This is possibly one of those things that I find obvious/assume that everybody is aware of. It definitely veers towards the philosophical edges of data science.
We are currently working on a knowledge graph at work. Trying to make the knowledge that has been accumulated over several years of curation of pediatric cancer cases more accessible to curators, clinicians and researchers. More accessible computationally speaking that is - governance of access is an entirely different subject. For the moment though, we have a lot of knowledge tied up in reports and case comments.
We have a fortnightly educational seminar which is not attended as well as it could be. I'm sort of tempted to pitch a talk to the chap that runs them, but I suspect the appeal would be ... limited.
The idea I'd like to get people thinking about is the Data - Information - Knowledge - Wisdom hierarchy. I know that philosophically speaking, it's not a thing that is universally accepted. Still, I think it's a useful way of thinking about our work.
Data: There is a ETV6:RUNX1 Fusion
Information: This fusion is diagnostic of some Leukaemia.
Knowledge: This fusion is treatable using <a drug>
Wisdom: We should treat it with <a drug>