Publication

SAFE: SPARQL federation over RDF data cubes with access control

Khan, Yasar
Saleem, Muhammad
Mehdi, Muntazir
Hogan, Aidan
Mehmood, Qaiser
Rebholz-Schuhmann, Dietrich
Sahay, Ratnesh
Citation
Khan, Yasar, Saleem, Muhammad, Mehdi, Muntazir, Hogan, Aidan, Mehmood, Qaiser, Rebholz-Schuhmann, Dietrich, & Sahay, Ratnesh. (2017). SAFE: SPARQL Federation over RDF Data Cubes with Access Control. Journal of Biomedical Semantics, 8(1), 5. doi: 10.1186/s13326-017-0112-6
Abstract
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 the Healthcare and Life Sciences (HCLS) domain real-world datasets contain sensitive statistical information: strict ownership is granted to individuals working in hospitals, research labs, clinical trial organisers, etc. Therefore, the legal and ethical concerns on (i) preserving the anonymity of patients (or clinical subjects); and (ii) respecting data ownership through access control; are key challenges faced by the data analytics community working within the HCLS domain. Likewise statistical data play a key role in the domain, where the RDF Data Cube Vocabulary has been proposed as a standard format to enable the exchange of such data. However, to the best of our knowledge, no existing approach has looked to optimise federated queries over such statistical data.
Publisher
BioMed Central
Publisher DOI
10.1186/s13326-017-0112-6
Rights
Attribution-NonCommercial-NoDerivs 3.0 Ireland