- From: Sam Kuper <sam.kuper@uclmail.net>
- Date: Tue, 14 May 2013 15:32:22 +0100
- To: public-lod <public-lod@w3.org>
On 14/05/2013, Gannon Dick <gannon_dick@yahoo.com> wrote: > Affiliation (for the text name) and ___domain of the lead Author's email should > give you a little "uncertainty" with which to resolve DBpedia. Their rules > are very fussy and not as much "uncertainty" as you would like, but it is a > start. IIUC, this strategy's success rests on (at least) the assumptions that: [1] Each of the universities I'll be searching for is listed as an affiliation in at least one publication within NCBI. [2] For all such publications, the lead author's email address is provided among the metadata for the publication. [3] For all such publications, the lead author's email address incorporates the ___domain of the affliated institution for which I searched. I may, as I say, be being a bit slow-minded, but these each strike me as rather tenuous assumptions; and the likelihood of them all being true seems even smaller. Assumption [3], for instance, was false for the first test I ran: affiliation searched for was "London School of Economics" but although both authors of the first open access publication listed shared this affiliation, the contact email's ___domain was "popcouncil.org" rather than "lse.ac.uk". Assumption [2] was false for the third test I ran: affiliation searched for was "Royal Holloway", but only the publication's third author's email address was provided (which happened to be for the "cam.ac.uk" ___domain). I suppose I could try to narrow down the results to those with only a single author, but that still wouldn't automatically fulfil assumptions [1]-[3]. Perhaps I am still failing to understand the crucial insight that enabled you to state with confidence that, "The problem is already solved in fine detail" via the NCBI; if so, please could you share it? Many thanks, Sam
Received on Tuesday, 14 May 2013 14:32:50 UTC