“Results that hold only for a particular mouse in a particular lab in a particular experiment are arguably not science.”, says Philip Stark, statistic professor at Berkeley, as he addresses the problem of data replicability.
Science is the method we, as mankind, developed to build knowledge through careful, reproducible and replicable experimentation, meaning that an experiment must give the same results (or at least a sufficiently similar one) regardless of the operator, research method and data sample used to collect data. Although the partial lack of this requirement seems to be a plague afflicting research in these days, some is also pointing out that most of papers lack the right precision in stating the experimental conditions that other colleagues might need in order to replicate a method, should they have the patience and intention of doing so. In other words, “communicating a scientific result requires enumerating, recording and reporting those things that cannot with advantage be omitted”, says prof. Stark.