Image via CrunchBase

With Facebook’s IPO just around the corner, the timing of Google’s latest press blitz should probably be regarded with a healthy dose of suspicion, but the unveiling of the Knowledge Graph is an important step in Google’s journey — and a reaffirmation of values diluted by recent dalliances in social networking. Writing for The Atlantic, Alexis Madrigal perhaps describes it best;

“To me, this update is the epitome of what Google does best. The graph makes the process of Googling something faster, easier, and better. The corporate imperative to keep people searching on Google in the face of renewed competition matches up very nicely with consumers’ desires for the best, fastest search experience. That hasn’t always been the case with the company’s social search integration, so this update feels so refreshing. It’s like a friend in the midst of a midlife crisis returning the Porsche and embracing a trusty new four-door.”

(my emphasis)

Exactly. As I’ve written before, I strongly believe that semantic smarts should be hidden very, very deep, and that semantic technologies are at their best when they quietly and unobtrusively make some existing process better. That’s why I like TripIt so much. It gets travel plans into my calendar faster and more accurately than I could type them, and throws in a whole heap of added value as a byproduct of the data ingest process.

Google’s Knowledge Graph is similar; it works with existing search behaviour, and unobtrusively adds a little extra value.

It’s going to be fascinating to see which direction Google takes this capability, and my latest column for SemanticWeb.com explores that in a little more detail.

Those (like me) based outside the US need to remember that none of this works on sites other than google.com right now.

And if you’ve not seen Google’s introductory video, take a look.

Related articles

• With Knowledge Graph, Google Can Finally Tell The Difference Between Apple Inc. And Apples(fastcompany.com)

  ---

• Google Goes Back to What It Does Well: Finding Things(readwriteweb.com)

Computer rendering of the Chicago Spire. This is not the current design as of July 12, 2008. (Photo credit: Wikipedia)

We have become accustomed to the simple yet all-powerful search box. ‘Advanced’ search options and arcane query syntaxes have largely been replaced by the learned behaviour of throwing some words at Google*, ignoring the sponsored links, and (usually) finding what we want somewhere in the first 5-10 proper results. A Google search is certainly impressive (especially to those who really remember how poor some of the earlier search engines were), but it remains far from perfect. Do Google’s limitations create a big enough opportunity for others to grab credible market share?

In recent weeks, I’ve received a flurry of information on partial alternatives to Google’s market-dominating search engine. Most appear useful in their own niche, but I doubt even their creators would be surprised to learn that none tempt me to change my Google-powered default search behaviour.

Far more damaging for their prospects, any hope they had of attracting my occasional use is dashed by the very way that they seem to work. They may excel in certain verticals, or in particular types of search, but most make the unfortunate mistake of expecting me to mould my behaviour to them. The pain of remembering how to concoct effective queries for each of these tools far outweighs the gain of their ‘better’ search result, creating a vicious spiral from which they must surely struggle to escape.

Take London-based Sehrch, for example. Behind a name that’s impossible to pronounce or communicate to others (say “Search for that on sehrch,” and 99.99% of those you tell will end up here rather than here) lies an interesting attempt to bring structure to web search, with a little help from data sources like Freebase and DBpedia.

Google could probably find you buildings with 150 floors (just the Chicago Spire, according to both my first page of Google hits and the trusty Wolfram Alpha), but might struggle to find those that were higher. Sehrch finds 14, and they appear in a neat list that’s free of the other stuff that cluttered my Google results. I’m confused that the Chicago Spire (sehrch agrees that it has exactly 150 floors) appears in a search that was quite clearly looking for buildings with more than 150 floors, but the other 13 appear to be valid. I’m not a tall building aficionado, so don’t know how many buildings Sehrch failed to find, but it certainly did better than Google (where the results are a mess, and would require careful reading) or even Wolfram Alpha (which reckons there are two ‘notable’ buildings with more than 150 floors). All of the searches returned a mix of actual buildings, planned buildings, and cancelled buildings.

But — and it’s a big but — both Google and Wolfram Alpha were pretty straightforward to search with normal search behaviours. Sehrch was not.

Wolfram Alpha took a perfectly realistic plain-text search for “buildings with more than 150 floors” and interpreted it to arrive at a query that the system could understand and operate upon. Sehrch, on the other hand, expected me to build a query from the 130,342 object properties and 249,777 object types that it understands. Frankly, if this search hadn’t been one of the examples, I doubt that I’d have formulated (type:building) (floors>150) correctly.

Extracting meaning and structure from data, and making it available to deliver better search results is a valid and useful thing to be doing. If you want to know about female teenage pop stars from Sweden, Sehrch can give you six. Both Google and Wolfram Alpha might be able to get there too, but I gave up trying to work out how. Sehrch may be returning ‘better’ results, but it’s too different to use.

Wolfram Alpha understands the power of meaning and structure too, but is getting better at hiding the power behind pretty user-friendly queries.

Even Google, the home of brute force computation across the unstructured mess of the Web, recognises the power of meaning and structure, and is doing something about it.

Enter some maths into a Google search box, and you don’t get a list of web pages containing calculators. You get the answer.

Enter a flight code into a Google search box, and you don’t get a list of airline or airport web pages. You get the time the flight is expected to land.

Enter a stock market code into a Google search box, and you don’t get a list of stock exchanges or companies. You get the share price, and a graph showing how it’s changing.

Type ‘showtimes’ into a Google search box, and you get a list of films showing at cinemas near you.

Google is getting better at structure. The company bought Freebase. The company is one of those behind schema.org. It’s investing in WikiData. Google knows that structure and meaning matter, and it’s applying itself to baking both into the search experience with which users are already familiar. Google is getting better, but it’s improving by doing more to anticipate the user’s needs, not by forcing the user to adopt arcane query syntax.

I use Google every day. For some searches, it’s really not (yet) the best place to answer my query. In those situations, I’ll turn to some other tool. Am I going to turn to one like Wolfram Alpha which works in a very different way, but hides that behind a box that typically takes the queries I’m used to typing? Or am I going to turn to one like Sehrch, which works in a very different way and expects me to work in a different way, too?

Sadly for Sehrch, until it finds a way to hide search syntax from the casual user, all its clever search capabilities are going to go unused. And it’s not alone. As I mentioned at the start, I’ve received pitches from a load of similar companies recently. All are interesting. All expect me to change too much without offering enough benefit in return. All therefore, ultimately, fall short.

Structure is good. Meaning is powerful. But I want the computer to infer, discover, reason and suggest. The last thing I want is to go back to typing arcane search syntax. And I very much doubt that I’m alone.

Note: Yes, I know that other big-name search engines like Bing exist and are broadly comparable to Google in scope and capability. But, honestly, they’ve never demonstrated a compelling reason for me to switch away from Google either. Feel free to substitute the name of your favourite mainstream search engine everywhere I wrote ‘Google’.

Related articles

• Siri makes up 25% of all Wolfram Alpha searches (venturebeat.com)

But as Kasabi CTO Leigh Dodds is keen to stress, you don’t need to be a Semantic Web developer or enthusiast to derive value from what Kasabi has to offer.

Like many others in the nascent data market space, Kasabi’s commercial models are still emerging, and Leigh shares some of the thinking that lies behind their current proposition.

There is some background noise on this recording, which will hopefully not affect your enjoyment of the conversation.

Kasabi is an initiative of Talis. I am a former employee of and current shareholder in Talis.

Following up on a blog post that I wrote at the start of 2012, this is the ninth in an ongoing series of podcasts with key stakeholders in the emerging category of Data Markets.

Related articles

• Data Market Chat: the podcasts are a-coming…(cloudofdata.com)
• Data Market Chat: Tyler Bell discusses Factual (cloudofdata.com)
• Data Market Chat: Hjálmar Gíslason discusses DataMarket.com (cloudofdata.com)
• Data Market Chat: Chris Hathaway discusses AggData (cloudofdata.com)
• Data Market Chat: Flip Kromer discusses Infochimps (cloudofdata.com)
• Data Market Chat: Nick Edouard discusses BuzzData (cloudofdata.com)
• Data Market Chat: Stephen O’Grady of RedMonk examines the bigger picture (cloudofdata.com)
• Data Market Chat: Shion Deysarkar discusses Datafiniti (cloudofdata.com)
• Data Market Chat: Piyush Lumba discusses Microsoft’s Windows Azure Marketplace (cloudofdata.com)

Richard Wallis

Our conversation is also an excuse for an experiment. I have been producing audio-only podcasts here and elsewhere for a number of years, but have always tended to avoid producing video. It’s more effort, it requires more bandwidth at both ends of the conversation, and I’ve never really been convinced that it adds very much to a conversation between two people. Anecdotal evidence would also suggest that my current podcasts are consumed in environments where video would not work; washing dishes, walking dogs, and sitting on buses.

However, rather than just continue to presume that my biases are correct, I’ve decided to give video a try. Richard kindly agreed to participate, and the result is available on YouTube and embedded here.

An audio-only version is also available for download if you prefer. The introductory remarks in this version are slightly different to those on the video, as they come straight from the original conversation.

It’s perhaps unfair to draw too many conclusions from this first attempt, but a few things are immediately apparent. The whole process takes an awful lot longer. The files are larger, so processing and uploading times increase 2-3 fold. Uploading a separate audio file also takes a bit of time. Simply dumping the Skype recording into iMovie worked just fine… but I’ve (so far) not managed to find any way to balance the audio levels. Garageband lets me do this with my audio-only podcasts, but iMovie doesn’t seem to, so Richard’s side of the conversation comes across as quite a bit louder than mine.

Having done one, I’m still not convinced that the video adds anything to the conversation. But what do you think? If you’ve listened to any of my podcasts, please take a moment to complete the short survey over at SurveyMonkey. Your responses will help me to decide where to go next.

Many thanks.

Image via CrunchBase

Chris Hathaway sees basic location information scattered across the websites of hundreds — or thousands — of coffee shop chains, hotel groups, and fast food joints, but argues that it’s almost impossible to do anything more sophisticated with the data than find your closest Starbucks. His company, AggData, is attempting to fill what he sees as a gap in the market; scraping addresses and other facts off company websites to create simple files of store locations that can then be enriched with coordinate data and sold.

Customers for this data include competitors, market researchers, consultants, and even the companies themselves; as is so often the case, it can be easier to buy data on store locations from a third party than to find the authoritative sources within your own organisation. AggData is strongest in the US today, but also offers a growing body of data for other countries. Although the data files are structurally simple, Chris sees plenty of opportunity to continue collecting and selling data to a growing community of customers.

Unlike Factual, which was the focus of last week’s podcast, AggData is not currently interested in combining data from different sources. Customers download separate files on the locations of Starbucks, Peets and Tim Hortons, and not a single aggregated set of coffee shop locations. The AggData model is also predicated upon using their own scripts to extract data from third party sites; asked if he would accept a file of WalMart store locations supplied by WalMart, Hathaway explained why he would — and does — decline.

Have a listen to learn more about AggData, and to hear Chris’ perspectives on the potential role of semantic technologies in making his job easier. And check back on Thursday for the next podcast in the series; Hjálmar Gíslason of DataMarket.com.

Following up on a blog post that I wrote at the start of 2012, this is the second in a series of podcasts with key stakeholders in the emerging category of Data Markets. Other conversations, all of which will be published here, have been scheduled with BuzzData, DataMarket.com, Factual, Infochimps, Kasabi, and Microsoft. I am still adding conversations to the series, and intend to talk with more companies and with analysts and investors with insight to share. 

Related articles

• Nurturing the market for Data Markets (cloudofdata.com)
• Data Market Chat: the podcasts are a-coming… (cloudofdata.com)
• Data Market Chat: Tyler Bell discusses Factual (cloudofdata.com)

Image of Stephen Wolfram via Wikipedia

British-born computer scientist Stephen Wolfram sees ongoing efforts to extend the Internet’s top-level domains (TLDs) beyond the familiar .com, .org, .uk etc as an opportunity to raise the profile of machine-readable data. In a blog post published yesterday, he argues that a new .data domain would increase “exposure of data on the internet—and [provide] added impetus for organizations to expose data in a way that can efficiently be found and accessed.” Whilst wholly in favour of Wolfram’s stated aim, I can’t help feeling that his suggested solution is at best unnecessary and at worst a worrying segregration of data from the ‘proper’ web that everyone else will continue to exploit.

Back in June of last year, the body responsible for coordinating the global domain name system approved a plan to permit new top-level domains (the letters after the final dot in an internet address — the .com in cloudofdata.com, the .uk in bbc.co.uk, the .edu in harvard.edu). Until recently, these top-level domains have been tightly controlled, with a small set of generic domains (.edu, .gov, .mil, .org, etc), a larger set of country domains (.uk, .fi, .nz, etc) and one or two others such as .eu. From tomorrow, anyone with $185,000 will be able to submit a proposal to create and manage a new top level domain, and it’s possible that there could eventually be thousands of them. Wolfram is keen to ensure that data doesn’t miss out on the ‘opportunity.’

As Wolfram himself recognises, there is already an awful lot of machine-readable data on the web. Some of it sits embedded within the web pages that humans read, with specially formatted code waiting to be triggered by the calendars, the address books, or the browser plugins of site visitors. Some of it is packaged up in data files, offered for download. And some of it waits inside a database, ready to be delivered in response to an API call or a query typed into a web form.

There is a growing enthusiasm for exposing this data for reuse. Government transparency agendas have driven public sector data sites like data.gov.uk and data.gov. Similarly, efforts such as data.open.ac.uk and data.southampton.ac.uk see universities beginning to consciously collect data sets together and offer them up for reuse. Similar efforts in the commercial world are less easy to point to, but that reticence has nothing whatsoever to do with the lack of a ford.data, boeing.data, ge.data or astrazeneca.data domain!

In some ways, the convention for gathering significant chunks of data on a data.xxx.yyy site echoes Wolfram’s intention, but with a number of advantages. Data without context is far less valuable than data with context. Much of that context may be inferred from the domain in which the data lives, with data delivered from a .gov or .edu (or .gov.uk or .ac.uk) site perhaps interpreted differently to data hosted on .com, .biz, or .xxx. Southampton University, the Open University, and the US Federal Government are able to gather data up and make it available for download via their existing data. sites if they choose. This offers human visitors to their sites a degree of convenience, whilst retaining the power and brand attributes of their existing domain. Gov.data, gov.uk.data, open.ac.uk.data, southampton.ac.uk.data, though? All are messy, in ways that Wolfram’s own wolfram.data would admittedly not be, and all are simply additional registrations that the institutions would have to pay for in order to stop someone else grabbing the domain.

At the end of the day, the machines don’t actually care. The existing data.open.ac.uk-type sites are human conveniences, not machine enablers. The computers, and the software they run, are quite capable of crawling the public web and finding accessible data wherever it lies on a site. There are plenty of reasons to continue embedding little snippets of data inside human readable web pages, regardless of whether you have a data.wolfram.com or a wolfram.data site. Content negotiation is becoming increasingly capable, such that there really is no need for what Wolfram calls a ‘parallel construct to the ordinary web’ at all. A human being arriving at a web site sees human readable content, whilst various software tools would automatically be presented with very different data or functions, optimised to their capabilities and requirements.

By all means, let us show the curious some of the existing techniques that work in making data more easily accessible. By all means, let us identify the gaps, the issues, the problems (none of which a new TLD even begins to address). Yes, let us definitely and unambiguously set about “highlighting the exposure of data on the internet—and providing added impetus for organizations to expose data in a way that can efficiently be found and accessed.”

But please, let us not be distracted by the false hope that adding yet another TLD to the babel that ICANN is about to unleash can do anything more than consign data to some online ghetto, wallowing unwanted, unloved and unused as companies and their customers lavish love, attention, and clicks upon the .com domain over on the ‘proper’ web.

Thanks to Raphaël Troncy, whose tweet first drew the story to my attention.

Related articles

• Is It Time For Computers To Have Their Own .Data Domains? (techcrunch.com)
• ICANN Pushes Ahead With January 12 Launch For New Top-Level Domains (wired.com)
• The biggest change in DNS since Dot-Com (wired.com)

Image via Wikipedia

For real-world applications of Linked Data and the Semantic Web, the long-running Semantic Technology Conference is hard to beat. For getting a real handle on the Cloud Computing landscape, GigaOM‘s Structure Conference is also a leading light.

Working across both areas as I do, these events tend to figure prominently in my calendar for the year*. Last year, both took place in San Francisco during the same week. I tried to attend both, and therefore succeeded in spending most of my week in cabs, shuttling between meetings at the two venues. I saw very few sessions that I wasn’t personally involved in, and the experience wasn’t a huge success.

This year the conference organisers have taken pity on me, and moved their events to opposite ends of June. The Semantic Technology Conference is up first, back at the Hilton Union Square from 5-9 June. Structure follows, returning to the Mission Bay Conference Centre on 22 and 23 June.

I’ll be attending both, and probably doing various official things during each event. At the moment, the only thing we’ve definitely nailed down is a special live appearance by The Semantic Link crew on the evening of 5 June; we’ll be taking a look at the highlights expected for the conference, offering some tips for those new to the event and its multitude of parallel sessions, and generally bringing our usual podcast chatter to the stage.

So if you’re in town around the time of either event, do get in touch; it promises to be an interesting month.

* Disclosure: WebMediaBrands pay me to host the monthly Semantic Link podcast, and to write a monthly column on SemanticWeb.com. GigaOM pay me to curate the Infrastructure/ Cloud Computing channel on their Pro site. I attended and participated in both of these events before that was the case, and still would today without the contractual relationship.

Related articles

• GigaOM Structure 2011 (datacenterknowledge.com)
• Semantic Technology Conference (fakeiitian.com)

Krista Thomas was responsible for marketing at Thomson Reuters‘ semantic technology success story, Open Calais, and is now VP Marketing at Los Angeles startup Ad.ly.

Scott Brinker is President & CTO at ion interactive, and writes the ChiefMarTec blog.

During the conversation, regulars and guests discuss the way in which ‘semantic technology’ solutions are being successfully marketed to potential beneficiaries.

Have a listen, and learn that pitches to non-semantic technology enthusiasts beginning “We’ll convert all your data to RDF, leverage the Semantic Web, and construct an OWL-based ontology” are probably doomed to failure.

The whole team is present once more, and we start the show discussing the implications of Drupal 7 and its newly formalised RDFa-publishing capabilities. Unlike regular semantic technology solutions, which someone has to consciously procure as a Semantic Technology solution, Drupal is first and foremost a (popular, free) Content Management System; the semantic smarts come for free, and therefore reach a massive new audience.

From there, we move into a broader discussion of the ways in which semantic projects take root within organisations.

Have a listen, and let us know what you think. As ever, suggestions for future topics or guests are always welcome.

@theSemanticLink is the show’s Twitter id, which we will use to invite questions ahead of shows on particular topics. If you’d like to ask questions, comment on shows, hear about new episodes as they’re released, etc, please do sign up to follow.

Related articles

• The Semantic Link is open (cloudofdata.com)
• Drupal 7 Released, With Improved UI and Semantic Technology (nytimes.com)
• House.gov moves to Drupal (radar.oreilly.com)
• Dries Buytaert Explains How Drupal Gardens SaaS Can Contribute to Semantic Web Momentum – semanticweb.com (semanticweb.com)
• Drupal 7 dives into machine-readable web (go.theregister.com)

We recorded the first episode earlier this week and it’s now online, along with an introduction to the series from myself.

Please do have a listen, and let me know what you think whilst I work out how to automate adding these to my sidebar on this site…

I look forward to lining up some great conversations – and guests – in the year ahead. We will record and publish regularly each month. Where we can agree a topic well ahead of the recording date, I’ll let you know via the @TheSemanticLink twitter account, and invite questions for me to throw at both regulars and guests.

If there are particular topics you’d like to see covered, particular guests you’d like us to secure, or other comments you’d like to make, please do let me know…

Related articles

• Top 10 Semantic Web Products of 2010 (readwriteweb.com)
• Looking forward to The Semantic Link podcast on SemanticWeb.com (cloudofdata.com)