A Hybrid Framework for Online Execution of Linked Data Queries

Linked Data has been widely adopted over the last few years, with the size of the Linked Data cloud almost doubling every year. However, there is still no well-defined, efficient mechanism for querying such a Web of Data. We propose a framework that incorporates a set of optimizations to tackle various limitations in the state-of-the-art. The framework aims at combining the centralized query optimization capabilities of the data warehouse-based approaches with the result freshness and explorative data source discovery capabilities of link-traversal approaches. This is achieved by augmenting base-line link-traversal query execution with a set of optimization techniques. The proposed optimizations fall under two categories: metadata-based optimizations and semantics-based optimizations.