The Resource Description Framework (RDF) is a graphbased data model promoted by the W3C as the standard for Semantic Web applications. Its associated query language is SPARQL. RDF graphs are often large and varied, produced in a variety of contexts, e.g., scientific applications, social or online media, government data etc. They are heterogeneous, i.e., resources described in an RDF graph may h...

SPARQL is the standard query language for RDF graphs. In its strict instantiation, it only offers querying according to the RDF semantics and would thus ignore the semantics of data expressed with respect to (RDF) schemas or (OWL) ontologies. Several extensions to SPARQL have been proposed to query RDF data modulo RDFS, i.e., interpreting the query with RDFS semantics and/or considering externa...

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...

Very recently, the vision of the Semantic Web has brought about new challenges in data management. One fundamental research issue in this arena is storage of the Resource Description Framework (RDF): the data model at the core of the Semantic Web. In this paper, we study a data-centric approach for storage of RDF in relational databases. The intuition behind our approach is that each RDF datase...

Petrini, J. 2008. Querying RDF Schema Views of Relational Databases. Acta Universitatis Upsaliensis. Uppsala Dissertations from the Faculty of Science and Technology 75. 117 pp. Uppsala. ISBN 978-91-554-7202-3. The amount of data found on the web today and its lack of semantics makes it increasingly harder to retrieve a particular piece of information. With the Resource Description Framework (R...

We build on our earlier finding that more than 95% of the triples in actual RDF triple graphs have a remarkably tabular structure, whose schema does not necessarily follow from explicit metadata such as ontologies, but for which an RDF store can automatically derive by looking at the data using so-called “emergent schema” detection techniques. In this paper we investigate how computers and in p...

Describing web resources using formal knowledge (i.e., creating metadata according to a formal representation of a domain of discourse) is the essence of the next evolution step of the Web, termed the Semantic Web. The W3C's RDF/S (Resource Description Framework/Schema Language) enables the creation and exchange of resource metadata as normal web data. In this paper, we investigate the use of R...

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This paper presents a minimalist program for RDF, by showing how one can do without several predicates and keywords of the RDF Schema vocabulary, obtaining a simpler language which preserves the original semantics. This approach is beneficial in at least two directions: (a) To have a simple abstract fragment of RDFS easy to formalize and to reason about, which captures the essence of RDFS; (b) ...

While the growing corpus of knowledge is now being encoded in the form of knowledge graphs with rich semantics, the current graph embedding models do not incorporate ontology information into themodeling.We propose a scalable and ontology-aware graph embedding model, EmbedS, which is able to capture RDFS ontological assertions. EmbedS models entities, classes, and properties differently in an R...