Privacy-Preserving WebID Analytics on the Decentralized Policy-Aware Social Web

We address the research challenges of privacy-preserving Web ID analytics on the decentralized Social Web. We first argue why we should use open and decentralized control but not closed and centralized control of personal data management. Then, we present a policy-aware architecture, where a data owner hand-picks a trusted data controller to mask his/her personally identifiable information (PII) and other sensitive social relationships of the Web ID so only anonymous RDF(S) linked datasets are available for analytics. Moreover, we advocate using a R and Hadoop integration paradigm, called RHadoop, for effective hybrid Web ID analytics of large-scale social network linked datasets. Finally, we propose various types of semantics-enabled policies to call for the RHadoop hybrid Web ID analytics and further balance data utility and protection on the privacy-aware Social Web.