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Reproducibility is the ability of an entire experiment or study to be reproduced, either by the researcher or by someone else working independently. It is one of the main principles of the scientific method and relies on ceteris paribus. The result values are said to be commensurate if they are obtained (in distinct experimental trials) according to the same reproducible experimental description and procedure. The basic idea can be seen in Aristotle's dictum that there is no scientific knowledge of the individual, where the word used for individual in Greek had the connotation of the idiosyncratic, or wholly isolated occurrence. Thus all knowledge, all science, necessarily involves the formation of general concepts and the invocation of their corresponding symbols in language (cf. Turner).

Aristotle′s conception about the knowledge of the individual being considered unscientific is due to lack of the field of statistics in his time, so he could not appeal to statistical averaging of the individual.

Reproducibility also refers to the degree of agreement between measurements or observations conducted on replicate specimens in different locations by different people, as part of the precision of a test method.[1]

Reproducible data[edit]

Reproducibility is one component of the precision of a measurement or test method. The other component is repeatability which is the degree of agreement of tests or measurements on replicate specimens by the same observer in the same laboratory. Both repeatability and reproducibility are usually reported as a standard deviation. A reproducibility limit is the value below which the difference between two test results obtained under reproducibility conditions may be expected to occur with a probability of approximately 0.95 (95%).[2]

Reproducibility is determined from controlled interlaboratory test programs or a Measurement systems analysis.[3][4]

Reproducible research[edit]

The term reproducible research refers to the idea that the ultimate product of academic research is the paper along with the full computational environment used to produce the results in the paper such as the code, data, etc. that can be used to reproduce the results and create new work based on the research.[5][6][7]

Psychology has recently seen a renewal of internal concerns about irreproducible results. Researchers explained in a 2006 study that, of 249 data sets from American Psychology Association (APA) empirical articles, 73% of contacted authors did not respond with their data over a 6-month period.[8] The first author published a paper in 2012 suggesting researchers should publish data along with their works, releasing a dataset alongside as a demonstration.[9]

Reproducible research is key to new discoveries in pharmacology. A Phase I discovery will be followed by Phase II reproductions as a drug develops towards commercial production. In recent decades Phase II success has fallen from 28% to 18%. A 2011 study found that 65% of medical studies were inconsistent when re-tested, and only 6% were completely reproducible.[10]

In 2012, a survey done for Nature found that 47 out of 53 medical research papers on the subject of cancer were irreproducible.[11] John P. A. Ioannidis writes, "While currently there is unilateral emphasis on 'first' discoveries, there should be as much emphasis on replication of discoveries."[12] The Nature study was itself reproduced in the journal PLOS ONE, which confirmed that a majority of cancer researchers surveyed had been unable to reproduce a result. Attempts to reproduce studies often strained relationships with the laboratories that were first to publish.[13]

Noteworthy irreproducible results[edit]

Hideyo Noguchi became famous for correctly identifying the bacterial agent of syphilis, but also claimed that he could culture this agent in his laboratory. Nobody else has been able to produce this latter result.

In March 1989, University of Utah chemists Stanley Pons and Martin Fleischmann reported the production of excess heat that could only be explained by a nuclear process ("cold fusion"). The report was astounding given the simplicity of the equipment: it was essentially an electrolysis cell containing heavy water and a palladium cathode which rapidly absorbed the deuterium produced during electrolysis. The news media reported on the experiments widely, and it was a front-page item on many newspapers around the world (see science by press conference). Over the next several months others tried to replicate the experiment, but were unsuccessful.

Nikola Tesla claimed as early as 1899 to have used a high frequency current to light gas-filled lamps from over 25 miles (40 km) away without using wires. In 1904 he built Wardenclyffe Tower on Long Island to demonstrate means to send and receive power without connecting wires. The facility was never fully operational and was not completed due to economic problems, so no attempt to reproduce his first result was ever carried out.[14]

See also[edit]


  1. ^ ASTM E177
  2. ^ ASTM E177
  3. ^ ASTM E691 Standard Practice for Conducting an Interlaboratory Study to Determine the Precision of a Test Method
  4. ^ ASTM F1469 Standard Guide for Conducting a Repeatability and Reproducibility Study on Test Equipment for Nondestructive Testing
  5. ^ Sergey Fomel and Jon Claerbout, "Guest Editors' Introduction: Reproducible Research," Computing in Science and Engineering, vol. 11, no. 1, pp. 5–7, Jan./Feb. 2009, doi:10.1109/MCSE.2009.14
  6. ^ J. B. Buckheit and D. L. Donoho, "WaveLab and Reproducible Research," Dept. of Statistics, Stanford University, Tech. Rep. 474, 1995.
  7. ^ The Yale Law School Round Table on Data and Core Sharing: "Reproducible Research", Computing in Science and Engineering, vol. 12, no. 5, pp. 8–12, Sept/Oct 2010, doi:10.1109/MCSE.2010.113
  8. ^ Wicherts, J. M.; Borsboom, D.; Kats, J.; Molenaar, D. (2006). "The poor availability of psychological research data for reanalysis". American Psychologist 61 (7): 726–728. doi:10.1037/0003-066X.61.7.726. PMID 17032082.  edit
  9. ^ Wicherts, J. M.; Bakker, M. (2012). "Publish (your data) or (let the data) perish! Why not publish your data too?". Intelligence 40 (2): 73. doi:10.1016/j.intell.2012.01.004.  edit
  10. ^ Prinz, F.; Schlange, T.; Asadullah, K. (2011). "Believe it or not: How much can we rely on published data on potential drug targets?". Nature Reviews Drug Discovery 10 (9): 712. doi:10.1038/nrd3439-c1. PMID 21892149.  edit
  11. ^ Begley, C. G.; Ellis, L. M. (2012). "Drug development: Raise standards for preclinical cancer research". Nature 483 (7391): 531–533. doi:10.1038/483531a. PMID 22460880.  edit
  12. ^ Is the spirit of Piltdown man alive and well?
  13. ^ Mobley, A.; Linder, S. K.; Braeuer, R.; Ellis, L. M.; Zwelling, L. (2013). "A Survey on Data Reproducibility in Cancer Research Provides Insights into Our Limited Ability to Translate Findings from the Laboratory to the Clinic". In Arakawa, Hirofumi. PLoS ONE 8 (5): e63221. doi:10.1371/journal.pone.0063221. PMC 3655010. PMID 23691000.  edit
  14. ^ Cheney, Margaret (1999), Tesla Master of Lightning, New York: Barnes & Noble Books, ISBN 0-7607-1005-8, pp. 107.; "Unable to overcome his financial burdens, he was forced to close the laboratory in 1905."

Further reading[edit]

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