Concept

Reproducibility

Summary

Reproducibility, closely related to replicability and repeatability, is a major principle underpinning the scientific method. For the findings of a study to be reproducible means that results obtained by an experiment or an observational study or in a statistical analysis of a data set should be achieved again with a high degree of reliability when the study is replicated. There are different kinds of replication but typically replication studies involve different researchers using the same methodology. Only after one or several such successful replications should a result be recognized as scientific knowledge. With a narrower scope, reproducibility has been introduced in computational sciences: Any results should be documented by making all data and code available in such a way that the computations can be executed again with identical results. In recent decades, there has been a rising concern that many published scientific results fail the test of reproducibility, evoking a reproducibility or replication crisis. The first to stress the importance of reproducibility in science was the Irish chemist Robert Boyle, in England in the 17th century. Boyle's air pump was designed to generate and study vacuum, which at the time was a very controversial concept. Indeed, distinguished philosophers such as René Descartes and Thomas Hobbes denied the very possibility of vacuum existence. Historians of science Steven Shapin and Simon Schaffer, in their 1985 book Leviathan and the Air-Pump, describe the debate between Boyle and Hobbes, ostensibly over the nature of vacuum, as fundamentally an argument about how useful knowledge should be gained. Boyle, a pioneer of the experimental method, maintained that the foundations of knowledge should be constituted by experimentally produced facts, which can be made believable to a scientific community by their reproducibility. By repeating the same experiment over and over again, Boyle argued, the certainty of fact will emerge.

Official source

https://en.wikipedia.org/wiki/Reproducibility

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Reproducibility

Data and Workflow to: Three-dimensional buoyant hydraulic fractures: finite volume release (Möri and Lecampion, (2023))

Regularization for distributionally robust state estimation and prediction

Data and Workflow to: Three-dimensional buoyant hydraulic fractures: finite volume release (Möri and Lecampion, (2023))

Regularization for distributionally robust state estimation and prediction