We describe a verbalization of the logical content of OWL ontologies — using OWL 1.1 without data-valued properties — in Attempto Controlled English (ACE). Because ACE is a subset of English, the verbalization makes OWL ontologies accessible to people with no training in formal methods. We conclude that OWL can be verbalized in concise and understandable English provided that a certain naming s...

Although OWL, an emerged standard of expressing ontologies in the Semantic Web, is a very expressive ontology language, the OWL datatyping formalism is far not expressive enough to generally represent user-defined datatypes (such as XML Schema derived datatypes), not to mention user-defined datatype predicates (such as > for non-negative integers) in Semantic Web ontologies and applications. In...

OWL-S is an application of OWL, theWeb Ontology Language, that describes the semantics of Web Services so that their discovery, selection, invocation and composition can be automated. The research literature reports the use of UML diagrams for the automatic generation of Semantic Web Service descriptions in OWL-S. This paper demonstrates a higher level of automation by generating complete compl...

The wide scale usage of OWL for the formalization of real-world ontologies is currently influenced by important limitations which concern both its expressivity and the efficiency of OWL specific reasoning tools. While the expressivity limitations may be overcame by extending the OWL language (e.g. with rules), the reasoning with such heterogeneous knowledge bases is still an open issue. In this...

One of the main aims of the so-called Web of Data is to be able to handle heterogeneous resources where data can be expressed in either XML or RDF. The design of programming languages able to handle both XML and RDF data is a key target in this context. In this paper we present a framework called XQOWL that makes possible to handle XML and RDF/OWL data with XQuery. XQOWL can be considered as an...

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...

The Orthant-Wise Limited memory QuasiNewton (OWL-QN) method has been demonstrated to be very effective in solving the l1regularized sparse learning problem. OWL-QN extends the L-BFGS from solving unconstrained smooth optimization problems to l1-regularized (non-smooth) sparse learning problems. At each iteration, OWL-QN does not involve any l1regularized quadratic optimization subproblem and on...

Web Ontology Language (OWL) is a core world wide web consortium [W3C] standard Knowledge representation language for the Semantic Web. The term Knowledge representation in general refers to the method of modeling the knowledge about the real world entities and relations. OWL is a highly expressive, flexible and efficient knowledge representation language, that can be used to model background kn...

The OWL language [1] is being widely used to define ontologies in the Web. This language provides three increasingly expressive sublanguages, namely OWL Lite, OWL-DL and OWL Full. The OWL-DL XML based syntax together with its correspondence with Description Logics (DL) [2], make it a good candidate to be the standard language for defining ontologies used by Semantic Web applications. However, t...