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Ten Pitfalls of Enterprise Ontology Management : Page 2

As ontologists and business strategists incorporate semantic web technologies in large organizations, they experience a natural growing pains process. This article will help you through that process.


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Duplicating Data Elements
Using keywords and synonyms is one way to ensure that search tools find and display the data elements a user needs.
One of the first tests of a high-quality ontology is to look for duplication of data elements. The larger an ontology grows, the higher the probability that an untrained user will enter a new data element that already exists in your corporate ontology. Untrained users usually do this because they are not aware that it already exists in the ontology. If your ontology management system has a search tool, then you can always train new users on how to use these tools. But searching tools alone are usually not enough. For example, a user might search for a term such as "Individual" not knowing that you stored information about human beings under the class "Person." Using keywords and synonyms is one way to ensure that search tools find and display the data elements a user needs.

The second line of defense against accidental duplication of data elements is a human-centric review process. Most ontologies have a few expert users that are familiar with the structure and conventions used in an ontology. When a novice user adds a new data element to an ontology an e-mail or other notification message can be sent to experts alerting them that new data elements are pending their review.

In large standards this review process usually is directed to a committee of experts who have a specialized understanding for specific parts of the ontology. In financial institutions some members might specialize in stock transactions and some in bonds. The key is to have a clearinghouse to assign data elements to the group that has the most expertise. This is one of the central aspects of data governance and data stewardship that must be in place for the ontology to gain enterprise respect and usage.



Role Pollution

Removing roles from properties is one of the best ways to keep your ontologies reasonable.
A common oversight a novice ontologist can make is mistaking a role for an actual object. For example, a person may play many roles in a business event. In healthcare, a person might play the role of a patient, a nurse, a physician or an office assistant. It seems obvious at first to take a form that has the label "PatientName" and create a property of patient-name in your ontology. Then you might add physician-name, and nurse-name and office-assistant-name. The key is to realize that these labels on the medical forms reflect the role that a "Person" plays in the business event. To create precise rules around names, you want to remove the role from the name and create subclasses of Person for each of these roles. The PersonGivenName and PersonFamilyName can then be properties of Person and your business rules for validating these names can be shared. You can then create a PersonRoleCode and assign the role to successive values of PersonRoleCode="Patient", etc. Removing roles from properties is one of the best ways to keep your ontologies reasonable.



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