Institute for Web Science and Technologies · Universität Koblenz - Landau
Institute WeST

An embedded, ontology based autocompletion for SPARQL

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SPARQL is the de-facto query language for RDF graphs. However, using SPARQL can be a tedious process because it requries knowledge of the data. A user must know of the relations between various graph nodes before he can actually write a sensible query. A user must therefore either study the data or schematic information about the data (e.g., an ontology) beforehand. An autocompletion for queries can alleviate these issues. Similar to [1], this thesis aims at providing an autocompletion for SPARQL queries.
While the autocompletion provided by [1] however works strictly on the data, this thesis aims at creating an autocompletion that can also work on an ontology without looking at the data. Such an ontology, e.g. the OWL movie ontology ( provide information about available relations and concepts in the data. It also provides information about disjoint concepts or relations,
allowing for rejecting unsatisfiable queries. Lastly, this autocompletion should be integrated into a programming language IDE, allowing for using SPARQL directly while programming. The thesis should target IntelliJ language injections

In summary, the goal of the thesis is the creation of a IntelliJ language injection for SPARQL code that provides an autocompletion mechanism. The autocompletion should be able to work with either an ontology, specifying the available relations and concepts or directly with a triplestore that can process SPARQL queries.


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