That's typically the case in several fields in the humanities where the 
complexity is in the representation refinement of the source, not necessarily 
the quantity.
Laurent

Le 22 avr. 2013 à 15:52, Peter Murray-Rust a écrit :

> I have been pushing this idea in STEM for about 5 years under the heading 
> (from Jim Downing) "Long-tail science". This emphasizes the heterogeneity and 
> the large number of sets. In practice (at least in sciences which want to 
> publish data) "big data" is already recognized and even often supported by 
> funders. Long-tail data is a myriad of Cinderellas.
> 
> 
> On Mon, Apr 22, 2013 at 2:23 PM, Rufus Pollock <[email protected]> wrote:
> Hi All,
> 
> I wanted to let folks know about this post which has just gone up:
> 
> http://blog.okfn.org/2013/04/22/forget-big-data-small-data-is-the-real-revolution/
> 
> <quote>
> There is a lot of talk about “big data” at the moment. For example,
> this is Big Data Week, which will see events about big data in dozens
> of cities around the world. But the discussions around big data miss a
> much bigger and more important picture: the real opportunity is not
> big data, but small data. Not centralized “big iron”, but
> decentralized data wrangling. Not“one ring to rule them all” but
> “small pieces loosely joined”.
> </quote>
> 
> Very interested to hear people's thoughts - this will be first in a series.
> 
> Rufus
> 
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> 
> 
> -- 
> Peter Murray-Rust
> Reader in Molecular Informatics
> Unilever Centre, Dep. Of Chemistry
> University of Cambridge
> CB2 1EW, UK
> +44-1223-763069
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Laurent Romary
INRIA & HUB-IDSL
[email protected]



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