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> 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.
Memphis, TN 38163
Phone Bus.: 901-448-7152
Phone FAX:  901-448-7126
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*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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