KNOWLEDGE-BASED MULTIMODAL DATA REPRESENTATION AND QUERYING
Julien Seinturier, Élisabeth Murisasco, Emmanuel Bruno · 2011
This paper focuses on the representation and querying of knowledge-based multimodal data. Our work stands in the multidisciplinary project OTIM (Tools for Multimodal Annotation) dedicated to the development of tools for multimodal annotation of french conversational data. OTIM aims at encoding and manipulating annotations from all the linguistic domains in an unique framework. Defining a data model suited to the concurrent representation of these annotations involve to be able to analyze and to query them in order to help to determinate correlations between the linguistic domains. Linguists commonly use Typed Feature Structures (TFS) to provide an uniform view of multimodal annotations but such a representation cannot be used within an applicative framework. Moreover TFS expressibility is limited to hierarchical and constituency relations and does not suit to any linguistic domain that needs for example to represent temporal relations. To overcome these limits, we propose an ontological approach based on Description logics (DL) for the description of linguistic knowledge and we provide an applicative framework based on OWL DL (Ontology Web Language) and the query language SPARQL.