The resources put forward in this part of the course all point to the same strategy: interdisciplinary data workers getting together, which will lead to new interpretations and applications. As such educational institutions will benefit from cross-polination on this topic.
Classification (especially for living objects), clustering all the information and removing ambiguity of terms is indeed an enormous task (language, semantics, hypes, cornering concepts...), yet at the same time we are already getting used to these methods (e.g. using Goggles). So the use of data results is immediate (which affects what needs to be learned, as old/new knowledge can change rapidly). Professional learners will be able to get to relevant up-to-date information much quicker.
The benefits for learning are enormous: it would not only provide me with personalized, tailored content that fits my current hunger for knowledge, it would also allow me to stay in close contact with those who provide that information and share it amongst those who have a similar interest. The professional groups will shift from a more localized network to real global networks that learn through connectivity (like we do here).
There is not only the personal learning which will benefit from the semantic web (getting relevant information ASAP), but also for professional groups, etcetera.
We - as educators or trainers - might even be in the possibility of creating a course which redesigns itself depending on the prerequisites and skills of a particular learner, thus giving her/him a much smoother learning path, without leaving the learning objective itself.
This approach of semantic learning might even take us out of the artificially divided classrooms. If we could cater lessons to a variety of learners, they would not be put into classes depending their age, but depending their ability to grasp what is necessary.
It will also facilitate research: just imagine, that you want to launch a new project in your scientific field? You need to write a proposal, and with an algorithm (AI friend) which searches in your scientific field (e.g.) scholar.google and cross-references this to the data bank of EU/WHO or B.& B. Gates foundation for funding that was granted... you could be on your way to get a funded post-doctorate or project going with much more ease.
However, I can see a potential downside: how much will it cost to access it? Will learning then turn towards: personalized and tailored to the ones that can afford it, and slow with more time demands for those with less money?
Overall, for me the semantic web will impact learning and ... innovation in a profound way.