I think that the even more powerful pitfall of that web scenario would be plain and simple lack of truthfulness. Machine readable lies. If you are old enough t

I think that the even more powerful pitfall of that web scenario would be plain and simple lack of truthfulness. Machine readable lies. If you are old enough then you will remember a time when SEO wasn't given a name yet, and mostly consisted of spamming the head tag with untrue META tags. The entire idea of the semantic web is basically a hypothetical extrapolation of the assumption "what if META didn't fell victim to lies?" But that idea quickly evolved away from that web use case full of deliberate deception and evolved into technology for interoperable knowledge representation. The "web" use case quickly turned into the science funding equivalent of spamming META tags: systems (decision-makers) that were still falling for it where considered so far behind that influencing them with that method did not even feel like lying. Interoperable knowledge representation isn't valuable because you might want to plug together random knowledge bases (you wouldn't), but because it would be an enabling technology to build one knowledge base on top of another (or on top of multiple others). This would be particularly valuable when modeling is done in short-lived iterative steps with changing teams, organisations and goals, like the quick iterations of student generations that each push ahead their niche of science with some miniscule contribution to progress. With sem-web tech, one generation of knowledge modelers would be able to do their work on top of the work of those who came before them, without being restricted to the technology of those earlier generations. Think of the "web" in "semantic web" as a big spelling error of "stack". (source: did my diploma during peak semantic web, shoveling OWL from a Java DOM into a Lisp server to brute force maximal consistent subsets of an inconsistent superset in fantastically un-scalable ways)