On Nov 22, 2005, at 9:11 PM, Luke Arno wrote:
On 11/22/05, Danny Ayers <[EMAIL PROTECTED]> wrote:
By getting people to upload their data, Google Base bypasses one of
the harder problems of distributed data: finding the stuff. I'd be
interested in hearing of any ideas anyone has around here that might
be helpful for finding the stuff.
Imagine there are lots and lots of microformat documents out there. I
want to get the data from a subset of these, e.g. restaurant reviews.
How do I do it?
The strategies I've seen for data discovery to date have all left a
lot to be desired, e.g. in-the-wild links - require crawling; more
controlled link lists (e.g. on a Wiki or at a directory service) -
heavily centralised; UDDI etc - service oriented, hard work;
distributed RDF queries - potentially workable, but still a way off.
Others..? Or are there any obvious ways I've missed of reducing the
drawbacks of these techniques?
Distruted query stuff is still a ways off, I think.
Any centralized-directory-stuff should be the result
of the crawl, IMO.
We just need more meaningful links, better trust
and identity systems, and good syndication
technology.
Speaking of meaningful links...
I am sure this has come up before, so sorry in
advance, but could we use rel values to say
"there are x and y uFs over there".
In most cases, this would be semantic abuse. Remember, rel and rev
describe the *relationship* between the current page and the referred
URL. Type could get you a big closer, but still wouldn't be very
reliable.
In other words, should there be a microformats
discovery microformat? uF-links or some such?
-ryan
--
Ryan King
[EMAIL PROTECTED]
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