The semantic web can be quite a hard concept to grasp when discussed in an abstract way: the above video is a particularly useful, clear exposition of the enormous promise and power the future of knowledge sharing holds.
Parallax, a novel browsing interface designed by David Huynh to manipulate Freebase, shows how contextual connections can be made with machine readable data to provide a much richer results set which in turn can spawn fascinating visual representations, and more.
Freebase is the foundational 800lb gorilla in the semantic space, quietly building momentum to create a 'global knowledge base: a structured, searchable, writeable and editable database built by a community of contributors, and open to everyone....It could be described as a data commons'.
Still technically in alpha, Freebase will be the underpinnings of many future companies - some would say this approach is the future of the entire Internet.
It’s built by the community and for the community – free for anyone to query, contribute to, build applications on top of, or integrate into their websites - basically an open database of the world’s information.
Freebase covers millions of topics in hundreds of categories. Drawing from large open data sets like Wikipedia, MusicBrainz, and the SEC archives, it contains structured information on many popular topics, including movies, music, people and locations – all reconciled and freely available via an open API. This information is supplemented by the efforts of a passionate global community of users who are working together to add structured information on everything from philosophy to European railway stations to the chemical properties of common food ingredients.
By structuring the world’s data in this manner, the Freebase community is creating a global resource that will one day allow people and machines everywhere to access information far more easily and quickly than they can today.
The 'people operated' side of things is the world we live in today. As David Huynh's video discusses, we busy ourselves manually searching by keyword in multiple locations and then compile our results.
Google is essentially a media company - as Tom Foremski succinctly points out here - logging your actions for Ad Word generation like a supermarket rewards card program while leveraging brute force search of the indexed web as you search for your keywords and phrases.
Wikipedia is essentially a single destination site, which means lots of laborious single issue searching.
The semantic web is a vision of information that is understandable by computers, so that they can perform more of the tedious work involved in finding, sharing and combining information on the web.
This semantic, machine-read next generation enables much richer search. So if you are looking for information about pinball machines for example, this Freebase example gives you a rich contextual grouping of related and highly relevant information.
Machines doing all the work is the next generation - humans asking questions of HAL is still a very long way off (fortunately) but the power illustrated today by the Parallax browsing interface, which is accessing Freebase to leverage its powerful range of connections (enabled by accessing 'multi-typed data') is highly impressive.
You can try the Parallax search interface here, although at this point it is slow (it does cache your results however). Enterprise search is notoriously hard: this level of functionality will ultimately have a major impact on find-ability in large enterprises.
There is much more to Freebase than this fascinating parallax browsing interface - I highly recommend taking the time to explore and contribute content!