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

2.7. SUMMARY 29
• Creation or import. The contents need to be created or converted so that they
fit the conventions of the company.
• Capture. Knowledge items have to be captured in order to determine their importance
and how they mesh with the company’s vocabulary conventions.
• Retrieval and access. This step satisfies the searches and queries for knowledge
by the knowledge worker.
• Use. The knowledge worker will not only recall knowledge items, but will process
them for further use.
The steps are illustrated in Figure 2.6. In this thesis, the scope of the knowledge
management is only limited on type level process knowledge – enterprise/business process
models. Therefore, in the context of our process knowledge management, process
modeling in knowledge representation language is concerned as knowledge creation.
Importing knowledge can be the transformation of conventional process models in the
knowledge representations. Knowledge capture is to capture the essential contents in
process models through annotation techniques by creating metadata conforming to
ontologies. Process knowledge retrieval and access can be conducted through a conventional
query or search tools, or by applying the ontology and the inference mechanism
to derive further views of process knowledge. The possible uses of process knowledge
include analysis of existing process models, reusing the legacy models to create new
process models, integrating systems based on the process descriptions, etc.
2.7 Summary
This chapter has outlined the context of this research work. We have introduced the
theoretical and technical setting relevant to our research topic, such as modeling theories
and methodologies, the Semantic Web, ontology, semantic annotation, business
process model and knowledge management. Main points are summarized as follows.
• From the discussion of modeling theory and methodology, we has scoped that our
research area is at conceptual modeling level.
• Ontology as the key enabling technology for the Semantic Web provides an explicit
representation of a shared conceptualization.
• Ontology and conceptual model share certain common grounds, which indicates
the potential links between them, e.g. usage combination and technology benefits
from each other.
• In this work, a concept modeling language – RML is used to analyze meta-models
and ontologies with graphical notations; while, an ontology modeling language –
OWL is applied to enable ontology machine-interpretable.
• Semantic annotation is an approach to achieve semantic interoperability of heterogeneous
information resources making use of ontology.