TL;DR
This paper advocates for integrating open source tools and practices in scientific lab management to enhance reproducibility, transparency, and efficiency across various aspects like data handling, IT management, and software development.
Contribution
It provides practical examples and emphasizes the importance of open source adoption for improving reproducibility and transparency in scientific research.
Findings
Open source tools improve reproducibility and transparency.
Practical applications include website management and dataset organization.
Open source practices enhance lab efficiency and student training.
Abstract
This document explores the advantages of integrating open source software and practices in managing a scientific lab, emphasizing reproducibility and the avoidance of pitfalls. It details practical applications from website management using GitHub Pages to organizing datasets in compliance with BIDS standards, highlights the importance of continuous testing for data integrity, IT management through Ansible for efficient system configuration, open source software development. The broader goal is to promote transparent, reproducible science by adopting open source tools. This approach not only saves time but exposes students to best practices, enhancing the transparency and reproducibility of scientific research.
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Taxonomy
TopicsScientific Computing and Data Management