Physiome: Encouraging Reproducible and FAIR Computational Modelling

Abstract

Computational modelling is a commonly used tool in the physiological sciences. For these models to be useful, it is essential that the model is reproducible and is available for other scientists to reuse. Despite development of standards and supporting software, widespread adoption of publishing reproducible and reusable computer models of biological systems is still lacking.Physiome is a new journal committed to reproducibility and reusability of mathematical models of physiological processes. Every article published in Physiome is connected to a curated and permanent version of the model code with a persistent identifier. Through the Physiome paper, the code necessary to run the model is easily accessible by just clicking a link, to be reused as it is or as a module in a bigger model. It is also connected to a primary paper published in a domain‐appropriate journal, where the validation and scientific value of the model is evaluated and presented. A Physiome publication is a complement to your primary article that ensures reproducibility, reusability and discoverability of your model. The format encourages modularity that facilitates the combination of different models to develop the next level of systems understanding. And all the models are in one place, easy to Find, Access, Interoperable, and Reuse (FAIR).Reproducibility and confirmation of results is crucial for useful science and should be one of the supporting pillars of good research. Yet, publication of it is rarely incentivised, often treated as a secondary result at best, which undermines the quality of our work. With the strict formulation of equations and easily shared code, one would expect mathematical models to be reproducible by default, but in fact less than 10% of the models published in scientific journals work when implemented by another group. Physiome will save valuable time and effort on trying to implement models from papers that lack information, or having your results lost because others cannot use them. In doing so, Physiome encourages model authors to make their work available in a reproducible and FAIR manner.For more information visit: https://journal.physiomeproject.org.Support or Funding InformationWe acknowledge the support of the International Union of Physiological Sciences, Digital Science, Figshare, Overleaf, and the University of Auckland.