The Resource Description Framework (RDF) represents a main ingredient and data
representation format for Linked Data and the Semantic Web. It supports a generic graph …

Distributed SPARQL engines promise to support very large RDF datasets by utilizing shared-
nothing computer clusters. Some are based on distributed frameworks such as MapReduce; …

RDF has become very popular for semantic data publishing due to its flexible and universal
graph-like data model. Yet, the ever-increasing size of RDF data collections makes it more …

We study the problem of finding and monitoring fixed-size subgraphs in a continually
changing large-scale graph. We present the first approach that (i) performs worst-case …

Abstract The Resource Description Framework (RDF) pioneered by the W3C is increasingly
being adopted to model data in a variety of scenarios, in particular data to be published or …

Many public knowledge bases are represented and stored as RDF graphs, where users can
issue structured queries on such graphs using SPARQL. With massive queries over large …

RDF is increasingly being used to encode data for the semantic web and data exchange.
There have been a large number of works that address RDF data management following …

The Resource Description Framework (RDF) and SPARQL query language are gaining
wide popularity and acceptance. In this paper, we present DREAM, a distributed and …

We propose techniques for processing SPARQL queries over a large RDF graph in a
distributed environment. We adopt a “partial evaluation and assembly” framework …

Graph analysis is a powerful method in data analysis. Although several frameworks have
been proposed for processing large graph instances in distributed environments, their …