Effective communication requires a common vocabulary. An ontology provides a description of the terminology, concepts and relationships for a particular area of interest. Because well-designed ontologies provide a declarative encoding of the meaning of vocabulary terms they can be critical to enabling communication, among people and between machines.

More than ten years ago, when we first developed this tutorial, there were few in our audience who had ever heard “the o word”. Today is a very different story, though. Between tremendous and growing uptake of schema.org, development of sophisticated pharmacogenomics and related bioinformatics research, and increasing usage of semantics to address issues in finance such as “know your customer” (KYC), counterparty risk, and data governance more generally, our audiences are far more knowledgeable.

This tutorial provides an overview of the knowledge representation landscape and attempts to de-mystify some of the ‘black art’ of ontology development.

We will outline basic methodology steps developed over time from a combination of:

• Business requirements analysis derived from best practices in business architecture capability and value stream analysis
• Domain analysis using business requirements adapted from software engineering
• IDEF methods developed for the US Department of Defense
• Best practices from Semantic Web colleagues as well as our own experience in building large, operational systems

Examples ranging from a successful effort to support docents volunteering in a historic garden to finance and healthcare will be covered, with a focus on the Web Ontology Language (OWL). We will touch on patterns, including some that can be extended through rule systems that reuse the ontologies, which dramatically improves rule set quality, reduces error, and increases manageability / understanding of the rules. These patterns are particularly relevant in the context of scientific and finance applications. We will also briefly cover appropriate use of OWL DL, other OWL 2 profiles, and more expressive languages such as RuleML, to help potential users understand both the power and limitations they impose on applications in making such choices. Finally, we will provide an update on current trends in standardization of ontologies and the related infrastructure to use them in enterprise systems.

This tutorial provides a great introduction for those who are just beginning to “get their feet wet” in the field, and can be helpful in setting the stage for the rest of the conference.