Towards the deep, knowledge-based interoperability of applications
Information Systems
Andrius Valatavičius
Saulius Gudas
Published 2018-01-25
https://doi.org/10.15388/Im.2017.79.11400
PDF

Keywords

internal modeling
enterprise management
domain modeling
self-managed system
MDA
knowledge discovery
interoperability
autonomic computing

How to Cite

Valatavičius A. and Gudas S. (2018) “Towards the deep, knowledge-based interoperability of applications”, Informacijos mokslai, 790, pp. 83-113. doi: 10.15388/Im.2017.79.11400.

Abstract

The interoperability of enterprise applications in a dynamic environment is a complex issue. New methodological approaches and solutions are required. The methodological background of our approach is the internal modeling paradigm integrated with MDA approach. The modified MDA schema includes the new layer of the domain knowledge discovery, frameworks for internal modeling of enterprises. The peculiarity of the modified MDA is a focus on the cross-layer transferring of domain causality. The presented frameworks will help to trace the domain causal dependencies across the layers of the software system development, and they will aid in determining the influence of domain causality to the integrity and interoperability of the application. Researchers consider that the dynamic enterprise domain must be a goal-driven and self-managed system. The management transaction concept uses the internal modeling of the enterprise, which reveals the goal-driven information transformations inside the enterprise management activity (deep knowledge). This approach is combining the business process modeling and control theory principles, enterprise architecture modeling and autonomic computing concepts. The ArchiMate enterprise architecture modeling language is used for illustrating the cross-layer transferring of domain causality. Finally, we developed the architecture of the interoperable enterprise applications with the autonomic integration component.

PDF

Please read the Copyright Notice in Journal Policy