Good Enough Practices in Scientific Computing
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Abstract (arXiv)
We present a set of computing tools and techniques that every researcher can and should adopt. 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 six years, and from a variety of other guides. Unlike some other guides, our recommendations are aimed specifically at people who are new to research computing.
Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). First posted on arXiv 31 Aug 2016.
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Citing papers per year: 2021: 1; 2022: 0; 2023: 0; 2024: 0; 2025: 4; 2026: 4.
9 papers.
- 2021"Garbage In, Garbage Out" Revisited: What Do Machine Learning Application Papers Report About Human-Labeled Training Data?cited by 24
- 2026AutoMOOSE: An Agentic AI for Autonomous Phase-Field Simulationcited by 2
- 2025AI Data Development: A Scorecard for the System Card Frameworkcited by 1
- 2025SurvBench: A Standardised Preprocessing Pipeline for Multi-Modal Electronic Health Record Survival Analysiscited by 1
- 2026Coding-agents can replicate scientific machine learning paperscited by 1
- 2026Scientific Agent Skills: A Library of Procedural Knowledge for Research Agentscited by 1
- 2025How Usable is Automated Feature Engineering for Tabular Data?cited by 0
- 2025A Configuration-First Framework for Reproducible, Low-Code Machine Learning: a Localization Use Casecited by 0
- 2026Accelerated Genetic Programming Hyper-Heuristics for Simulation-Based Scheduling via Agentic AIcited by 0
- 2026Scientific Agent Skills: A Library of Procedural Knowledge for Research Agents30 Aug 2026
- 2026Accelerated Genetic Programming Hyper-Heuristics for Simulation-Based Scheduling via Agentic AI19 Aug 2026
- 2026Coding-agents can replicate scientific machine learning papers2 Jul 2026
- 2026AutoMOOSE: An Agentic AI for Autonomous Phase-Field Simulation22 Mar 2026
- 2025SurvBench: A Standardised Preprocessing Pipeline for Multi-Modal Electronic Health Record Survival Analysis14 Nov 2025
- 2025A Configuration-First Framework for Reproducible, Low-Code Machine Learning: a Localization Use Case29 Oct 2025
- 2025How Usable is Automated Feature Engineering for Tabular Data?19 Aug 2025
- 2025AI Data Development: A Scorecard for the System Card Framework2 Jun 2025
- 2021"Garbage In, Garbage Out" Revisited: What Do Machine Learning Application Papers Report About Human-Labeled Training Data?5 Jul 2021