The main library doesn't appear to have a Twitter account, but it does have a Facebook page, as well as a presence on French video sharing site DailyMotion and YouTube
Just a quick post to gather together links to the videos from the sessions at the ICSTI Workshop "Multimedia & Visualisations for Science" held at Microsoft Research in Redmond on February 8, 2011. You should be able to get downloads in most any format, if the player doesn't work for you. The entire day's worth of video is online.
Google has announced it will be using (some) microformats and RDFa to enrich search results. They call this Rich Snippets.
To display Rich Snippets, Google looks for markup formats (microformats and RDFa) that you can easily add to your own web pages. In most cases, it's as quick as wrapping the existing data on your web pages with some additional tags.
Moving toward the Semantic Web will allow our searching technologies to become more intelligent and will set the stage for the next revolution in which computing systems can become more aware of the "meaningfulness of data".
We've already seen a shift toward "semantic search": Google has already been augmenting search results with Google Maps, limited catalog searches, and more recent entries into the search market such as Amazon's A9 and the yet to be released Wolfram Alpha differentiate themselves by the structured data and content that can be extracted from a search result. We have yet to a see a compelling reason for web masters to place RDFa or microformats into a site to enable this semantic data to be mined until today, until Google provided a social incentive for site designers.
Incidentally, if you're thinking, "why didn't someone tell me this structured data thing was coming?" I should mention that actually I did try to tell people, whether it was in my presentation to Allen Press in 2007 (where I talked about the need for microformats and semantic enrichment) or in my keynote to NISO Discovery last year (where I talked specifically about Yahoo SearchMonkey using semantic information).
The time has changed, the times have changed, the days are getting brighter - what better time for Sunshine Week.
Sunshine Week is a [United States] national initiative to open a dialogue about the importance of open government and freedom of information. Participants include print, broadcast and online news media, civic groups, libraries, non-profits, schools and others interested in the public's right to know.
March 15-21, 2009
They have a blog, Facebook, Twitter and all that groovy stuff. I couldn't find a declared tag, so I'm just using the rather long "sunshineweek".
Through their Twitter I find an interesting article from The Economist - Track my tax dollars.
THE taxpayers do their part, and faithfully fling their hard-earned treasure into the gaping public maw. Surely they should be allowed to know what happens to it. So why not put government spending online?
This also gives me a chance to link to a great TED video of Sir Tim Berners-Lee (inventor of the WorldWideWeb) talking about "linked data". He talks about the importance of sharing data because you can build so much on raw data. The data part starts at about 3:58 in, and the government data specific part starts about 9:46 in.
I also very much liked his simple message of "Raw Data Now!" - my experience with Linked Data, at least at Open Repositories 2008, was that it very rapidly descends into obscure discussions about the philosophy of data representations (e.g. "do we point at the data, or the metadata about the data?"). The most important thing is to just get the raw data up, and then we can work to have wonderful semantic markup things once we actually have something to work with.
In the model of Five Weeks to a Social Library, I see in my FriendFeed today a posting from Fiona Bradley about putting together a Semantic Library training program online. It's still in the initial planning stages, you can have a look at the program outline at
The wiki is open for people to sign up, you just need to enter the password you'll see at the bottom of the login screen.
For those of us who deal more with academic content, I think semantic concepts and Semantic Web services may become even more important than social networking is right now.
(Whew, I got through all of that without saying "from Library 2.0 to Library 3.0".)
Describing the Semantic Web can be a bit complicated, I think of it as enriching our current text content on the web so that machines are able to do more processing for us - enabling us to build much more powerful scientific search and reasoning systems.
As I said in my presentation Building SkyNet for Science, invoking (and extending) Ranganathan and Noruzi: "every web resource its machine reader" (slide 13).
Thomas Tague has asked for input to help better define semantic search.
So, let’s deconstruct semantic search into it’s constituent components and talk a bit about how and whether semantic technologies might actually make it better. The results of the dissection are here on the table….
1. What kinds of questions can we ask? Can we embed logic in our questions? Do we expect inference in our results? 2. How can we ask them – keywords, natural language and all that jazz. 3. Generating the “right” result set for the query. 4. Displaying the result set in the most effective manner 5. Making money from doing all that
Here at CISTI we see Semantic Search as a key advanced technology to help the library support researchers, and in particular to help researchers get at the meaning locked up in our millions of locally-loaded journal articles.
We think of it as three pieces:
Domain-specific semantic extraction, in which the different types of scientific information are identified and indexed for search (e.g. chemical names, mathematical formulas, genes, etc.)
Straightforward search frontends, which use basic keyword mapping to provide an enhanced discovery interface (e.g. you search for water and you get any documents with the various possible representations for water)
Semantic search frontends (possibly also domain-specific) in which a researcher enters a search in terminology that's meaningful to them - for example drawing a chemical structure, or asking a complex question (e.g. what X are affected by Y when conditions A and B hold)
For all of these areas we see partnering as a key, as no single organisation is going to have the domain-specific expertise necessary, or the technology expertise necessary.
I'd be happy to hear other opinions on semantic search, particularly as it relates to science. Should we separate it into several subareas? Perhaps
Semantic embedding (the document is already semantically enriched)
semantic extraction (terms are extracted from a document that isn't semantically encoded)
semantic indexing (constructing search indexes using semantic information)
semantic search (search engines that use semantic information)
I see I don't even have a category for Semantic Web, so I guess it's time to make one.
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