Friday, April 25, 2014

Confessions of an RDF agnostic, part 1: What can we learn using RDF?
 Disclaimer: the opinions expressed here are mine alone and do not reflect policies or recommendations of TDWG, the TDWG RDF/OWL Task Group, or W3C.

I've now spent several years as part of the TDWG community working toward making it possible to apply RDF technology to biodiversity data (for the last two years as co-convener of the TDWG RDF/OWL Task Group).  Over the last nine months I've spent some time reflecting about that effort - most intensively while preparing for the Primer session (part 1 part 2) at the Semantics of Biodiversity session at the TDWG meeting in October.  Trying to figure out how to teach something to beginners is a great way to cut through the fuzziness in your thinking on a subject and I was helped in the effort by forcing myself to slog through some of the rather dry W3C technical material on RDF such as the RDF Semantics ( ) and RDF Concepts and Abstract Syntax ( ) documents. 

If one is going to start off an educational session for beginners, it's probably good to try to address questions like "why should I bother to learn about this?" and "what good is all this for?"  So in addition to thrashing through the W3C documents, I prepared for the Primer session by thinking about the Rod Page Challenge (first expressed in an email, then fleshed out at which stated succinctly was "What new things have we learnt about biodiversity by converting biodiversity data into RDF?"  The quick and dirty answer to Rod's question is "nothing much", at least at the present time.  I'm basing that answer on the fact that nobody has been trumpeting on tdwg-content about great things that they have done with the RDF data that Rod linked to in his blog post. 

In thinking about Rod's challenge, I tried to dig a little deeper and ask myself: what does it actually mean to say that we can "learn" something using RDF?  RDF and its vocabulary interpretations RDFS and OWL are supposed to support "reasoning", which implies that machines that use them can help us figure out things with them.  What is the nature of those things and are they really things that we couldn't figure out using a more conventional technology?  In the end, I ended up with way more slides than I could show in the time allocated to my part of the Primer session, but hey, I could just blog about the parts I had to cut, right? 

Some people may be surprised that the convener of an RDF Task Group would claim to be an "RDF agnostic".  I truly don't know whether RDF will actually help us "learn" anything useful that we couldn't more easily find out using other technologies.  That's not necessarily because I think it's not possible, but rather because I think success will depend on a large extent to our ability to have more clear expectations about what we as a community want to accomplish and whether we can work together effectively to accomplish those things.  In some number of blog posts greater than zero and less than infinity, I want to explore the issues of what we can reasonably expect to "learn" using RDF and what barriers exist that inhibit progress towards accomplishing that "learning".

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