On Jan 15, 2019, at 2:00 PM, Kyle Banerjee <[log in to unmask]> wrote:
>> ...... How can I go beyond parsing the RDF with XPath, stuffing the
>> results into a database, and applying SQL to the result? How can truly
>> exploit the nature of the RDF and possibly manifest it as linked data?
> I'd spin that around and ask how you'd exploit a set of CSV or files in any
> other format since regardless of how data is obtained, the structure and
> methods you use should be driven by the problem you want to solve.
> This is not to say that it's not sometimes fun to have a tool in your hand
> and then try to find problems it might be good for -- especially if that
> tool throws fire or potentially does a lot of destruction. But I
> digress.... In general, lessons are more likely to stick if you're working
> on something you actually care about.
> If you're just looking to play around with this particular data, the
> authors strike me the most interesting part of the equation. Would be
> interesting to know how consistent their names are entered (especially
> across publishers), how many of the authors different publishers list, etc.
I concur; I'm not necessarily looking for the answer to a specific question. Rather, I am looking to practice with some well-formed data and exploit its particular characteristics. I've never seen such real, rich RDF which is so relevant to my local community. I believe benefits learnt from this particular data and be applied to other data sets which might present itself in the future. Can we say, "Possible killer application?"
What sorts of questions can these particular RDF streams answer that more generic CSV files can't, and if such questions exist, then how can I go about answering them?