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I do like the Gutierrez and Sequeda approach of:

1) A short characterization of the issue of using technology to realize value from Data and Knowledge (we could use a ‘semantic technology value proposition’ graph and John’s hexagon);

2) Then have ‘decades’, with something like their accomplishments and foci followed by ‘realizations’ and ‘limitations’;

They cover ‘Data’, ‘Knowledge’, and ‘Knowledge + Data’. That’s a good start at articulating the elements, but it should go a little farther. In particular,

1) It conflates the conceptual knowledge or theory about a domain necessary for an agent to operate in a way an observer would deem ‘intelligent’ (Newell’s criterion as emphasized by Musen) with the logical theory used to *formalize* the knowledge into a formal theory so it can be validated and a machine can operate on it.

2) Along with that conflation, they don’t emphasize enough the software/agent/program/algorithm that will use the cleaned/organized/processed data as an inseparable complement (dual?) to the data. As David Eddy just wrote in his email to Ram, “data doesn’t exist without software”. This software hare a strong logical aspect, but it is not identical to logic.

3) John’s (and his other presentations) can help us think about how to frame the elements of the history in a way that ends up with CLIP and DOL as the KG/ontologies state of the art.

4) We do need to work on a characterization of ontology beyond what John has there as “ Ontology is a catalog of words and the kinds of things they refer to.”