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paper.bib

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@article{Barker:2022aa,
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abstract = {Research software is a fundamental and vital part of research, yet significant challenges to discoverability, productivity, quality, reproducibility, and sustainability exist. Improving the practice of scholarship is a common goal of the open science, open source, and FAIR (Findable, Accessible, Interoperable and Reusable) communities and research software is now being understood as a type of digital object to which FAIR should be applied. This emergence reflects a maturation of the research community to better understand the crucial role of FAIR research software in maximising research value. The FAIR for Research Software (FAIR4RS) Working Group has adapted the FAIR Guiding Principles to create the FAIR Principles for Research Software (FAIR4RS Principles). The contents and context of the FAIR4RS Principles are summarised here to provide the basis for discussion of their adoption. Examples of implementation by organisations are provided to share information on how to maximise the value of research outputs, and to encourage others to amplify the importance and impact of this work.},
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author = {Barker, Michelle and Chue Hong, Neil P. and Katz, Daniel S. and Lamprecht, Anna-Lena and Martinez-Ortiz, Carlos and Psomopoulos, Fotis and Harrow, Jennifer and Castro, Leyla Jael and Gruenpeter, Morane and Martinez, Paula Andrea and Honeyman, Tom},
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doi = {10.1038/s41597-022-01710-x},
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isbn = {2052-4463},
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journal = {Scientific Data},
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number = {1},
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pages = {622},
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title = {Introducing the FAIR Principles for research software},
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url = {https://doi.org/10.1038/s41597-022-01710-x},
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volume = {9},
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year = {2022},
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bdsk-url-1 = {https://doi.org/10.1038/s41597-022-01710-x}}
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@article{Matplotlib_2007,
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author = {Hunter, John D.},
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doi = {10.1109/MCSE.2007.55},

paper.md

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# Statement of Need
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Today’s geoscientists require not only domain expertise but also proficiency with specialized software and high-level technical skills to effectively analyze, manipulate, and manage potentially vast volumes of digital data in a complex and ever-changing computing environment. The scientific Python ecosystem and the emergence of cloud computing have been game-changers for many, providing an abundance of open-source tools with wide ranging functionality. Ironically, however, this abundance is often untapped, and can be a source of great frustration. Scientists spend an inordinate amount of time pondering questions such as: Which tool or technology should I use? How do I use it? Can I trust it? Is it compatible with other tools in my workflow? Often, the answers are unclear, due to inadequate documentation or difficulty in finding relevant up-to-date working examples. The result is too much time spent navigating or avoiding technology—time that could have been spent productively doing science. Pythia Foundations fills this need by providing a trusted community-owned, web-accessible, geoscience-specific education and training resource for scientists and students at all career stages who want to know what tools to use and how to use them to explore their data.
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The Foundations book embodies the FAIR principles [@wilkinson_fair_2016] that play a central role in open science. Findability is served by gathering geoscience-specific tutorials into a high-visibility community archive. Accessibility is served by our automated CI testing and integrated public binder. Tutorials and example code are largely Interoperable due to reliance on a common ecosystem of tools (e.g., NumPy and Xarray). Reusability is addressed through permissive licensing of book content and geoscience relevance of the examples, as well as our commitment to maintaining up-to-date working examples—an essential need in light of the widespread problem of rapid obsolescence of computational notebooks [@pimentel_2019].
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The Foundations book embodies the FAIR principles [@wilkinson_fair_2016; @Barker:2022aa] that play a central role in open science. Findability is served by gathering geoscience-specific tutorials into a high-visibility community archive. Accessibility is served by our automated CI testing and integrated public binder. Tutorials and example code are largely Interoperable due to reliance on a common ecosystem of tools (e.g., NumPy and Xarray). Reusability is addressed through permissive licensing of book content and geoscience relevance of the examples, as well as our commitment to maintaining up-to-date working examples—an essential need in light of the widespread problem of rapid obsolescence of computational notebooks [@pimentel_2019].
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# Content, instructional design, and usage
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The scope of Pythia Foundations is limited to tools and packages that are currently in broad use across multiple geoscience disciplines; packages tailored to more narrow scientific domains are not covered in Foundations but may be suitable for a Cookbook. The book outline was designed collaboratively by the core author team, informed by community feedback, and drawing on our substantial collective experience in teaching Python-based scientific workflows in classrooms, workshops, and outreach events.

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