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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.

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|June 23, 2017
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Summary
This summary is machine-generated.

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.

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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.