Detecting semantically related concepts in a SOA integration scenario

In this paper, we present an approach to detecting semantically related concepts in a service oriented environment. This method is essential when creating collaborative business processes. Standard enterprise application systems such as enterprise resource planning (ERP), customer relationship management (CRM), supply chain management (SCM) etc. offer a lot of opportunities for application interoperability. System integrators assign a set of services from various application systems to the integration scenario. A well defined discovery process can detect these services. Nevertheless, building an operable business process requires the mapping of these services in the data schema used in the business process. This mapping results in a global understanding of relevant business concepts in the integration scenario. This paper focuses on the identification of semantically relevant concepts in different schemas in the participating services. A short overview of our integration platform and methodology is also included

SOA based web service adaptation in enterprise application integration

Enterprise Application Integration (EAI) is a permanent need since various information systems are employed at companies. Numerous standard systems must be aligned to new business processes. There are participant systems older than 10 years, and others developed only 1-2 years ago. This implicates a wide technological variance making the integration problem a real challenging issue. The widespread of the Service Oriented Architecture (SOA) seems to be one of the most promising approaches in EAI. Although this is already supported by solid technology and tools, deploying executable processes, predicting and optimizing their non-functional performance is still an open issue. In this paper we propose a technological solution for the adaptation of standard enterprise services into SOA integration scenarios providing support for applying data transformation to bridge data incompatibilities. To evaluate our approach three other possible solutions are designed and implemented. An in detailed analytic and experimenta l comparison of the approaches is also presented