LEVERAGING SOA IN BANKING SYSTEMS INTEGRATION

There is no doubt that the systems integration is one of the most important and complicated tasks in software filed especially for complex applications like banking systems. Complexity in integrating banking systems often comes from continues changes in both technical and business features provided by them to meet customer needs. Banking systems always come from different software vendors which mean using platforms and different design and architecture patterns, and this for sure adds extra complexity for integrating them. Serviceoriented architecture (SOA) is a promising method in software filed that aims to build or restructure software systems in a manner that makes their maintenance and integration easier. Agility is the most important goal that should be achieved when building and integrating banking systems. Simply, agility is needed to meet market needs quickly and efficiently and SOA is the way that could provide itSOA, SOI, P2P Integration, Web Services, and Legacy Code

Business and technology integrated model

There is a growing interest in business modeling and architecture in the areas of management and information systems. One of the issues in the area is the lack of integration between the modeling techniques that are employed to support business development and those used for technology modeling. This paper proposes a modeling approach that is capable of integrating the modeling of the business and of the technology. By depicting the business model, the organization structure and the technology architecture, it can contribute to improve existing development practices.(undefined

An ontology-based model management architecture for service innovation

Organizations have indicated renewed interest in service innovation, design and management, given the growth of service sector. Decision support systems (DSS) play an important role in supporting this endeavor, through management of organizational resources such as data and models. Given the global nature of service value chains, there have been ever increasing demands on managing, sharing, and reusing these heterogeneous and distributed resources, both within and across organizational boundaries, through DSS consisting of database management systems (DBMS) and model management systems (MMS). Analogous to DBMS, model management systems focus on the management of decision models, dealing with representation, storage, and retrieval of models as well as a variety of applications such as analysis, reuse, sharing, and composition of models. Recent developments in the areas of semantic web and ontologies have provided a rich tool set for computational reasoning about these resources in an intelligent manner. In this chapter, we leverage these advances and apply service-oriented design principles to propose an ontology-based model management architecture supporting service innovation. The architecture is illustrated with case study scenarios and current state of implementation. The role of potential information technologies in supporting the architecture is also discussed. We then provide a roadmap to make advancements in research in this direction