Recently, a company developed a software product with some information architecture issues. Data was modeled as metadata, and a single term was used to mean different things in different places. At first glance, these problems seemed straightforward, but complex modeling issues lurked just below their surface. There’s even an ancient Greek paradox at play.
In this case study, we’ll borrow concepts from ontology modeling to diagnose what’s at the root of these messes. We’ll talk about how to identify and head off problems like these and explore what happens when we transfer the ambiguity of human thought to our computer systems.
Sharon is a UX researcher and designer at Intel, where she consults with internal teams on taxonomy, ontology, and content. Her research work has focused on employee information-finding strategies, and she has worked with Intel IT on enterprise-scale information systems, such as enterprise search and intelligent virtual assistants.
Previously, she was the ontology modeling lead at a semantic web start-up.
Her favorite category is rdf:Property.