Combining SAWSDL, OWL-DL and UDDI for Semantically Enhanced Web Service Discovery

Abstract

Abstract. UDDI registries are included as a standard offering within the product suite of any major SOA vendor, serving as the foundation for establishing design-time and run-time SOA governance. Despite the success of the UDDI specification and its rapid uptake by the industry, the capabilities of its offered service discovery facilities are rather limited. The lack of machineunderstandable semantics in the technical specifications and classification schemes used for retrieving services, prevent UDDI registries from supporting fully automated and thus truly effective service discovery. This paper presents the implementation of a semantically-enhanced registry that builds on the UDDI specification and augments its service publication and discovery facilities to overcome the aforementioned limitations. The proposed solution combines the use of SAWSDL for creating semantically annotated descriptions of service interfaces and the use of OWL-DL for modelling service capabilities and for performing matchmaking via DL reasoning.

A Visual Semantic Service Browser Supporting User-Centric Service Composition

“…Various features and attributes of a class can be described with the properties of the class. In the service-oriented computing area, using ontologies to describe the formal semantics of Web services has proven its effectiveness in high-precision service discovery [17], [11] and automatic service composition [24]. To facilitate service exploring and discovering, we define the OPUCE Ontology which is based on OWL-DL, a sublanguage of the Web Ontology Language (OWL) W3C standard that is named for its correspondence with description logics.…”

“…The exploring and discovering of large information spaces is still a difficult task, especially if the user is not familiar with the terminology used to describe information and the query language used to search specific information [9]. Work on enhancing Web service discovery framework-such as UDDI-with semantic features [11], [21] cannot solve the problem since the user still needs to write the query in a dedicated ontology language, or to fill a template with terms defined in an ontology to find services. To cross this hurdle, we develop the OPUCE Visual Semantic Service Browser (OPUCE Browser in short) that provides intuitive visual interfaces for users to easily carry out the tasks of service exploring and discovering.…”

“…• hasInput and hasOputput:Just like most service semantic models such as OWL-S [13] and FU-SION [11], inputs and outputs (IO) are introduced to represent the set of parameters that a service expects to receive and the set of parameters that a service will produce if invoked. Furthermore, these two properties are grouped as the sub-properties of the hasParameter property.…”

Hybrid Adaptive Web Service Selection with SAWSDL-MX and WSDL-Analyzer

“…For result ranking, the distances of training samples to this plane are computed, and then taken as reference similarity values for deciding on the relevance of unknown services. 7 ) feature vectors where each feature f 1 to f 5 represents the logic-based matching result for a service query/offer pair including fail, feature f 6 stands for the text-based similarity value, and f 7 for the structural similarity value computed by the WSDL-Analyzer. For example, the feature vector (0, 0, 1, 0, 0, 0.6, 0.7) represents the hybrid semantic matching result computed by SAWSDL-MX as follows: A logical subsumes match with text similarity of 0.6 and structural similarity of 0.7.…”

“…In FUSION [7], any SAWSDL service description is classified at the time of its publishing and then mapped to UDDI to allow for fast lookups. In case of unknown semantic service requests reasoning has to be done at query time.…”