I'm working on a research project to develop an ontology for wetlands in PROTEGE, but I have doubts about the relationship between ontologies and knowledge management, I understand that ontologies are used for the representation of knowledge, but I can not find an academic text about the relationship between ontologies and knowledge management, specifically I find information on knowledge management.

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    I don't think that this question is a good fit for this site. They claim that dba.stackexchange.com is supposed to be for 'data professionals', even with the domain name that makes it look like it's just for RDBMS administrators. The Information Science site (which went under) would've been an even better site for this question. – Joe May 18 '16 at 17:20
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    Oh ... and ontologies are just a type of system that can be used for storing information, which can include the type of information of interest in knowledge management. – Joe May 18 '16 at 17:40
  • Perhaps Wood, D. (ed.) Linked Enterprise Data is related to your question. Probably MDM (Master Data Management) is the most prominent application of ontologies in knowledge management. – Stanislav Kralin Jun 23 '17 at 20:50

There are a lot of different definitions of "ontology" out there. In my opinion this here is highly relevant in practice:


See this article for a formal discussion (ignore the "math", read the text).

For concept and conceptualization (conceptual model) see Wiki-pedia or page 15 in the reference above (semiotic triangle).

Therefore the most interesting questions in creating an ontology is, which competency questions (see the section in ontology development 101) do you want your model or knowledge base to answer?

That settled, what does it have to do with knowledge management?

Wikipedia defines Knowledge Management as:


So ontologies can only be a tool in knowledge management (KM). So how do they help with KM?

Wherever you annotate data with terms from your ontology, it becomes more findable, accessible, interoperable and re-usable (see FAIR data principles) for humans and machines alike.

In addition it is easier to connect your data with other information (they facilitate data integration).

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