Managing Linked Data in the Cloud

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The research proposal objectives are to significantly improve cloud-based data management techniques to facilitate the publication and consumption of structured and semi-structured data on the Web, leveraging the capabilities of Linked Data. Linked Data uses a graph data model, encoded in the Resource Description Format (RDF), where real world entities are identified via web addresses. We will focus on three initial aspects; (1) creating novel data and metadata exploration approaches and tools that will significantly improve upon existing capabilities to explore and to understand (at web-scale) the data and metadata that is used within and across linked datasets on the Web, (2) introducing a flexible, linked data based framework to support privacy, transparency, and accountability that leverages cloud based Big Data analytics techniques that are suitable to log queries in our setting (such as accountability and compliance queries that detect privacy violations as well as the parties involved), and (3) developing autonomic and self-managing techniques appropriate to applications that consume linked data on the cloud, by formalizing new problems and developing experimentally validated solutions that are tailored to the cloud environment.