
I very much share Duncan's concern that research in statistical software 
should move ahead, and contribute to some of the exciting new uses of 
data we see.

R is the most striking success in statistical software over the last 
decade, in terms of the variety and quantity of statistical technology 
it's made available.  The R mechanism for managing the system and making 
packages available is very effective for sharing statistical 
techniques.  I think the community owes a big debt to the people in R 
core and others who've made this happen.

But the most striking current developments in how data & information are 
collected and used are taking place largely outside our context.  The 
software implemented in R and the people involved could add some 
important abilities that won't be available otherwise.  How do we get 
from here to there, though?  The very success of R tends to push against 
major changes, as opposed to incremental additions.

Thinking about the situation now versus the way S developed starting 
about 30 years ago, I see differences in the context, technical and 
human, that challenge us.

Technical challenges: 
Mainly, the obvious difference is the scale of current hardware and 
software, and the speed with which new technology arises.  I think this 
means our response has to emphasize components, and interfaces that work 
_with_ other systems, including R.

Human challenges:
As S grew, we had a group of about 2-6 people working together with  
support for risk-taking research aimed at major changes.   How do we get 
a critical mass going for the next breakthrough?  We need people working 
closely together, we need support, and we need to include teaching and 
graduate research, all required to keep good research going in this area.


Duncan Temple Lang wrote:

> ...................................
>
>
>And while we are on the topic of wishlists...
>Generally (i.e. not directed specifically to Gabor),
>the suggestions are very welcome, but so are contributions.
>And for issues such as making the existing R available on handhelds,
>that is a programming task. And I draw a large distinction between
>programming and creative research which is based on new concepts and
>paradigms.  The pool of people working in statistical computing research
>is very small. And to a large extent, their time is consumed with
>programming - making the same thing work on multiple platforms,
>correcting documentation, etc. which are good things, but
>not obviously the best use of available research ability and time.
>There are many more topics that are in progress that represent
>changes to what we can do  rather than just to how we do the same thing.
>
>One of the reasons S (R and S-Plus) is where it is now
>is because in Bell Labs, the idea was to be thinking
>5 years ahead and both meeting and directing the needs for the future.
>Because of R's popularity (somewhat related to it being free), there is
>an aspect of development that focuses more on software for statisticians
>to use "right now".
>Obviously, th development is a mixture of both the current and the
>future, but there is less of the future and certainly less of the
>longer term directions that is sacrificed by the need to maintain an
>existing system and be backward-compatible.
>If statistics is to fulfill its potential in this modern IT, we need new
>ideas and research into those new ideas. If we focus on basic
>programming tasks (however complex) and demand usability above concepts,
>we risk losing those whose primary focus is in statistical computing
>research from the field.
>
>While R provides statisticians and stat. comp. researchers with a
>terrific vehicle for doing their respective work, it also acts as
>a constraint for doing anything even moderately new. But much (not all)
>of R is based on innovations from the 1970's, 80's and 90's.   And
>as IT evolves at a terrific pace, to keep up with it, we need to be
>forward looking.
>
>
>I'll leave it there - for the moment - and go fight off the ants
>that are invading my desk!  While I wrote this down relatively
>rapidly, the ideas have been brewing for a long time. If anyone
>wishes to comment on the theme, I hope they will take a few minutes
>to think about the broad set of issues and tradeoffs.
>
>
>  D.
>
>
>  
>
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>
>- --
>Duncan Temple Lang                    duncan@wald.ucdavis.edu
>Department of Statistics              work:  (530) 752-4782
>4210 Mathematical Sciences Building   fax:   (530) 752-7099
>One Shields Ave.
>University of California at Davis
>Davis,
>CA 95616,
>USA
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