Open Science and Preregistration
Making methods, data, and intentions public before results are known guards against selective reporting and lets others check the work.
What Open Science Covers
Open science is a family of practices that make research checkable: open access to publications, open data, open source code, and open protocols. The unifying idea is that a claim others cannot inspect is a claim others cannot verify. Openness does not make a result correct, but it makes correctness testable by people other than the authors.
Preregistration
Preregistration records the hypotheses, methods, and analysis plan before the data are seen or the runs are made. It draws a hard line between confirmatory analysis, testing a prediction stated in advance, and exploratory analysis, generating hypotheses after looking. Both are valuable; conflating them, presenting an exploratory finding as if it were predicted, is a major source of false results.
Problems It Addresses
- Selective reporting: publishing only the runs or metrics that looked good.
- The garden of forking paths: many undisclosed analysis choices that inflate false positives.
- Hypothesizing after results are known, which turns noise into apparent discovery.
- Publication bias toward positive findings.
Limits
Preregistration does not fit every kind of work; much simulation science is legitimately exploratory. Its value is honesty about which mode a result belongs to, not forcing all inquiry into a confirmatory mold. The discipline is to label exploratory findings as hypotheses to be tested, not as confirmations.
At Kronos
Physics deposits publish code, inputs, and methods so results can be independently rechecked, and design claims are stated with their assumptions and open questions rather than only the favorable outcomes. Distinguishing a demonstrated result from an aspiration is the same discipline that separates confirmatory from exploratory work.