Although taxonomies have become increasingly common within enterprises and on websites, they are not always well understood. Taxonomies are sometimes confused with other knowledge organizations systems, such as classification systems, website navigation schemes, business glossaries, or ontologies.
A taxonomy is a controlled, structurally organized set of unambiguous concepts, which may describe content, information, or data, and which users may be interested in querying about. A taxonomy links users to the information they seek by bringing together various users’ terms with the terms that occur in the content or data. Prior to the emergence of modern taxonomies in applications for digital information, indexes at the back of printed books had been serving a similar role (and they still do). I have already written a blog post on Taxonomy Definition, so to further clarify what taxonomies are, it is also useful to explain what taxonomies are not.
Taxonomies are not the same as classification systems/schemes (such as industrial classification codes for economic analysis or medical classifications for health data collection or health insurance purposes), as the latter have mutually exclusive classes to which items are assigned for non-redundant analysis. Classification thus allows comparison, analysis, identification, location, and other actions associated with things based on their class. Taxonomies are organized sets of concepts tagged to content or associated with data, where the taxonomy organization serves merely for finding the desired concept or providing context for tagging. Thus, a concept may have more than one broader concept and thus appear in more than one place in the taxonomy hierarchy.
Taxonomies are not the same as navigation systems, which are common in websites or web applications. A taxonomy is more similar to an index, while a navigation system is more similar to a table of contents. Menu labels in a navigation can link to only one page, whereas concepts in a taxonomy are tagged to multiple pages, content items, or data records. Navigation systems are only used in browsing, but taxonomies may be both browsed and searched for their concepts. Navigation systems reflect paths and established links to content, whereas taxonomies comprise concepts that become metadata when tagged to content. Navigation systems, like classification systems, are not frequently or easily changed, whereas taxonomies can grow and change continuously, as needed.
Taxonomies are not the same as business glossaries, which are lists of terms of relevance to an organization’s business along with their definitions, although there is usually considerable overlap between the terms an organization gathers for its glossary(s). Not only is there usually the difference of a taxonomy’s hierarchical structure (although categories could be assigned to glossary terms), but the ultimate objectives differ, resulting in differences of scopes of term inclusion. A business glossary includes all terms of importance to the business but may not be understood by everyone, so definitions need to be provided. There could be terms of importance, that need no definition, such as Marketing, so they are not included in the glossary. Technical terms and acronyms are usually included. A taxonomy, on the other hand, includes only the terms/concepts of which there are sufficient documents, pages, or content items to be tagged for retrieval. Sufficient content on a subject is a leading criteria for including a concept in a taxonomy.
Finally, taxonomies are not the same as ontologies. The confusion between the two may arise because taxonomies and ontologies are increasingly used in combination, and software (now referred to as TOMS for taxonomy-ontology management system) allows you to create a taxonomy and ontology as a single project or knowledge model. An ontology can be an upper-level model of a knowledge domain, but domain-specific ontologies may include multiple hierarchical levels of subclasses, and thus include what are essentially taxonomies. A taxonomy, however, can stand on its own without an ontology and serve the functions of tagging and retrieval via browsing and/or searching without the extension of an ontology. Ontologies support complex, multi-part queries involving reactions, and they support reasoning and inference, which taxonomies do not. Each utilizes different data models: SKOS for taxonomies and RDFS and OWL for ontologies.
Prior blog posts I have written that compare taxonomies to other knowledge organization systems in more detail are:
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