- From: Matt Williams <matthew.williams@cancer.org.uk>
- Date: Wed, 13 Feb 2008 21:06:41 +0000
- To: Colin Batchelor <BatchelorC@rsc.org>, public-semweb-lifesci hcls <public-semweb-lifesci@w3.org>
I'd agree - I suspect that simply matching terms doesn't help that much - we'd need to know the context of it, but then it all gets very sticky. There is some work on mining the Chemistry literature from Cambridge (UK) - using ? OSCAR/ Sci-ML I think.... We've done a little work in the clinical domain using structured abstracts as a guide to help extract info automatically/ semi-automatically. Looks promising, but noting concrete yet. Matt Colin Batchelor wrote: >> I also think that the machine-readable representation of facts about >> biology >> should have a higher priortiy than the description of experimental > setups >> and procedures (which is the major goal of OBI and EXPO). People only > have >> limited time and motivation to create machine-readable annotations, > and it >> is much more useful when they spend that time on describing the > RESULTS >> (biological facts). Of course, descriptions of experiments are also >> valuable, when there are sufficient resources left for creating them. > > Good point. What I was sort of driving at (and failing) was the context > in which the facts are mentioned---are they the aim of the paper, > background information, mentioned as results and so forth? > > Currently in our (Project Prospect) RSS feeds we connect the OBO terms > to the article with the content module of RSS, which I feel is > unsatisfactory. > > Best wishes, > Colin. > -- http://acl.icnet.uk/~mw http://adhominem.blogsome.com/ +44 (0)7834 899570
Received on Wednesday, 13 February 2008 21:07:10 UTC