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SAFE: SPARQL Federation over RDF Data Cubes with Access Control

Background

Several query federation engines have been proposed for accessing public Linked Open Data sources. However, in many domains, resources are sensitive and access to these resources is tightly controlled by stakeholders; consequently, privacy is a major concern when federating queries over such datasets. In this paper, we present SAFE, a SPARQL query federation engine that enables decentralised, access to clinical information represented as RDF data cubes with access control. As SAFE is index-based approach, so we also present SAFE data summaries generation algorithm.

Results

We validate the performance of the system with experiments over real-world datasets provided by three clinical organisations as well as legacy Linked Datasets. In our evaluation, we show that SAFE enables granular graph-level access control over distributed clinical RDF data cubes and efficiently reduces the query execution time when compared with general-purpose SPARQL query federation engine. In this extended article we did a comprehensive evaluation of SAFE and its index generation algorithm.

Conclusions

We present SAFE: a query federation engine that enables policy-based access to sensitive statistical datasets represented as RDF data cubes with better performance in terms of source selection and query execution times as compared to other state-of-the-art federation engines, both on clinical and legacy linked datasets.