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Model Driven Service Domain Analysis
ISBN
978-3-540-75491-6
Type
conference paper
Date Issued
2006-12-04
Author(s)
Schoenherr, Marten
Editor(s)
Georgakopoulos, Dimitrios
Ritter, Norbert
Benatallah, Boualem
Zirpins, Christian
Feuerlicht, George
Schoenherr, Marten
Motahari-Nezhad, Hamid Reza
Research Team
IWI1
Abstract
Currently scientists and practitioners are discussing Service Oriented Architectures (SOA) as an approach to reconcile business requirements and IT. The alignment of business and technology in organizations is a key challenge in the discipline of Enterprise Architecture (EA). Therefore the contribution starts with a discussion of SOA as an EA integration concept to synchronize business requirements and IT architecture in an efficient way. Differentiating methodological and technological aspects of EA the paper shows the need for methods in the field of domain analysis supporting the design of a SOA. The main contribution of the paper is an algorithm based modeling tool and methodology to support service domain clustering. Service clusters are being used for service definition and management. Due to enormous complexity it is necessary to support architects by finding and defining appropriate clusters. For modeling interdependencies in EA the paper's focus is on business processes, information systems and interfaces. Our approach adopts network-centric algorithms used in the field of social network analysis to define and/or identify service domain clusters in complex scenarios. Edge remover algorithm is used to compute the relevant model aspects. The results of our approach will be demonstrated in acase study.
Language
English
HSG Classification
not classified
Refereed
Yes
Book title
Service-Oriented Computing ICSOC 2006, Workshops Proceedings
Publisher
Springer
Publisher place
Berlin, Heidelberg
Volume
LNCS 4652
Start page
190
End page
200
Pages
11
Event Title
4th International Conference on Service-Oriented Computing, ICSOC 2006
Event Location
Chicago, IL , USA
Event Date
04.-07.12.2006
Subject(s)
Division(s)
Eprints ID
234143