Back in September WolframAlpha unveiled its Personal Analytics for Facebook. With Personal Analytics, which The Semantic Web Blog covered here, you could visualize your networks, friends and social activities – and late last month it was updated to give even more insight into you and your Facebook linkages.

Not in the same way that Facebook does with its recently-launched Graph Search (see our story here). It’s not, for example, going to tell you who else out there likes running and lives in Nassau County, NY, or your favorite books that your friends also have read. In its initial debut, Personal Analytics for Facebook would show you things like gender distribution among your friends, or their common names, or who you share the most friends with.

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Heading into the Labor Day weekend, Wolfram|Alpha released a new feature that lets users perform personal analytics with Facebook data, for free. Users can head here and type in “Facebook Report” for an analysis of their Facebook data.

Stephen Wolfram, the creator of the computational knowledge engine, alerted the world to the news in this blog post. “When you type “facebook report,” Wolfram|Alpha generates a pretty seriously long report—almost a small book about you, with more than a dozen major chapters, broken into more than 60 sections, with all sorts of drill-downs, alternate views, etc.,” he writes.

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Last week speculation reigned about whether Google had set its sites on computational knowledge engine WolframAlpha, with the announcement that the search engine now is using WebGL technology for enhancing users’ ability to interact with complex, compound math functions. The search giant in December added 2-D graphing to its delivery of computed answers for calculations typed into its search box, and the most recent update means users now can plot and manipulate 3D graphs.

In addition to Google just wanting to own as much of search as possible – and increasingly to want to be a more semantically-enabled answer engine for user queries – discussion pointed to the fact that Wolfram Alpha is integrated with Apple’s Siri technology to help deliver factual answers to iPhone  user queries. And Google itself reportedly is working on a Siri rival in a project code-named Majel that potentially could one-up Siri when it comes to delivering answers to requested information. Not to mention the recently publicized – and both lauded and lampooned – Project Glass, which has been described here as Google’s Siri for your eyes. (See the video here.) As of February, according to the NY Times, Siri accounted for 25 percent of all searches made on WolframAlpha.

WolframAlpha decided to make some more news of its own yesterday, following an already busy first quarter that saw, among other things, the launch of Wolfram Alpha Pro, a fee-based service that lets users compute with their own data, get dynamic versions of existing Wolfram|Alpha output, and download what WolframAlpha computes as data.

Now it’s added to its repertoire a feature that provides some computational insights into the work of the immortal Bard.

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You’ve probably read a couple of hundred remembrances and memorials to Steve Jobs in the last day. Don’t worry – this little blog isn’t going to rehash each of his amazing achievements.

Rather, perhaps the sad news of his passing might provide an opportunity to reflect on what it means to innovate, and what it means to be an innovator. Apple’s well-known mantra – Jobs’ coaxing of his fans to “think different” – isn’t just something we’ve seen played out in the design of that company’s products, or in the sheer genius Jobs had for tapping into the zeitgeist, turning it around, and building a business model out of it.

Certainly those are the most obvious fruits to most people. But the work the Semantic Web community is doing exemplifies the “think different” attitude every day. That’s true of products like Apple’s Siri that bring some (now) in-house semantic smarts to Jobs’ creations, as well as a host of others whose creators hope to harness new opportunities from Jobs’ tablet revolution.

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Photo Courtesy: Flickr/ceslava.com

eBooks are cool, but they could get even cooler with EPUB3, the next version of the widely adopted distribution and interchange format for digital books (well, except for Amazon). The latest version of the standard could make it easier for publishers to more flexibly represent their offerings to digital book retailers, and add a lot of excitement to the eBook reading experience, too.

EPUB3 is based on HTML 5 and was proposed to include RDFa. RDFa is in question for eBook metadata now, however, though there is still the possibility to embed RDF/OWL within eBook content. (Membership comments on EPUB3 are due in by Aug. 22). EPUB 3 requires the same three metadata elements as EPUB 2, which are dc:identifier, dc:title, and dc:language, while also permitting many more. “We left it open to using something like RDFa so you can put in what you need to,” says Eric Freese, solutions architect at digital publishing solutions vendor Aptara. That could include, for example, using the PRISM (Publishing Requirements for Industry Standard Metadata) XML metadata vocabulary for managing and aggregating publishing content, or ONIX metadata for representing and communicating book industry product information.

However the RDFa question fares, one thing that is increasingly clear to publishers that have done any looking at all into eBooks, Freese says, is that “it doesn’t take long before they get hit in the face with the metadata problem. And as more time goes by there are fewer and fewer publishers who haven’t thought about doing eBooks.”

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The world’s waiting to see how IBM’s Watson will fare against past Jeopardy! champions Ken Jennings and Brad Rutter. The battle of the brains – real and digital – takes place next week, and we here at The Semantic Web Blog will be keeping you up to date with coverage of the big event. (Yes, not all show recap blogs have to be about American Idol or Dancing With the Stars.)

The topic has, of course, been a hot one in the Semantic Web trenches. Heck, it’s been a hot one in the general press. Will the NLP, machine learning, knowledge representation and reasoning, and deep analytics algorithms invested in this massively parallel QA system that counts terabytes of storage and thousands of POWER7 computing cores enable it to beat its human competitors to the buzzer with the right answer? As of this writing, some 54 percent of voters responding to a poll here thought Watson would emerge as the winner of the Jeopardy! IBM Grand Challenge. Rutter, who’s won more money on Jeopardy than anyone else, held 28 percent and Jennings, who went undefeated longer than any other contestant, was clocking in at 18 percent.

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