There was an attempt in doing something like this for the CSEd
community a few years back: http://www8.cs.umu.se/~dcer/index.html
There are also a few papers about this, for example
http://doi.acm.org/10.1145/1404520.1404534
and if I'm correct there was also a few actual research papers
produced
All,
I prefer to think that somebody who knows more about statistics than
me will find something significant that I missed:
Willingness to Share Research Data Is Related to the Strength of the
Evidence and the Quality of Reporting of Statistical Results
Hi all,
IMO the most important things are to have:
- permanently accessible URLs or other references (e.g. DOIs). For
this it helps to choose a website or archive that you believe will last
a long time. Github is great for software sharing but I don't see any
reason to expect their URL
I don't know of
a public service that attaches DOIs to arbitrary datasets (shame), but I
use archive.org for publishing datasets (e.g.
http://www.archive.org/details/beatboxset1) - it is a US
library-oriented service whose explicit mission is to preserve digital
data for a very long time.
Well
Ooops - half sent message. Let's just say I am saying nothing at the moment.
L.
--
The Open University is incorporated by Royal Charter (RC 000391), an exempt
charity in England Wales and a charity registered in Scotland (SC 038302).
- permanently accessible URLs or other references (e.g. DOIs). For this
This is certainly the ideal. Let's not fall into the trap of not
doing anything until the ideal system is in place.
I was just talking to my friendly local DOI guru and this is definitely
possible now using datacite and
Lindsay,
A couple of researchers I have contacted to obtain data
told me that they have either lost it or did not make an
effort to keep it.
Having someplace that people could automatically upload their
data to might help preserve more of it, as well as making
life easier for other by cutting
On 17/02/2012, at 2:53 AM, Derek M Jones wrote:
You can find mine here (only the 2011 experiment has all the code
needed to perform the analysis; I'm working on fixing that):
http://www.knosof.co.uk/dev-experiment.html
This is a wonderful thing you have done.
I note that these days, when I
Richard,
There's the corresp() function in library(MASS)
and Fionn Murtagh's code to go with his correspondence analysis
book is available over the web.
This is very common practice with R books.
While playing with the data, I was struck by two prominent
lines I kept seeing:
