What I understand about the semantic web is that it:
-- relies on metadata that codes the metaphysical identity of a piece of data and how it relates to other things or concepts. Is it an image? a person? an idea? An author? This reminds me of bibliographic cataloging in libraries. ("The Semantic Web: An Introduction")
--exists on a very small scale currently ( Tim Berners-Lee's TED talk).
--would allow us to find and visualize relationships between any two bodies of information, whether the information is a person or an image or a body of raw data.
--would allow the implementation of learning analytics on a much more far-reaching scale.
This is what I understand and it isn't much, but what I don't understand is a lot. I really did not understand the "semantic web: an introduction" paper, nor the specifics of Hilary Mason's talk, but I found it fascinating none the less, and was particularly pleased that she used a disease-related example to illustrate Bayesian statistics. I made a connection from that to the concept of evidence-based medicine which I've also been learning about in the past couple of years.
Still need to watch Dragan Gasevic's presentation from last week. Perhaps it will make all things clear.