Certainly, people who are defing modern information systems (i.e. programmers) need ontologies for at least two things: interchange and configuration. The techniques we teach build upon the demonstrated success of XML in these areas.

But more broadly, the modeling power offered by semantic technology is potentially relevant to many tasks faced by modern knowledge workers, including researchers, analysts, legal and health care workers, librarians, designers, web developers, entrepeneurs, and engineers.

Some examples of applications where ontology integration should be considered:

• Media resource management (e.g. library science)
• Definition of message vocabularies (for B2B, B2G, G2G applications)
• Clinical medical applications (e.g. insurance and billing, drug interaction, decision support)
  
• Scientific collaboration workflows involving complex datasets
  
• Statistical population analysis (e.g. correlation of survey responses wth election data)
  
• Matchmaking (e.g. matching jobs with resumes, matching romantic profiles, etc.)
• Financial applications (forecasts, what-if analysis, pricing models)
• Product modelling (e.g. complex financial products involving securities)
• Intelligent search applications
• Rigorous validation systems
  
• Planning and optimization
  
• Simulations, games, and educational applications
• Law enforcement applications
• Information security models (e.g. complex privelege hierarchies)