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

7.5. PROCESS KNOWLEDGE MANAGEMENT SYSTEM 121
7.5.1 System architecture
The architecture of the system for process knowledge management is shown in Figure
7.15. Since the process knowledge management system is based on the semantic annotations,
we include the annotation client tool in the system architecture. In the context
of this thesis, the annotation client tool is Pro-SEAT. Annotators works with the annotation
client too to annotate the original process knowledge resources. Annotators
in this scenario should be model experts and domain experts to assure the annotation
quality 1 . The original process knowledge resources — models and meta-models in XML
files and XML schema files are stored in the local process model repository.
As references, ontologies are essential in our approach. Ontologies are stored on
an ontology server. When annotators employ the annotation with the client tool, the
selected ontologies must be loaded from the ontology server. The annotator should
select appropriate domain ontologies and goal ontologies according to the ontology
categories. The GPO ontology is only applied for the meta-model annotation.
Completing the annotation, annotators submit the annotated process models and/or
the annotated meta-models to process knowledge repository server. It is allowed to
modify the annotated models stored on the knowledge repository server but the authorization
and the authentication are required (which we do not consider in this approach).
Knowledge users might be different from annotators. They do not know about
the original process models but the system will assist them to access the desired process
models. There are three applications for knowledge users, i.e. process knowledge
query, discovery and navigation. Those applications are implemented by client user interfaces
and application servers. Through the user interface, users can edit the queries
or provide business goals. Queries can be keyword-based or ontology-based. For the
ontology-based query, users can browse domain ontologies from the ontology repository
and use ontology concepts to form a query. Goal ontologies can be applied by
users to set goals for the knowledge discovery. When the application server receives
queries or goal requirements from the client, the matchmaker component and the reasoner
component co-work with ontologies to find process models. The reasoner uses
description logic inference technology on both the ontological query and the ontological
annotation, because ontologies and annotations are all in OWL. Based on the
inference, the matchmaker matches user’s query/goals with annotated models in the
repository. The application server sends the search results to the client and the returned
knowledge/models can be explored by the client. Users can navigate process
knowledge/models from different views according to the process properties defined in
PSAM.
7.5.2 Semantic reasoning
The underlying logic basis of OWL is description logic, which can provide the inference
services of the knowledge for semantic reasoning (w.r.t. an ontology O) [53]:
• Consistency. Check if the knowledge is meaningful. (Is C is satisfiable w.r.t.
O? i.e. C I ̸= ∅ in some model I of O?)
1 The quality of annotation affects the quality of knowledge.