In the standard OBDA approach (called the virtual approach), the mappings are exploited to reformulate users queries into effective queries evaluated over the data sources. However, the state-of-the art rewriting approaches are unable to deal with complex aggregated and counting queries, which are yet at the core of data analytics.
Funding: University of Lyon 1, Samsei project
Directors: Marie-Christine Rousset
co-supervisor: Fabrice Jouanot, Loic Druette
Medical simulation is now a central thread in the fabric of medical education and as an integrative strategy 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.