Integrating an Enterprise Architecture Using Domain Clustering

Enterprise Architecture (EA) in the context of enterprise engineering addresses aspects of developing, improving and integrating organizations. The paper introduces an approach to EA proposing Integration Concepts (IC) to reconcile changing business process requirements and information systems. Being process-driven and supporting integration issues the chosen IC is a Service Oriented Architecture (SOA). Therefore the contribution aims at developing a methodology to support service engineering by defining architectural domains in an EA. The paper shows the need for methods in the field of domain engineering supporting the design of a SOA. The main contribution of the paper is an algorithm based modelling approach and a methodology to support service domain clustering. The clustering algorithms are using a model considering business processes, information systems and information system interfaces. The algorithm adopts network-centric approaches used in the field of social network analysis to define and/or identify service domain clusters in complex scenarios. The paper summarizes a case study in a globally operating company and closes with a conclusion. The paper is organized by chapters addressing context, objective, approach, case, results and lessons learned.

[1]  M E J Newman,et al.  Community structure in social and biological networks , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[2]  Leonard M. Freeman,et al.  A set of measures of centrality based upon betweenness , 1977 .

[3]  Robert Winter,et al.  Essential Layers, Artifacts, and Dependencies of Enterprise Architecture , 2006, 2006 10th IEEE International Enterprise Distributed Object Computing Conference Workshops (EDOCW'06).

[4]  Dan Gisolfi,et al.  Web Services Architect Part 1: An Introduction to Dynamic e-Business , 2001 .

[5]  Daniela Florescu,et al.  XL: a platform for web services , 2002, SIGMOD '02.

[6]  M E J Newman,et al.  Finding and evaluating community structure in networks. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[7]  Padhraic Smyth,et al.  Analysis and Visualization of Network Data using JUNG , 2005 .

[8]  Paul Clements,et al.  Software architecture in practice , 1999, SEI series in software engineering.

[9]  Peter Kruck,et al.  Ein algorithmisches Verfahren zur Bewertung und Verdichtung von Entity-Relationship-Modellen , 1993, Inform. Forsch. Entwickl..

[10]  Jean-Daniel Fekete,et al.  Analysis and Visualization , 2020, Neural Machine Translation.

[11]  Robert Winter,et al.  Towards a Methodology for Service Construction , 2007, 2007 40th Annual Hawaii International Conference on System Sciences (HICSS'07).

[12]  Jean-Francois Girard,et al.  Finding components in a hierarchy of modules: a step towards architectural understanding , 1997, 1997 Proceedings International Conference on Software Maintenance.

[13]  M. Newman Analysis of weighted networks. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

[14]  Johannes Sametinger,et al.  Component models and component services: concepts and principles , 2001 .

[15]  Stanley Wasserman,et al.  Social Network Analysis: Methods and Applications , 1994, Structural analysis in the social sciences.

[16]  Stephan Aier,et al.  Evaluating Integration Architectures - A Scenario-Based Evaluation of Integration Technologies , 2005, TEAA.

[17]  Martin Bichler,et al.  Design science in information systems research , 2006, Wirtschaftsinf..

[18]  Stephan Aier,et al.  How Clustering Enterprise Architectures helps to Design Service Oriented Architectures , 2006, 2006 IEEE International Conference on Services Computing (SCC'06).

[19]  Purdue Methodology,et al.  A HANDBOOK ON MASTER PLANNING AND IMPLEMENTATION FOR ENTERPRISE INTEGRATION PROGRAMS , 2001 .

[20]  Malcolm Munro,et al.  Understanding service-oriented software , 2004, IEEE Software.

[21]  Alan R. Hevner,et al.  Design Science in Information Systems Research , 2004, MIS Q..

[22]  John Scott Social Network Analysis , 1988 .