One promise of Semantic Web applications is to seamlessly deal with heterogeneous data. The Extensible Markup Language (XML) has become widely adopted as an almost ubiquitous interchange format for data, along with transformation languages like XSLT and XQuery to translate data from one XML format into another. However, the more recent Resource Description Framework (RDF) has become another popular standard for data representation and exchange, supported by its own query language SPAR-QL, that enables extraction and transformation of RDF data. Being able to work with XML and RDF using a common framework eliminates several unnecessary steps that are currently required when handling both formats side by side. In this paper we present the XSPARQL language that, by combining XQuery and SPARQL, allows to query XML and RDF data using the same framework and transform data from

No abstract

In addition to taxonomic knowledge about concepts and properties typically expressible in languages such as RDFS and OWL, implicit information in an RDF graph may be likewise determined by arithmetic equations. The main use case here is exploiting knowledge about functional dependencies among numerical attributes expressible by means of such equations. While some of this knowledge can be encoded in rule extensions to ontology languages, we provide an arguably more flexible framework that treats attribute equations as first class citizens in the ontology language. The combination of ontological reasoning and attribute equations is realized by extending query rewriting techniques already successfully applied for ontology languages such as (the DL-Lite-fragment of) RDFS or OWL, respectively. We deploy this technique for rewriting SPARQL queries and discuss the feasibility of alternative implementations, such as rulebased approaches.