New Data Causing Revisions
Date: January 2009
How can new scientific data cause any existing scientific
explanation to be supported, revised, or rejected?
All scientific model (also called "theories", but that is a term that
carries a lot of baggage with it) must be, to use the common term
"falsifiable". That means that the model must be able to be shown to be
false, or incomplete. That is the difference between a scientific theory
and a "dogma". The scientific theory is malleable, that is it is subject
to change in the light of experimental data (which also may have its own
limitations). On the other hand "dogma" is a "top -- down" proposition.
This pronouncement, whatever it is, is "true" no matter how absurd it might
appear. Then investigators are faced with the problem of making any and all
experimental observations "fit" the immutable dogma. That scenario falls in
the domain of philosophy or religion, not science. So no existing scientific
explanation is ever total and complete. For those positions one must look
into fields of religion or philosophy -- but do not call it science.
The main way scientists communicate their findings is through scientific
journal articles. Researchers publish experiments, data, results, and
conclusions. Their goal is to come up with a way to explain their data or
findings. Other researchers can read the articles and decide if their data
fit the published work -- and then plan new experiments to confirm or refute
One scientist might only run experiments in a range of conditions, and those
conditions may differ from another scientist. One vital task of science is
to take the combined "quilt" of different scientists' work and find an
overall explanation that explains all the data, not just one specific area.
Scientists can also gather at conferences to present new findings and
discuss them in person. Researchers who disagree about the data might gather
and discuss their views at a conference, and come up with a comprehensive
Once a consistent explanation is found, a scientist might come back later
and summarize all the data in a 'review' article. This article explains the
overall findings in a given field, and is usually written a few years after
the original disagreement.
Hope this helps,
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Update: June 2012