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20 years ago, Tim Berners-Lee invented the World Wide Web. For his next project, he's building a web for open, linked data that could do for numbers what the Web did for words, pictures, video: unlock our data and reframe the way we use it together.

This document was an attempt to persuade CERN management that a global hypertext system was in CERN's interests. Note that the only name I had for it at this time was "Mesh" -- I decided on "World Wide Web" when writing the code in 1990.

A documentary by Kate Ray

Metaweb is a service that help you build your website around entities and not just words.

This document is designed as being a simple but comprehensive introductory publication for anybody trying to get into the Semantic Web: from beginners through to long time hackers. Recommended pre-reading: the Semantic Web in Breadth.

I've been following developments in intelligent tutoring systems for a while,  and find it interesting to see how researchers are combining artificial intelligence, learning theory, affective computing, and sensor networks to create applications that might prove to be useful and effective.

Here we've got a classmate PC demo that shows off Richard Beckwith shows off Classmate Assist which supports users seated or standing at the desk or table. This is an example of context aware computing. There are visual sensors that recognize the items on the table and instruct and walk the students through a series of educational tasks. The goal is to support existing curriculum and practices of teachers.

Hans Rosling's famous lectures combine enormous quantities of public data with a sport's commentator's style to reveal the story of the world's past, present and future development. Now he explores stats in a way he has never done before - using augmented reality animation. In this spectacular section of 'The Joy of Stats' he tells the story of the world in 200 countries over 200 years using 120,000 numbers - in just four minutes. Plotting life expectancy against income for every country since 1810, Hans shows how the world we live in is radically different from the world most of us imagine.

An entity graph of people, places and things, built by a community that loves open data.

Learning analytics is the use of intelligent data, learner-produced data, and analysis models to discover information and social connections, and to predict and advise on learning. EDUCAUSE's Next Generation learning initiative offers a slightly different definition "the use of data and models to predict student progress and performance, and the ability to act on that information". Their definition is cleaner than the one I offer, but, as I'll detail below, is intended to work within the existing educational system, rather than to modify it. I'm interested in how learning analytics can restructure the process of teaching, learning, and administration.

Today, we measure the size of the Web in exabytes and are uploading to it 15 times more data than we were 3 years ago. Technologies for sensing, storing, and sharing information are driving innovation in the tools available to help us understand our world in greater detail and accuracy than ever before. The implications of analyzing data on a massive scale transcend the tech industry, impacting the environmental sector, social justice issues, health and science research, and more. When coupled with astute technical insight, data is dynamic, accessible, and ultimately, creative. Marissa Mayer will speak to the power of data and the role it plays in Google's innovation. She will present on the technology trends that are changing our relationship with data, discuss fresh Google products that creatively put data to work, and offer her vision for the future of data in driving the Web forward.

Hilary Mason presents the history of machine learning covering some of the most significant developments taking place over the last two decades, especially the fundamental math and algorithmic tools employed. She also exemplifies how machine learning is used by bit.ly to discover various statistical information about users.

These, and other similar projects, promise the emergence of a new social and theoretical paradigm whose goal is to decipher the web of social interactions generated by social media.

After visualizing chat room dialogue earlier this week, I thought it might be neat to try and visualize some Twitter dialogue from the #LAK11 course.  For some reason I thought it would be simple to extract tweets from Twitter for analysis.  It wasn't!  So if you happen to know an easier way please leave a comment.

Ah… the semantic web. The saviour of the internet, and the evil empire enforcing its evil standardization upon my freedom. I've always been a little suspicious of this particular topic. Not that I'm opposed to any kind of stardardization, railroads and the lack of standardizations with bank cards at grocery stores come to mind (grrr…) But the semantic web and how data is 'linked' is pretty important to analytics. time to dive in.

Last week ReadWriteWeb asked: "Is Linked Data Gaining Acceptance?" Our answer: definitely yes. Projects like DBPedia, a community effort to structure the information from Wikipedia and provide it as Linked Open Data, have come a long way and work really well. For example, you can search for all scientists born in Zürich, Switzerland.