3 ms·
> It'd be interesting if we could break down academic papers into stand-alone facts, which could be cited more succinctly than the paragraphs of prose that we d
by hackuser 12y ago
> It'd be interesting if we could break down academic papers into stand-alone facts, which could be cited more succinctly than the paragraphs of prose that we do now.
Perhaps there could be some kind of semantic syntax that would group together the factual claim and supporting information (data and references). For example,
<"e=mc^2",cite1,cite2,data1,data2>
The claims still could be included in prose, but also easily extracted, analyzed, manipulated, etc.
With a little work the claims could form a semantic web, with all that entails, and the validity of cites could be checked automatically when the document is opened or on a regular basis, updating the claim appropriately. For example, the UI could display the claim differently based on whether the cited source has been withdrawn, partially invalidated, superseded, confirmed, rarely cited, heavily cited, based on impact factor, if the source's own citations have been invalidated (e.g., claimC cites claimB which cites claimA; if claimA is invalidated, there should be some sort of indication in claimC -- consider that the invalidation of a seminal claimA would set off a massive chain reaction, as it should), etc.
But that all seems obvious and I suspect I'm not the first to think of it.
- jasonpriem 12y agoIt is indeed interesting, and as you suspect it has attracted some attention. Check out "nanopubs,"(http://nanopub.org http://nanopub.org), or Simon Buckingham Shum's very cool work on ScholOnto (http://projects.kmi.open.ac.uk/scholonto/ http://projects.kmi.open.ac.uk/scholonto/) among others.
- stevewilhelm 12y agoMicroformats were popular back when blogging was new. [1] http://microformats.org/wiki/citation http://microformats.org/wiki/citation
- rdtsc 12y agoThat approach has been tried and in the bioinformatics community years ago. Basically scanning published papers that mentioned genes relationship and extracting them in order to build a graph. Say someone publishes "T3SS1 induces cell death" so you can now add an edge to a graph "T3SS1->autofaghy" or something like that.