With the increasing adoption of NoSQL data base systems like MongoDB or CouchDB more and more applications store structured data according to a non-relational, document oriented model. Exposing this structured data as Linked Data is currently inhibited by a lack of standards as well as tools and requires the implementation of custom solutions. While recent efforts aim at expressing transformations of such data models into RDF in a standardized manner, there is a lack of approaches which facilitate SPARQL execution over mapped non-relational data sources. With SparqlMap-M we show how dynamic SPARQL access to non-relational data can be achieved. SparqlMap-M is an extension to our SPARQL-to-SQL rewriter SparqlMap that performs a (partial) transformation of SPARQL queries by using a relational abstraction over a document store. Further, duplicate data in the document store is used to reduce the number of joins and custom optimiza-tions are introduced. Our showcase scenario employs the Berlin SPARQL Benchmark (BSBM) with different adap-tions to a document data model. We use this scenario to demonstrate the viability of our approach and compare it to different MongoDB setups and native SQL.
Jörg Unbehauen started his career in computer sciences by studying and working at a large telecommunications provider, where his work revolved around data integration. Seeking new challenges, he continued studying in Lüneburg and Wolverhampton and is currently pursuing his Ph.D. in Leipzig. His work at the AKSW research group focuses on SPARQL query translations and transformations in different settings.