Our research is organized along two main themes:
- We seek to exploit parallel data processing infrastructures for highly scalable, parallel Big Data storage and processing tools.Topic we study in this area include: highly efficient query processing in polystores, efficient query answering in the presence of ontologies, and algorithms for scalable, fast data analytics.
- To enhance the usefulness of Big Data, we study new paradigms of user interaction with Big Data, based on exploratory querying, analytics for semantic graphs, and intuitive query tools over highly heterogeneous data.
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We collaborate with the INRIA teams: ILDA@Saclay, TYREX@Grenoble, Graphik and Zenith@Montpellier, and also with colleagues from U. Rennes 1, Ecole Polytechnique, Télécom ParisTech, LIMSI (U. Paris Sud), CentraleSupéléc, and INSA Lyon. International partners include UC San Diego, AT&T Research, U. Dresden, U. Bolzano. Current industrial partners include SemSoft, Business & Decision and Le Monde.
The INRIA predecessor of CEDAR is the OAK project-team, joint between INRIA and Université de Paris Sud (2012-2015).