Good enough practices in scientific computing

Abstract

Computers are now essential in all branches of science, but most researchers are never taught the equivalent of basic lab skills for research computing.As a result, data can get lost, analyses can take much longer than necessary, and researchers are limited in how effectively they can work with software and data.Computing workflows need to follow the same practices as lab projects and notebooks, with organized data, documented steps, and the project structured for reproducibility, but researchers new to computing often don't know where to start.This paper presents a set of good computing practices that every researcher can adopt, regardless of their current level of computational skill.These practices, which encompass data management, programming, collaborating with colleagues, organizing projects, tracking work, and writing manuscripts, are drawn from a wide variety of published sources from our daily lives and from our work with volunteer organizations that have delivered workshops to over 11,000 people since 2010. OverviewWe present a set of computing tools and techniques that every researcher can and should consider adopting.These recommendations synthesize inspiration from our own work, from the experiences of the thousands of people who have taken part in Software Carpentry and Data Carpentry workshops over the past 6 years, and from a variety of other guides.Our recommendations are aimed specifically at people who are new to research computing.

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