Types of Vertical Ontologies

Moving forward with the notion that the application of ontologies in the vertical domains is where the most value exists, it's feasible to further define types of ontologies, or architectural approaches. For our purposes we can define them as:

• Information based

• Behavior based

• Process based

Information-based ontologies are the most basic of the architectural approaches. They simply define common information properties, concepts, rules, and how they relate one to another, using standard reference models that support information integration as well as knowledge sharing for a vertical domain. Information-based ontology is required in all domains, no matter if you leverage behavior-based or process-based ontologies. What is more, information-based ontologies typically require a repository.

Behavior-based ontologies define terminologies and concepts relevant to a particular application service that is repeatable across multiple vertical domains. A problem example of this is HIPPA processing, which is made up of common sets of functions as well as common sets of semantics. The purpose of this type of ontology architecture is to define standard semantic meaning around Service-Oriented Architecture (SOA), thus providing better reuse from problem domain to problem domain. It is interesting to note that the concept of semantics is missing from the current Web services-based standards, and the use of behavior-based ontologies is something that would fill that gap (for more information about this subject, see "The Web Services Scandal" by Jeffrey Pollock in the August 2002 issue of Application Integration Journal).

Process-based ontologies define terminologies and concepts around coordinating processes that are relevant to a vertical domain. This differs from behavior-based ontologies in that the process coordinates the use of both behavior (remote functions) and information (information passing between systems). However, like behavior-based ontologies, we are again looking to define standard semantic meaning to common processes that are transferable among vertical domains, such as Straight Through Processing (STP). Moreover, process-based ontologies define inputs, outputs, constraints, relations, hierarchies, sequences, subprocesses, and process control semantics.

Abstraction and Ontologies

When dealing with abstraction, certain characteristics of the objects are coded in the databases in such a manner that the set of characteristics is representative of real-world objects.^[9] Depending on the importance of the information, or need for detail, the set of characteristics are defined as more or less detailed. This is, in essence, the notion of abstraction and ontologies.

To this end, in some instances, object-oriented modeling may be employed to define ontologies by defining information at different levels of abstraction. We define this by suggesting a number of specializations. In each specialization, a number of additional characteristics are required, thus increasing the level of detail in the original object. Being an object-oriented model, each specialization inherits the characteristics of the more generic object class. Using this model, you can mix and match ontologies for use inside of your application integration problem domain.

When using this type of ontology model, ontologies are translated into classes, and all classes have special operations for navigation in the ontology tree. This model can support both single and multiple inheritance.

Object abstraction and object-oriented modeling are helpful in creating ontologies for application integration. The support of inheritance is especially useful, considering the opportunity for reuse, as well as abstraction layers that offer various levels of detail.

^[9] Fonseca, Frederico, Max Egenhover, and Clodoveu David. 1999. "Ontology-Driven Information Integration."