Search the CONFOCAL archive at
http://listserv.acsu.buffalo.edu/cgi-bin/wa?S1=confocal
So you'd like to reanalyze published data in an attempt to prove poor
methodology because those (newly published) data conflict with those
previously published, perhaps your own? IMHO, this sounds like an
excellent reason for denying access to data and for forgetting about
all this "image ethics by law" stuff. If your point is methodology,
you should complain to the journal with a letter to the editor
(published) - the reviewers are obviously not doing their job re the
methods. Very high profile journals even have "technical comments"
sections for exactly this reason. If your complaint is about the
scientific conclusions (the only thing that really matters unless it
is a methods journal) then refute the data with a reasoned discussion
of what is out there already and with your own analysis of your own
samples. "Reanalysis wars" are not good for science.
>Search the CONFOCAL archive at
>http://listserv.acsu.buffalo.edu/cgi-bin/wa?S1=confocal
>
>I been refused access by the authors to images published in a recent
>review article about colocalisation, in a respectable journal- our
>declared intention was to renalyse them, there seemed to be major
>difference between the published measurements of colocalisation, the
>data as shown in a scattergram and how we believed the analysis
>should be performed.
>
>I have also had no response to queries made to another set of
>authors about methods of data analysis. We did not even get close to
>a request to examine the published images.
>
>
>It is very important that journals stipulate that, at the very least
>the published images should be considered to be in the public domain
>and that authors should be expected to respond to legitimate
>questions about poorly described methods.
>
>A related question is how, as a community, we should respond when
>reasonable requests are blocked.
>
>
>
>Jeremy Adler
>Cell Biology
>The Wenner-Gren Inst.
>Arrhenius Laboratories E5
>Stockholm University
>Stockholm 106 91
>Sweden
>
>
>
>-----Original Message-----
>From: Confocal Microscopy List on behalf of Larry Tague
>Sent: Wed 7/2/2008 16:43
>To: [log in to unmask]
>Subject: Re: An alarming amount of (statistical) image manipulation
>
>Search the CONFOCAL archive at
>http://listserv.acsu.buffalo.edu/cgi-bin/wa?S1=confocal
>
>> The traditional way that research is validated is by reproducibility
>> rather than by combing through raw data.
>Yes... and who is going to pay for all of this reproducibility
>testing... not NIH who is only funding about 1 in 10 proposals at the
>present time. I do not have the time or the money to reproduce
>questionable data when trying to complete my own research. I need to be
>able to quickly make a determination relative to the "acceptable" nature
>of published material. I have discovered the hard way that peer review,
>even though it is the best we have, is not always sufficient. After all,
>how many peer reviewers take the time to look at the original data?
>Customarily, all they see is the polished product to be published. With
>the wonderful advantages of the digital age comes a mess of
>disadvantages and pit-falls that will require new and innovative ways of
>management and review. There is a lot of innocent garbage being
>published that is scary. We had better be quick studies in this new
>digital world, or otherwise our professions in science may quickly
>develop credibility problems.
>
>Larry
>
>Bill Oliver wrote:
>> Search the CONFOCAL archive at
>> http://listserv.acsu.buffalo.edu/cgi-bin/wa?S1=confocal
>>
>> On Tue, 1 Jul 2008, Larry Tague wrote:
>>
>>>
>>> Yes, this diatribe strays somewhat from the original image
>>> manipulation question, but if there is no data to check or continue
>>> using, how could you possibly know if an improper image analysis had
>>> been applied. Even if rules for image analysis exist, there is no
>>> good way to be sure mistakes were not made... especially when there
>>> are questions post publication and no raw data to check. Cheers!
> >>
>>
>> The traditional way that research is validated is by reproducibility
>> rather than by combing through raw data. The bottom line is that if
>> "ethics" is a problem, then there's nothing to stop someone from
>> faking the data altogether. Further, many mistakes are not those that
>> will lie in being able to scrutinize the images, but in the physical
>> process of doing the experiment. In the cases of experiments-gone-bad
>> that I am familiar with, the errors were not in recording the data,
>> but in the execution -- a poorly calibrated water bath, a mislabeled
>> specimen, etc.
>>
>> I kow of one study, for instance, where the data was way off base
>> because an operator simply didn't know how to operate an
>> oscilloscope. The only way to figure out the error (by reproducing
>> the results), however, was to redo the experiment. When you did that,
>> it was clear that the only way to get the data that was reported was
>> by incorrectly setting the gain at one point in the process. You
>> couldn't see that by looking at the data itself -- the data were
>> accurately reported.
>>
>> So I would suggest that the best way to see if mistakes were made is
>> the traditional way -- reproducibility.
>>
>> billo
>
>--
>Larry Tague
>Co-Investigator BBHSL*
>Co-Director of MECCA**
>Research Associate (Dept. of Physiology)
>University of Tennessee Health Science Center
>894 Union Ave.
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>Phone Bus.: 901-448-7152
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>e-mail:[log in to unmask] or
> [log in to unmask]
>
>*BBHSL "Building Bridges to Health Science Literacy" URL:
>http://bbhsl.mecca.org, a Science Education Partnership Award
>(SEPA). Supported by the National Center of Research Resources
>(NCRR) of the National Institutes of Health (NIH).
>**MECCA (Memphis Educational Computer Connectivity Alliance)
>URL: http://www.mecca.org/. Originally support by the National
>Science Foundation's "Networking Infrastructure or Education"
>program.
>
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