RDF is the data model of choice for Semantic Web applications. RDF graphs are often large and have heterogeneous, complex structure. Graph summaries are compact structures computed from the input graph; they are typically used to simplify users’ experience and to speed up graph processing. We introduce a formal RDF summarization framework, based on graph quotients and RDF node equivalence; our ...

Large-scale RDF graph databases stored in shared-nothing clusters require query processing engine that can effectively exploit highly parallel computation environment. We propose algebra of RDF graphs and its physical counterpart, physical algebra of RDF graphs, designed to implement queries as distributed dataflow programs that run on cluster of servers. Operations of algebra reflect the chara...

Since a big part of web content is stored in relational databases (RDB) there are several approaches for generating of semantic web metadata from RDB. In our previous work we designed a novel approach for RDB to RDF data transformation. This paper describes experimental comparison of our system with several means of RDF production. We benchmarked both systems for the RDB to RDF transformation a...

The Resource Description Framework (RDF) is a standard for conceptually describing data on the Web, and SPARQL is the query language for RDF. As RDF is becoming widely utilized, RDF data management systems are being exposed to more diverse and dynamic workloads. Existing systems are workload-oblivious, and are therefore unable to provide consistently good performance. We propose a vision for a ...

From our experience in using RDF stores as a backend for social media streams, we pinpoint three shortcomings of current RDF stores in terms of aggregation speed, constraints checking and largescale reasoning. Parallel algorithms are being proposed to scale reasoning on RDF graphs. However the current efforts focus on the closure computation using High Performance Computing (HPC) and require pr...

To manage the increasing amount of RDF data, an RDF repository should provide not only necessary scalability and efficiency, but also sufficient inference capabilities. In this paper, we propose a native RDF repository, SystemΠ, to pursue a better tradeoff among the above requirements. System Π takes the hypergraph representation for RDF as the data model for its persistent storage, which effec...

In many applications (like social or sensor networks) the information generated can be represented as a continuous stream of RDF items, where each item describes an application event (social network post, sensor measurement, etc). In this paper we focus on compressing RDF streams. In particular, we propose an approach for lossless RDF stream compression, named RDSZ (RDF Differential Stream comp...

RDF is the format of choice for representing Semantic Web data. RDF graphs may be large and their structure is heterogeneous and complex, making them very hard to explore and understand. To help users discover valuable insights from RDF graph, we have developed Dagger, a tool which automatically recommends interesting aggregation queries over the RDF graphs; Dagger evaluates the queries and gra...

RDF data is often treated as incomplete, following the OpenWorld Assumption. On the other hand, SPARQL, the standard query language over RDF, usually follows the Closed-World Assumption, assuming RDF data to be complete. This gives rise to a semantic gap between RDF and SPARQL. In this paper, we address how to close the semantic gap between RDF and SPARQL in terms of certain answers and possibl...

A general and flexible way to publish relational data in RDF format is to create RDF views of the underlying relational data. In this paper, we demonstrate a framework, based on rules, for the incremental maintenance of RDF views defined on top of relational data. We also demonstrate a tool that automatically generates, based on the mapping between the relational schema and a target ontology, t...