What is an Ontology?

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In this post I ponder the definition of an ontology using the Semiotic Triangle as a guide. (Note that because business people do not understand what an ontology is, I prefer to call it a concept model.) I purposely gloss over the nitty gritty of taxonomy, generalization, specialization, dynamic classification, and so on, to focus on defining an ontology by what it provides to its consumers.

Before I talk about what it provides, I'd like to explain what goes into an ontology. An ontologist works with subject matter experts to develop and validate a conceptualization of the real world within a particular domain, such as finance, weather, or even music theory. The ontologist develops this conceptualization either by reusing existing concepts that other ontologists have defined, or by defining new concepts. The ontologist can generate structured English sentences to make it easier for the SMEs to understand and validate the ontology. Some examples of concepts might be Invoice, has line item, Wind, has speed, Chord, and has pitch. Regardless of who defines the concepts, the ontologist defines every concept using a predefined vocabulary of symbols, which is built on set theory and predicate calculus. These concepts are generally classes and properties, but can also included axioms expressed in a logic language.

So, why would an ontologist put that much effort into creating a conceptualization of the real world? There is a spectrum of reasons, ranging from the low end to the hard core. Here are some examples, ranked from the low end to the high end:

• A database for a business to track real-world things needs to reflect the real world as much as possible to reduce rework in the database and the programs that manipulate it.
• An enterprise architecture is a kind of an ontology about information, processes, roles, collaborations, and rules that allows business people to improve their business.
• IT systems with different databases and interfaces need a Rosetta Stone to communicate. This is called semantic interoperability.
  
• An expert system aids in the decision making of human professionals, such as doctors or pharmacists.
• An artificial intelligence learns by itself, simulates human reasoning, and answers questions.
  

All of these things require some kind of an ontology. My experiential sweet spot is in enterprise architecture and semantic interoperability, so I'll expound on them a bit more.

Many ontology consumers use an ontology about the enterprise to reason about their business so they can bring more value to their customers than their competitors. Being able to see how the business works in terms of a controlled vocabulary allows business people to optimize how they meet the needs of their customers.

Other ontology consumers augment the ontology about the enterprise with a Rosetta Stone for aligning disparate systems. How does that work? An ontology allows its consumer to understand the ontologist's conceptualization of the real world, link a data element in a system to an ontology concept to declare its real-world meaning, and follow a link from a data element to an ontology concept to determine its real-world meaning. Having this Rosetta Stone allows computers to automatically map information elements between systems, and it provides a well-thought-out, overarching structure for all information in an enterprise or a community.

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