Storing information about the meaning of terms—their “semantics”—can make data more valuable. Critics of semantic web technology consider such talk to be pie-in-the-sky AI talk; how can you encode the real meaning of words? More importantly, how can you do it in a way that programs can read and use to solve real data problems?

RDFa seems to be picking up more momentum in the last few weeks. The formerly skeptical Taylor Cowan is liking it more, and I learned from the RDFa blog that Digg has lots of RDFa—five triples of information for some stories, so there are some simple but cool applications waiting to be written around those.

Looking at Michael Pick’s video DataPortability - Connect, Control, Share, Remix and on the dataportability.com home page, I saw that RDF was included in a brief list of standards involved, and something occurred to me about the value of RDF in attempts to share data across applications such as social networking sites—in particular, why it’s better than XML for this.

Since the beginning of RDFa’s history, many of its advocates have stressed its value in adding machine-readable semantics to personal web pages. This example from the RDFa Primer is typical:

I drive a Honda Accord EX. To even write that, I had to look at the back of my car to remember the “EX” part, because it never meant anything to me. I try to remember to mention it when I call the dealership to ask about the availability of some part, because it might matter to them, but it doesn’t to me.

I recently asked if anyone knew of applications that pull meta[@name and @content] metadata out of HTML head elements, and I got a few interesting answers. To extract such data, writing a short XSLT stylesheet that reads the output of John Cowan’s TagSoup would be easy, but lately I’ve been thinking: with a slight change to those meta elements, they’d be RDFa, which can store more versatile metadata that is easier to get out (see Getting Those Triples).