Introduction
In an era where science is afflicted by the ‘reproducibility crisis’, the need to improve confidence in scientific methods and data is immediate. Within the domain of computational science, the ability to produce high-fidelity predictions based on in silico methods is widely recognised to be essential in order to transform numerous industries, from pharmaceuticals to aerospace, automotive and fusion.
This event deals with reliability and reproducibility of data produced by computer simulations in a number of research fields, including biomedicine, advanced functional materials, climate change, energy, and urban analytics.
About the event
The event will be in conjunction with the European Commission-funded project called "VECMA" (Verified Exascale Computing for Multiscale Applications) and aligns well with the Turing’s mission to tackle the biggest challenges in science, society, and the economy. Reproducibility pertains to all three, and ‘The Turing Way’, the Institute’s handbook for reproducible data science, is evidence of its importance.
The central objective is to propose methods that enable computer simulation predictions to guide real decision-making. Theory, software, tools and services in support of these goals are now being actively developed and will be showcased in a special interactive software session.
Ultimately, the goal is to support students and academics as they develop their code, as well as to train next-generation scientists and leaders to produce work that will be regarded as gold-standard examples of trustworthy and reusable research.
The day will comprise expert talks, a panel session, and an interactive session on open-access software produced by VECMA (www.vecma-toolkit.eu) and The Alan Turing Institute.
The event is expected to attract interest from physical and life scientists, engineers, medics, and social scientists, whether in academia, government, or industry, and to engage them in an active exchange of ideas and methods that will create impact on the way science is done.
