Semantic Annotation for Process Models: - Department of Computer ...

6 CHAPTER 1. INTRODUCTION
• RQ5. How can we use the proposed approach to facilitate process knowledge
management?
1.3 Objectives
Corresponding to the main research question, the overall objective of this thesis is to
propose a semantic annotation approach for dealing with semantic heterogeneity of
process models in order to facilitate process knowledge management activities (such as
recognizing and reusing IS solutions of process models) via semantic interoperability.
It is decomposed into the following four sub-objectives which are to be achieved step
by step during the development of the work.
1. To investigate semantic heterogeneity issues in business process modeling.
2. To explore a comprehensive annotation approach to deal with heterogeneous semantics
of process knowledge with referenced ontology.
3. To develop an annotation tool to implement the approach by applying Semantic
Web technologies.
4. To evaluate quality and use feasibility of the proposed approach and tool in
supporting process knowledge management activities.
1.4 Approach and Scope
We focus on business process models at a conceptual level. They are available process
knowledge resources which need to be managed for further reuse. Therefore, heterogeneous
process models should be reconciled and process knowledge conveyed by the
models should be explicitly expressed.
The approach taken is (1) to express the process properties of each business process
model in a common annotation system, (2) to express model context in ontologies that
may be compared to each other, one ontology for each context, and (3) to map the
intentions of the systems’ owners to goal structures that may be compared to each
other. These three elements constitute the means to profile a business process model,
and provides the basis for building a library of modeling assets, and for recognizing
similar model fragments to make them easier available for reuse.
Ontologies aid to share knowledge on the basis of the assumption that there is a
single reality and the sharing is a matter of aligning the way different people or systems
think about it [70]. Annotating models with the agreed ontologies provides a
way of reconciling heterogeneity and reaching consensus on the semantics of terms and
concepts. To facilitate management and reuse of the reconciled models, the semantics
of the process models should be interpretable and inferable by machines as modeling
assets. The approach is hereby deployed having the two concerns: 1) reconciling
process knowledge representation of heterogeneous models, and 2) explicating process
knowledge in a machine-interpretable manner.