[Editor's note: this guest post was co-written by Héctor Pérez-Urbina (Clark & Parsia) and Juan Sequeda (Capsenta)]

Image of a human brain with computer data overlay.Important enterprise business logic is often buried deep within a complex ecosystem of applications. Domain constraints and assumptions, as well as the main actors and the relations with one another, exist only implicitly in thousands of lines of code distributed across the enterprise.

Sure, there might be some complex UML diagrams somewhere accompanied by hundreds of pages of use case descriptions; but there is no common global representation of the domain that can be effectively shared by enterprise applications. When the domain inevitably evolves, applications must be updated one by one, forcing developers to dive into long-forgotten code to try to make sense of what needs to be done. Maintenance in this kind of environment is time-consuming, error-prone, and expensive.

The suite of semantic technologies, including OWL, allows the creation of rich domain models (a.k.a., ontologies) where business logic can be captured and maintained. Crucially, unlike UML diagrams, OWL ontologies are machine-processable so they can be directly exploited by applications.

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