More andmore RDF data is exposed on theWeb via SPARQL endpoints. With the recent SPARQL 1.1 standard, these datasets can be queried in novel and more powerful ways, e.g., complex analysis tasks involving grouping and aggregation, and even data frommultiple SPARQL endpoints, can now be formulated in a single query. This enables Business Intelligence applications that access data from federated w...

Updates in RDF stores have recently been standardised in the SPARQL 1.1 Update specification. However, computing answers entailed by ontologies in triple stores is usually treated orthogonally to updates. Even W3C’s SPARQL 1.1 Update language and SPARQL 1.1 Entailment Regimes specifications explicitly exclude a standard behaviour for entailment regimes other than simple entailment in the contex...

There are many query languages (QLs) that can be used to query RDF and OWL ontologies but neither type is satisfactory for querying OWL-DL ontologies. RDF-based QLs (RDQL, SeRQL, SPARQL) are harder to give a semantics w.r.t. OWL-DL and are more powerful than what OWL-DL reasoners can provide. DL-based QLs (DIG ask queries, nRQL) have clear semantics but are not powerful enough in the general ca...

In this paper, we propose a plugin-based framework for RDF stream processing (PRSP). With this framework, we can apply SPARQL engines to process C-SPARQL queries with maintaining the high performance of those engines in a simple way. Taking advantage of PRSP, we can process large RDF streams in a distributed context via distributed SPARQL engines. Moreover, we can evaluate the performance and c...

Google Fusion Tables (GFT) is a data management, integration and visualization service provided by Google. Users can upload their structured data, integrate it with other people’s data, and visualize it on various tools provided, such as Google Maps, charts or graphs. Every GFT table constitutes a data silo that is not commonly linked to other data sources. A way to enable data to be linked and...

We believe that the possibility to use SPARQL as a front end to heterogeneous data without significant cost in performance or expressive power is key to RDF taking its rightful place as the lingua franca of data integration. To this effect, we demonstrate how RDF and SPARQL can tackle a mix of standard relational workload and data mining in public data sources. We discuss extending SPARQL for b...

SPARQL is the standard query language for RDF data. The distinctive feature of SPARQL is the OPTIONAL operator, which allows for partial answers when complete answers are not available due to lack of information. However, optional matching is computationally expensive – query answering is PSPACE-complete. The well-designed fragment of SPARQL achieves much better computational properties by rest...

An ever-growing amount of life science databases are (partially) exposed as RDF graphs (e.g. UniProt, TCGA, DisGeNET, Human Protein Atlas), complementing traditional methods to disseminate biodata. The SPARQL query language provides a powerful tool to rapidly retrieve and integrate this data. However, the inability to incorporate custom data processing methods in SPARQL queries inhibits its app...