Open data and open-source software may be part of the solution to sciences reproducibility crisis, but they are insufficient to guarantee reproducibility. Requiring minimal end-user expertise, encapsulator creates a "time capsule" with reproducible code (right now, only supporting R code) in a self-contained computational environment. encapsulator provides end-users with a fully-featured desktop environment for reproducible research.
In 1942, Robert Merton wrote that "Incipient and actual attacks upon the integrity of science" meant that science needed to "restate its objectives, seek out its rationale". Some 77 years later we are similarly in an environment where “the people of this country have had enough of experts". It is essential that science is able to withstand rigorous scrutiny to avoid being dismissed, pilloried or ignored. Transparency and reproducibility in the scientific process is a mechanism to meet this challenge and good research data management is a fundamental factor in this.
The "Crisis of Reproducibility" has received considerable attention both within the scientific community and without. While factors associated with scientific culture and practical practice are most often invoked, I propose that the Crisis of Reproducibility is ultimately a failure of generalization with a fundamental scientific basis in the methods used for biomedical research. The Denominator Problem describes how limitations intrinsic to the two primary approaches of biomedical research, clinical studies and pre-clinical experimental biology, lead to an inability to effectively characterize the full extent of biological heterogeneity, which compromises the task of generalizing acquired knowledge. Drawing on the example of the unifying role of theory in the physical sciences, I propose that multi-scale mathematical and dynamic computational models, when mapped to the modular structure of biological systems, can serve a unifying role as formal representations of what is conserved and similar from one biological context to another. This ability to explicitly describe the generation of heterogeneity from similarity addresses the Denominator Problem and provides a scientific response to the Crisis of Reproducibility.
Replication is the scientific gold standard that enables the confirmation of research findings. Concerns related to publication bias, flexibility in data analysis, and high-profile cases of academic misconduct have led to recent calls for more replication and systematic accumulation of scientific knowledge in psychological science. This renewed emphasis on replication may pose specific challenges to cross-cultural research due to inherent practical difficulties in emulating an original study in other cultural groups. The purpose of the present article is to discuss how the core concepts of this replication debate apply to cross-cultural psychology. Distinct to replications in cross-cultural research are examinations of bias and equivalence in manipulations and procedures, and that targeted research populations may differ in meaningful ways. We identify issues in current psychological research (analytic flexibility, low power) and possible solutions (preregistration, power analysis), and discuss ways to implement best practices in cross-cultural replication attempts.
Scientific instruments are at the heart of the scientific process, from 17th‐century telescopes and microscopes, to modern particle colliders and DNA sequencing machines. Nowadays, most scientific instruments in biomedical research come from commercial suppliers , , and yet, compared to the biopharmaceutical and medical devices industries, little is known about the interactions between scientific instrument makers and academic researchers. Our research suggests that this knowledge gap is a cause for concern.
We propose an approach for improved reproducibility that includes capturing and relating provenance characteristics and performance metrics, in a hybrid queriable system, the ProvEn server. The system capabilities are illustrated on two use cases: scientific reproducibility of results in the ACME climate simulations and performance reproducibility in molecular dynamics workflows on HPC computing platforms.