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  • The Inria's Research Teams produce an annual Activity Report presenting their activities and their results of the year. These reports include the team members, the scientific program, the software developed by the team and the new results of the year. The report also describes the grants, contracts and the activities of dissemination and teaching. Finally, the report gives the list of publications of the year.

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Section: Overall Objectives


The following three paragraphs summarize our main research objectives.

Querying Heterogeneous Linked Data

We will develop new kinds of schema mappings for semi-structured datasets in hybrid formats including graph databases, RDF collections, and relational databases. These induce recursive queries on linked data collections for which we will investigate evaluation algorithms, containment problems, and concrete applications.

Managing Dynamic Linked Data

In order to manage dynamic linked data collections and workflows, we will develop distributed data-centric programming languages with streams and parallelism, based on novel algorithms for incremental query answering, study the propagation of updates of dynamic data through schema mappings, and investigate static analysis methods for linked data workflows.

Linking Data Graphs

Finally, we will develop symbolic machine learning algorithms, for inferring queries and mappings between linked data collections in various graphs formats from annotated examples.