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

22 CHAPTER 2. PROBLEM SETTING
ity of RML and OWL, it is not surprising to find a big overlapping of the modeling
constructs between the two languages since both of them share a similar logic basis 5 .
We do not intend to build one-to-one mapping between RML and OWL, but take the
advantages of both as our research tools. We mainly use RML to visualize the concepts
and relations of ontologies for human comprehension, and employ OWL to formalize
ontology models for machine interpretation and reasoning.
2.4 Semantic Interoperability
Interoperability is the ability of two or more systems or components to exchange information
and to use the information that has been exchanged [119]. Interoperability is a
broadly used term, encompassing many of the issues impinging upon the effectiveness
with which diverse information resources might fruitfully co-exists. The issues can be
defined for different purpose, such as, semantics.
Semantic interoperability is the ability of two or more computer systems to exchange
information and have the meaning of that information accurately and automatically
interpreted by the receiving system. The main obstacle of semantic interoperability is
semantic heterogeneity of the information to be exchanged. Common understanding of
semantics and standardization of semantic representation are usually concerned as the
solutions tackling the semantic heterogeneity to achieve semantic interoperability.
2.4.1 Semantic heterogeneity
Semantic heterogeneity is usually distinguished from syntactic heterogeneity and structural
heterogeneity in the database community [37] [39] [86] [88] [89]. Syntactic heterogeneity
is concerned with the heterogeneity of data formats. Standardizing data formats
is taken as an approach to solve syntactic heterogeneity problems. For example, XML is
used as a standard format for all forms of Web-accessible data. Structural heterogeneity
is associated with different data models, data structures or schemas, e.g. relational and
object-oriented database models. An example of the solutions for structural heterogeneity
is that RDF based on XML syntax provides a unified way to structure information
sources or object models for Web-based information exchange [100]. When two information
sources are modeled in a same format by applying a same modeling methodology,
there still might be semantic heterogeneity problem. Semantic heterogeneity can be
identified according to the different types of conflicts [172]:
1. Semantic conflicts. Different modelers do not perceive exactly the same set of
real world objects, but instead they visualize overlapping sets (included or intersecting
sets). For example, a "Student" object class may appear in one schema,
while a more restrictive "CS-Student" object class (grouping students majoring in
computer science) is in another schema. The "CS-Student" class will be integrated
as a subclass of the "Student" class in the integration of two schemas.
2. Descriptive conflicts. Descriptive conflicts include naming conflicts due to homonyms
and synonyms [7] [111], attribute domain, scale, constraints, operations, etc. [84].
5 FOL (Fist Order Logic) can formalize the set theory.