If the result of the transformative nature of taxonomies and ontologies is automating core business processes, as Clarke implied, it’s spawned from the ability to make enterprise knowledge searchable. You cannot achieve the former without the latter, making the faculty for search no less transformative—and indebted to taxonomies—for KM. Without structured vocabularies, thesauri, synonym management, and other mechanisms that support taxonomies, organizations would rely on ad-hoc, unsustainable means of organizing their knowledge.
By effectively standardizing the terms by which enterprise knowledge is collected and stratified, taxonomies produce several transformative benefits. “People use them in peer review for sorting articles,” Hlava said. “They use them in sorting conference tracks. They use them in support of call centers. They use them in web navigation and webpage keywording. They use them to tag documents: not just the entire document, but the paragraphs, the figures, and the graphics.”
These applications are based on the structured terminology of taxonomies to describe enterprise knowledge. Most make the underlying content searchable. More granularly, taxonomies supply the words in which people think about knowledge, classify it, and, ultimately, make it available.
The transformative effects of taxonomies on KM are expanded when they’re coupled with ontologies. However, taxonomies need not involve ontologies. “If you’re just trying to organize data for knowledge management, the paths of other people, you don’t need the ontology,” Hlava remarked. “You only need the taxonomy.” In addition to providing schema and a conceptual data model, ontologies furnish an orderly structure for adding additional classifications and attributes to business concepts and entities. It behooves organizations to implement ontologies in standards-based environments—such as RDF and semantic knowledge graphs—in which constructs like OWL are designed for users to customize ontologies with their data.