Supporting Semantically Enhanced Web Service Discovery for Enterprise Application Integration

The availability of sophisticated Web service discovery mechanisms is an essential prerequisite for increasing the levels of efficiency and automation in EAI. In this chapter, we present an approach for developing service registries building on the UDDI standard and offering semantically-enhanced publication and discovery capabilities in order to overcome some of the known limitations of conventional service registries. The approach aspires to promote efficiency in EAI in a number of ways, but primarily by automating the task of evaluating service integrability on the basis of the input and output messages that are defined in the Web service’s interface. The presented solution combines the use of three technology standards to meet its objectives: OWL-DL, for modelling service characteristics and performing fine-grained service matchmaking via DL reasoning, SAWSDL, for creating semantically annotated descriptions of service interfaces, and UDDI, for storing and retrieving syntactic and semantic information about services and service providers

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

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 machine-understandable 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 Model-driven Approach for the Description of Blockchain Business Networks

The concept of blockchain technology has gained significant momentum in practice and research in the past few years, as it provides an effective way for addressing the issues of anonymity and traceability in distributed scenarios with multiple parties, which have to exchange information and want to securely collaborate with each other. However, up-to-date, the impact of the structure and setup of business networks on successfully applying blockchain technology, remains largely unexplored. We propose a model-driven approach, combining an ontology and a layer model, that is capable of capturing the properties of existing blockchain-driven business networks. The layers are used to facilitate the comprehensive description of such networks. We also introduce the Blockchain Business Network Ontology (BBO), formalizing the concepts and properties for describing the integral parts of a blockchain network. We show the practical applicability of our work by evaluating and applying it to an available blockchain use case

Semantic Benchmarking of Process Models - An Ontology-Based Approach

This article suggests an approach which allows the costly analysis of processes (e.g., in serviceoriented architectures) for benchmarking to be partially automated, so that the performance indicators, as well as qualitative differences between processes become apparent. The approach is based on using appropriate ontologies, which make the process models both syntactically and semantically comparable. In this article, we present a conceptual model for this new approach to process benchmarking, a framework, as well as a software prototype for analyzing and comparing individual process models. We provide an overview of our multi-method evaluation methodology and delineate the technical, conceptual, and economic evaluation perspectives with their respective outcomes. This analysis allowed us to determine whether our approach is generally suitable for generating novel and useful information on different process models that describe the same problem domain

Ontology of core data mining entities

In this article, we present OntoDM-core, an ontology of core data mining entities. OntoDM-core defines themost essential datamining entities in a three-layered ontological structure comprising of a specification, an implementation and an application layer. It provides a representational framework for the description of mining structured data, and in addition provides taxonomies of datasets, data mining tasks, generalizations, data mining algorithms and constraints, based on the type of data. OntoDM-core is designed to support a wide range of applications/use cases, such as semantic annotation of data mining algorithms, datasets and results; annotation of QSAR studies in the context of drug discovery investigations; and disambiguation of terms in text mining. The ontology has been thoroughly assessed following the practices in ontology engineering, is fully interoperable with many domain resources and is easy to extend

Value-driven partner search for <i>Energy from Waste</i> projects

Energy from Waste (EfW) projects require complex value chains to operate effectively. To identify business partners, plant operators need to network with organisations whose strategic objectives are aligned with their own. Supplier organisations need to work out where they fit in the value chain. Our aim is to support people in identifying potential business partners, based on their organisation’s interpretation of value. Value for an organisation should reflect its strategy and may be interpreted using key priorities and KPIs (key performance indicators). KPIs may comprise any or all of knowledge, operational, economic, social and convenience indicators. This paper presents an ontology for modelling and prioritising connections within the business environment, and in the process provides means for defining value and mapping these to corresponding KPIs. The ontology is used to guide the design of a visual representation of the environment to aid partner search