Ten Pitfalls of Enterprise Ontology Management : Page 5

Lack of Code-Level Semantics
Many of the glamorous parts of creating an ontology are creating the highly visible high-level classes that are used for multiple years across an enterprise. But there are many not-so-glamorous and not-so-visible parts of creating highly-precise ontologies that are critical for system interoperability. One of these is the value domains of properties. For example, each state in the U.S. has a two-letter state code. You may have a business rule that indicates a state-code must use one of the correct state codes. And to be complete an ontology must store:

• Each of these codes
• Creation dates
• Definitions
• Extended properties, including:
• Who created the code
• How it is distinct from other codes
• If a code was depreciated in a searchable structure

Documenting precise semantics for each of the codes in your system can comprise over half of the work in an ontology and reviewers need to review each of the codes with the same process that goes on for many other data elements. This is the drudgery work of building an ontology but one that gives any enterprise project credibility.

Taking a Leading Role in Your Organization

Figure 5. Data Element Approval: To help your organization, create a shared process for defining data element approval.

Many organizations empower enterprise ontologists to become the keeper of semantic precision. Ontologists can become the core team that helps an organization:

• Enforce consistent semantics for shared business rules
• Create a shared process for defining data element approval (see Figure 5)
• Create shared meaning of conformed dimensions in a data warehouse
• Create consistent product taxonomies
• Create consistent integration maps that map database systems to web services
• Create consistent leaf-level data elements that move between any two computer systems

This precision and consistency of ontologies allows organizations to save time and money building complex systems. Tools to find trusted data elements quickly allow these organizations to be agile. Together ontologists and semantic web technologies can play a leading role in large-scale enterprise costs savings.

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