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Good enough practices in scientific computing.
Greg Wilson1, Jennifer Bryan2, Karen Cranston3
1Software Carpentry Foundation, Austin, Texas, United States of America.
Plos Computational Biology
|June 23, 2017
Summary
Researchers often lack basic computing skills, leading to data loss and inefficient workflows. This paper introduces essential computing practices for organized data management, reproducible research, and effective scientific software use.
Area of Science:
- * Computational science
- * Research methodology
Background:
- * Computers are integral to modern scientific research across all disciplines.
- * Many researchers lack formal training in essential research computing skills.
- * Inadequate computational practices lead to data loss, inefficient analyses, and limited software/data interaction.
Purpose of the Study:
- * To present a foundational set of good computing practices for researchers.
- * To address the gap in formal training for research computing skills.
- * To improve data management, reproducibility, and overall research efficiency.
Main Methods:
- * Synthesizing best practices from diverse published sources.
- * Incorporating practical experience from workshops delivered to over 11,000 individuals since 2010.
- * Focusing on universally applicable principles for researchers of all computational skill levels.
Main Results:
- * A comprehensive set of recommended computing practices.
- * Guidance on data management, programming, project organization, and collaboration.
- * Strategies for effective work tracking and manuscript preparation.
Conclusions:
- * Adopting these good computing practices enhances research quality and efficiency.
- * Standardizing computational workflows improves data integrity and reproducibility.
- * Empowering researchers with these skills is crucial for scientific advancement.
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