The hidden costs of GPL software?
The author of the article says nothing about the large number of hours and weeks that he surely spent learning S-plus! There should be attention to the costs that arise from a wrong or inappropriate analysis, perhaps because the software that is in use makes it difficult to do anything better, perhaps because of statistical skill limitations, often with these two factors working together. Analyses that misrepresent the science, or designs and analyses that conspire together to this end, have serious and costly implications for research. I've refereed several papers recently, in broadly ecological fields of endeavour, with seemingly quite reasonable data, where the mix of author skill and abilities of the package was clearly not up to the task in hand. Relative to getting on top of the statistical issues (for which they will probably end up getting, as they need to, statistical help), the GUI/noGUI issue will be a minor consideration, and hours or weeks spent learning R will be at most a modest consideration. John Maindonald email: john.maindonald at anu.edu.au phone : +61 2 (6125)3473 fax : +61 2(6125)5549 Centre for Bioinformation Science, Room 1194, John Dedman Mathematical Sciences Building (Building 27) Australian National University, Canberra ACT 0200.
On 17 Nov 2004, at 10:27 PM, r-help-request at stat.math.ethz.ch wrote:
From: "Philippe Grosjean" <phgrosjean at sciviews.org>
Date: 17 November 2004 8:53:28 PM
To: <r-help at stat.math.ethz.ch>, <r-sig-gui at stat.math.ethz.ch>
Cc: Subject:
Hello,
In the latest 'Scientific Computing World' magazine (issue 78, p. 22),
there
is a review on free statistical software by Felix Grant ("doesn't have
to
pay good money to obtain good statistics software"). As far as I know,
this
is the first time that R is even mentioned in this magazine, given
that it
usually discuss commercial products.
In this article, the analysis of R is interesting. It is admitted that
R is
a great software with lots of potentials, but: "All in all, R was a
good
lesson in the price that may have to be paid for free software: I
spent many
hours relearning some quite basic things taken for granted in the
commercial
package." Those basic things are releated with data import, obtention
of
basic plots, etc... with a claim for a missing more intuitive GUI in
order
to smooth a little bit the learning curve.
There are several R GUI projects ongoing, but these are progressing
very
slowly. The main reason is, I believe, that a relatively low number of
programmers working on R are interested by this field. Most people
wanting
such a GUI are basic user that do not (cannot) contribute... And if
they
eventually become more knowledgeable, they tend to have other
interests.
So, is this analysis correct: are there hidden costs for free software
like
R in the time required to learn it? At least currently, for the people
I
know (biologists, ecologists, oceanographers, ...), this is perfectly
true.
This is even an insurmountable barrier for many of them I know, and
they
have given up (they come back to Statistica, Systat, or S-PLUS using
exclusively functions they can reach through menus/dialog boxes).
Of course, the solution is to have a decent GUI for R, but this is a
lot of
work, and I wonder if the intrinsic mechanism of GPL is not working
against
such a development (leading to a very low pool of programmers actively
involved in the elaboration of such a GUI, in comparison to the very
large
pool of competent developers working on R itself).
Do not misunderstand me: I don't give up with my GUI project, I am just
wondering if there is a general, ineluctable mechanism that leads to
the
current R / R GUI situation as it stands,... and consequently to a
"general
rule" that there are indeed most of the time "hidden costs" in free
software, due to the larger time required to learn it. I am sure there
are
counter-examples, however, my feeling is that, for Linux, Apache,
etc... the
GUI (if there is one) is often a way back in comparison to the
potentials in
the software, leading to a steep learning curve in order to use all
these
features.
I would be interested by your impressions and ideas on this topic.
Best regards,
Philippe Grosjean