The Semantic Web Journal is running a 10 year anniversary edition, and Jerome Euzenat wrote a very nice piece for that special issue, entitled “A map without a legend“. It’s actually a rather bold an unashamed case for the explicit representation of knowledge:
- Jerome articulates very clearly the value of explicitly expressed knowledge, both in humans and machines, in forms that can be communicated (as opposed to actionable but implicit knowledge that has to be relearned all the time).
- He unashamedly expresses the ambition that such explicit knowledge, in formats that are interpretable by machines, can contribute to the next step in the knowledge ecosystem (in a progression from storytelling to teaching, book writing, monasteries, universities and semantic webs)
- He uses eScience as a good illustrator for what could be achieved (a good choice, because eScience is a field where more progress in “real semantics” has been made than elsewhere
A minor complaint would be that the final section on knowledge dynamics (and the role of evolutionary mechanisms in knowledge dynamics) is rather disconnected from the main thesis of the rest of the paper.The whole “in defense of explicit knowledge” argument of the paper could have been done without that final section.
Finally, I’d like to point out that Euzenat’s whole argument about the value of explicit knowledge in a form processable by machines is also very relevant to the major debate that’s raging currently in Artificial Intelligence: should we not just fully rely on statistical techniques that learn actionable patterns from data. This paper is a clear articulation of the viewpoint that the answer to this question is ‘no’:
“Nowadays, web users are not expected to provide knowledge, nor to access it. It seems that they are mere data provider, mostly through their actions, e.g. click, buy, like. These data are machine processable, but not open. They are kept secret, in silos, to the exclusive exploitation of a single organisation. They are processed by corporations which eventually learn knowledge from that data. But this knowledge, in turn, is not shared nor even prone to be communicated because not necessarily expressed in an articulated language. Instead, it is directly actioned. Hence, knowledge does not improve.”
Amen to that.