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    Interview With Tim Berners-Lee, Part 2: Search Engines, User Interfaces for Data, Wolfram Alpha, And More... - ReadWriteWeb

    In part 2 of my one-on-one interview with Tim Berners-Lee, we explore a variety of topics relating to Linked Data and the Semantic Web. If you missed it, in Part 1 of the interview we covered the emergence of Linked Data and how it is being used now even by governments.

    In Part 2 we discuss: how previously reticent search engines like Google and Yahoo have begun to participate in the Semantic Web in 2009, user interfaces for browsing and using data, what Tim Berners-Lee thinks of new computational engine Wolfram Alpha, how e-commerce vendors are moving into the Linked Data world, and finally how the Internet of Things intersects with the Semantic Web.

    Semantic Web and Search Engines Like Google, Yahoo

    RWW: You've been talking about the Semantic Web for many years now. Generally the view is that Semantic Web is great in theory, but we're still not seeing a large number of commercial web apps that use RDF (we've seen a number of scientific or academic ones). However we have begun to see some traction with RDFa (embedding RDF metadata into XHTML Web content), for example Google's Rich Snippets and Yahoo's SearchMonkey. Has the takeup of RDFa taken you by surprise?

    TBL: Not really, but the takeup by the search engines is interesting. In a way I was happy to see that, it was a milestone for those things to come out of the search engines. The search engines had typically not been keen on the Semantic Web - maybe you could argue that their business is making order out of chaos, and they're actually happy with the chaos. And if you provide them with the order, they don't immediately see the use of it.

    "The search engines have not been keen on the Semantic Web [...] their business is making order out of chaos, and they're actually happy with the chaos."

    Also I think there was misunderstanding in the search engine industry that the Semantic Web meant metadata, and metadata meant keywords, and keywords don't work because people lie. Because traditionally in information retrieval systems, keywords haven't proven up to the task of finding stuff on the Web. One of the reasons is that people lie, the other is that they can't be bothered to enter keywords. So keywords have gotten a bad reputation, then metadata in general was tarred with this 'keywords don't work' brush. Because a lot of Semantic Web data included metadata, then people thought that with Semantic Web data -- again, that people will lie and won't have the time to produce it.


    Google rich snippets example; image credit: Matt Cutts

    Now I think there's a realization that when you're putting data online, that people are motivated NOT to lie. For example when your band is going to produce its next album, or when your band is going to play next downtown, you're motivated to put that information up there on the Semantic Web. There's an awful lot of cases when actually data is really important to people; and it's on the web anyway. So I think it's great that some of the search engine companies are starting to read RDFa.

    Does this mean that they [search engines] will start to absorb the whole RDF data model? If they do, then they will be able to start pulling all of the linked data cloud in.

    "The web of linked data and the web of documents actually connect in both directions, with links."

    Will they know what to do with it? Because when it's data in a very organized form, I think some people have been misunderstanding the Semantic Web as being something that tries to make a better search engine - i.e. when you type something into a little box. But of course the great thing about the Semantic Web is that you can query it, you can ask a complicated query of the Semantic Web, like a SQL query (we call it a SPARQL query), and that's such a different thing to be able to do. It really doesn't compare to a search engine.

    You've got search for text phrases on one side (which is a useful tool) and querying of the data on the other. I think that those things will connect together a lot.

    So I think people will search using a search text engine, and find a webpage. On the front of the webpage they'll find a link to some data, then they'll browse with a data browser, then they'll find a pattern which is really interesting, then they'll make their data system go and find all the things which are like that pattern (which is actually doing a query, but they'll not realize it), then they'll be in data mode with tables and doing statistical analysis, and in that statistical analysis they'll find an interesting object which has a home page, and they'll click on that, and go to a homepage and be back on the Web again.

    So the web of linked data and the web of documents actually connect in both directions, with links.

    User Interfaces for Semantic Content

    RWW: At the recent SemTech conference, Tom Tague of Thomson Reuters' Calais project suggested that user interfaces for semantic content are key in getting more take-up. With that in mind, I wonder if you've seen some great interfaces or designs for semantic applications in recent months - if so which ones and why did they impress you?

    TBL: I think that whole area is very exciting at the moment. The only piece of hacking I've done over the past few years has been on a thing called the Tabulator [a data browser and editor], which is addressing exactly that. Partly because I wanted to be able to look at this data. And now there are lots of different ways that people need to be able to look at data. You need to be able to browse through it piece by piece, exploring the world of data. You need to be able to look for patterns of particular things that have happened. Because this is data, we need to be able to use all of the power that traditionally we've used for data. When I've pulled in my chosen data set, using a query, I want to be able to do [things like] maps, graphs, analysis, and statistical stuff.


    W3C Tabulator, a data browser/editor; Image credit: wiwiss.fu-berlin.de

    So when you talk about user interfaces for this, it's really very very broad. Yes I think it's important. There's also the distinction we can make between the generic interfaces and the specific interfaces.

    There will always be specific interfaces; for example if you're looking at calendar data, there's nothing else like a calendar that understands weeks, months and years. If you're looking at a genome, it's good to have a genetics-specific user interface.

    "I want to be able to do maps, graphs, analysis, and statistical stuff."

    However you also need to be able to connect that data, through generic interfaces. So if my genome data was taken during an experiment which happened over a particular period, I need to be able to look at that in the calendar - so I can connect the genetics to the calendar.

    So one of the things I hope to see is domain-specific things for various different domains, and the generic user interfaces. And hopefully the generic interfaces will be able to tie together all of the domains.

    via readwriteweb.com

    • 10 July 2009
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