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	    2019</a> | <a href="http://www.inria.fr/en/teams/cedar">Presentation of the Project-Team CEDAR</a> | <a href="https://team.inria.fr/cedar/">CEDAR Web Site
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        <h2>Section: 
      Research Program</h2>
        <h3 class="titre3">Multi-Model Querying</h3>
        <p>As the world's affairs get increasingly more digital, a large and varied set of data sources becomes available: they are either structured databases, such as government-gathered data (demographics, economics, taxes, elections, ...), legal records, stock quotes for specific companies, un-structured or semi-structured, including in particular graph data, sometimes endowed with semantics (see e.g. the Linked Open Data cloud). Modern data management applications, such as data journalism, are eager to combine in innovative ways both static and dynamic information coming from structured, semi-structured, and un-structured databases and social feeds. However, current content management tools for this task are not suited for the task, in particular when they require a lenghy rigid cycle of data integration and consolidation in a warehouse. Thus, we see a need for flexible tools allowing to interconnect various kinds of data sources and to query them together.</p>
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