Authors:
Thomas Moser
1
;
Richard Mordinyi
1
;
Stefan Biffl
1
and
Alexander Mikula
2
Affiliations:
1
Vienna University of Technology, Austria
;
2
Frequentis AG, Austria
Keyword(s):
System Integration, Integration of Heterogeneous Data Sources.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Artificial Intelligence and Decision Support Systems
;
Coupling and Integrating Heterogeneous Data Sources
;
Databases and Information Systems Integration
;
Enterprise Information Systems
;
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Knowledge Engineering
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Knowledge-Based Systems Applications
;
Organisational Issues on Systems Integration
;
Software Engineering
;
Symbolic Systems
Abstract:
Business system designers want to integrate heterogeneous legacy systems to provide flexible business ser-vices cheaper and faster. Unfortunately, modern integration technologies represent important integration knowledge only implicitly making solutions harder to understand, verify, and maintain. In this paper we propose a data-driven approach, “Semantically-Enabled Externalization of Knowledge” (SEEK), that explicitly models the semantics of integration requirements & capabilities, and data transformations between he-terogeneous legacy systems. Goal of SEEK is to make the systems integration process more efficient by providing tool support for quality assurance (QA) steps and generation of system configurations. Based on use cases from industry partners, we compare the SEEK approach with UML-based modeling. In the evalua-tion context SEEK was found to be more effective to make expert knowledge on system requirements and capabilities available for more efficient tool support and reuse.