Taxonomies and Knowledge Management

As taxonomies and ontologies become more widely adopted by organizations on the enterprise level, we see that these semantic structures are integrating and supporting knowledge management to a greater degree. I was recently invited to give a presentation with the title “How Taxonomies and Ontologies Drive Knowledge Management” https://www.hedden-information.com/wp-content/uploads/2026/09/Taxonomies-and-Ontologies-Drive-Knowledge-Management.pdfwas at the Progress Data Platform Summit, which was held September 15-16.

Knowledge Management

Knowledge management (KM) is the process of identifying, organizing, storing, and disseminating information within an organization to improve organizational knowledge. It’s related to information management, but it goes further than organizing and providing access to information by address how to enable people and organizations to better share, retain, find, apply, and improve knowledge. 

KM addresses all forms of knowledge: explicit knowledge, which is documented or in databases; implicit knowledge, which include task steps and know-how people have but are not yet documented; tacit knowledge, which includes personal experience-based knowledge; and embedded knowledge, which is built into routines and standard operating procedures. One of the goals of knowledge management is to capture and document these latter three forms of knowledge.

Knowledge management has various components. Most fundamentally, it includes people, processes, and technology. KM also includes information, organizational structure, and corporate culture. The tasks related to knowledge in KM can be considered as part of a KM lifecycle, starting with capturing or created knowledge. Other lifecycle steps include storing, selecting, curating, sharing, finding and applying knowledge.

There are many benefits are KM, which is typically a program that could be a small department, along with others, under a chief information office (CIO).  These include improving decision-making, problem-solving, innovation, employee productivity, organizational learning, capability development, onboarding, quality, and operational performance. KM also reduces duplication, wasted effort, and organizational risk. KM. retains critical organizational knowledge and makes better use of a company’s intellectual assets.

Taxonomy alignment and support for Knowledge Management

 
Taxonomies are a valuable tool in making information findable and discoverable. Once the desired information is retrieved and compiled, it can be interpreted, compared, analyzed, and integrated with other information or data to create new knowledge.

Taxonomies are highly relevant to managing explicit knowledge. They also have the potential for helping capture and manage tacit knowledge. By having a taxonomy in place, it can facilitate the task of identifying and then documenting tacit knowledge.

Taxonomies also support KM through its various components:

• People – Taxonomies are a good way to involve people in KM. The creation of taxonomies engages stakeholders, who contribute to the taxonomy through activities of brainstorming, card sorting, and answering interview questions.
• Processes – Building and updating taxonomies involves certain processes of research, testing, feedback, and approval.
• Technology – Taxonomy management, automated tagging, and user-interface implementations all require technology, which connects to the other systems involved in KM.
• Information/content – The main purpose of taxonomies is to make information or content findable.
• Culture – The choice of taxonomy concepts and their labels reflect corporate culture. Taxonomy creation can reaffirm or challenge the choices.

Taxonomies may support, to varying degree, most processes or stages of the KM lifecycle. The following list synthesizes life cycle stages from various KM theories and suggests how taxonomies or at least controlled vocabulary metadata is a part of each process.

Knowledge Management Lifecycle

 

• Identify and capture knowledge – Pre-existing tagging of taxonomy/controlled vocabulary can facilitate the identification and capture of explicit knowledge, especially from external sources.
• Create knowledge – The creation of an enterprise taxonomy or another knowledge organization system is also a form of knowledge creation.
• Compile, store or archive knowledge – Typically some metadata is applied to facilitate archiving.
• Filter or select knowledge – If knowledge assets have metadata from controlled vocabularies, they can be filtered by metadata terms to facilitate selection.
• Curate, transform, codify, or refine knowledge – This is where comprehensive enrichment of the knowledge assets by tagging with taxonomy terms and other metadata make them more accessible.
• Share, distribute, or disseminate knowledge – Taxonomies that are linked to each other enable the sharing of knowledge more broadly, from different sources and into different end-user applications.
• Access, find, and retrieve knowledge – This is where taxonomies are utilized to their fullest and are most clearly beneficial in supporting various methods for findability and retrieval with search matches, hierarchical browse, and faceted browse/search.
• Use, apply, integrate, or implement knowledge – While taxonomies are primarily used for information retrieval, they can also play a role in the analysis and comparison of information.

The work of creating taxonomies is increasingly included within KM work, but, more significantly, taxonomies and ontologies can serve as tools for KM work and potentially even drivers of KM in their alignment with trends in KM. These trends includes the integration of Generative AI, conversational answers and recommendations to questions, an emphasis on information quality, the adoption of knowledge graphs and semantic layers, and the implementation of retrieval augmented generation (RAG) and Graph RAG, and the capture of tacit knowledge.