A few weeks ago I asked on this blog “What makes good linked data?”. A recent blog post by Mike Bergman and Frédérick Giasson really helps to get to the heart of this question.

If you are interested in how to use linked data effectively you should definitely read Mike and Fred’s article. To summarise briefly , they look at two specific high profile examples of linked data: the Rensellaer Polytechnic Tetherless World group’s work on converting data.gov datasets to RDF, and the recent New York Times initiative to open up their topic pages as RDF.

The main problem with the TW data is that their approach is a simple mapping from rows and columns of a table to RDF statements, with limited further information about the meaning of predicates. They don’t dig into the semantics of the contents of table cells, which is sometimes not obvious. I had a look at these issues a couple of months back in these two articles, though Mike and Fred examine it in more depth.

With the New York Times data, as Mike and Fred explain, the problem is essentially one of confusing information about a person with information on articles about that person, the old information vs non-information resource dilemma. Richard Cyganiak also wrote about this a few weeks ago.

Hopefully the efforts of the Pedantic Web initiative can help spread good practices in this area. (Let’s hope it’s not long before Galway dries up enough that they can turn their servers back on!).

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