Ten simple rules for documenting scientific software

Lee, Benjamin D.

doi:10.1371/journal.pcbi.1006561

Cited by 56 publications

(58 citation statements)

References 9 publications

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“…In some ways, accessiblity or ability to gain access to the code means nothing if adequate documentation for the model, a description of its components, instructions on how to compile or run it, and basic examples are not provided. This is in line with recommendations contained in the literature (Lee, 2018).…”

Section: Resultssupporting

confidence: 91%

Current status on the need for improved accessibility to climate change models

Añel

García-Rodríguez

Rodeiro³

2019

Preprint

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Abstract. Over the last years, we have seen growing concerns on the need to publish computer code as an integral part of the research process. This has been reflected on improved publishing policies by scientific journals, addressing the relevant issues such as repositories or licensing. Here we explore the state-of-the-art of code availability and sharing for climate models, using as testbed the models from the Climate Model Intercomparison Project 5 and make some reflections on it. Our results show that there are great limitations in the access to the code of these climate models and that the climate modelling community needs to greatly improve their code sharing practices in order to comply with the best scientific practices and the most up to date editorial publishing policies.

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Section: Resultssupporting

confidence: 91%

Current status on the need for improved accessibility to climate change models

Añel

García-Rodríguez

Rodeiro³

2019

Preprint

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“…We provide a standard command-line interface that follows modern Unix conventions [32, 33], including providing arguments for help and the program version [18, 34], and provision of single-dash notation for short argument names and double-dash notation for long argument names. Most importantly, the --help argument causes the program to display usage information, including a description of each argument and its expected parameters.…”

Section: Resultsmentioning

confidence: 99%

“…For user documentation we provide 2 critical components: a README file that appears at the top level of the repository, and comprehensive command-line usage output via the --help argument [18, 34, 38] as discussed above. The README file includes a program description, dependencies, installation instructions, inputs and outputs, example usage, and licensing information [12, 43].…”

Section: Resultsmentioning

confidence: 99%

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Bionitio: demonstrating and facilitating best practices for bioinformatics command-line software

et al. 2019

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Background Bioinformatics software tools are often created ad hoc, frequently by people without extensive training in software development. In particular, for beginners, the barrier to entry in bioinformatics software development is high, especially if they want to adopt good programming practices. Even experienced developers do not always follow best practices. This results in the proliferation of poorer-quality bioinformatics software, leading to limited scalability and inefficient use of resources; lack of reproducibility, usability, adaptability, and interoperability; and erroneous or inaccurate results. Findings We have developed Bionitio, a tool that automates the process of starting new bioinformatics software projects following recommended best practices. With a single command, the user can create a new well-structured project in 1 of 12 programming languages. The resulting software is functional, carrying out a prototypical bioinformatics task, and thus serves as both a working example and a template for building new tools. Key features include command-line argument parsing, error handling, progress logging, defined exit status values, a test suite, a version number, standardized building and packaging, user documentation, code documentation, a standard open source software license, software revision control, and containerization. Conclusions Bionitio serves as a learning aid for beginner-to-intermediate bioinformatics programmers and provides an excellent starting point for new projects. This helps developers adopt good programming practices from the beginning of a project and encourages high-quality tools to be developed more rapidly. This also benefits users because tools are more easily installed and consistent in their usage. Bionitio is released as open source software under the MIT License and is available at https://github.com/bionitio-team/bionitio.

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“…MuMoT’s implementation, testing, and documentation seeks to adhere to the best standards for scientific software deployment [12, 13].…”

Section: Design and Implementationmentioning

confidence: 99%

Multiscale Modelling Tool: Mathematical modelling of collective behaviour without the maths

2019

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Collective behaviour is of fundamental importance in the life sciences, where it appears at levels of biological complexity from single cells to superorganisms, in demography and the social sciences, where it describes the behaviour of populations, and in the physical and engineering sciences, where it describes physical phenomena and can be used to design distributed systems. Reasoning about collective behaviour is inherently difficult, as the non-linear interactions between individuals give rise to complex emergent dynamics. Mathematical techniques have been developed to analyse systematically collective behaviour in such systems, yet these frequently require extensive formal training and technical ability to apply. Even for those with the requisite training and ability, analysis using these techniques can be laborious, time-consuming and error-prone. Together these difficulties raise a barrier-to-entry for practitioners wishing to analyse models of collective behaviour. However, rigorous modelling of collective behaviour is required to make progress in understanding and applying it. Here we present an accessible tool which aims to automate the process of modelling and analysing collective behaviour, as far as possible. We focus our attention on the general class of systems described by reaction kinetics, involving interactions between components that change state as a result, as these are easily understood and extracted from data by natural, physical and social scientists, and correspond to algorithms for component-level controllers in engineering applications. By providing simple automated access to advanced mathematical techniques from statistical physics, nonlinear dynamical systems analysis, and computational simulation, we hope to advance standards in modelling collective behaviour. At the same time, by providing expert users with access to the results of automated analyses, sophisticated investigations that could take significant effort are substantially facilitated. Our tool can be accessed online without installing software, uses a simple programmatic interface, and provides interactive graphical plots for users to develop understanding of their models.

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Ten simple rules for documenting scientific software

Cited by 56 publications

References 9 publications

Current status on the need for improved accessibility to climate change models

Current status on the need for improved accessibility to climate change models

Bionitio: demonstrating and facilitating best practices for bioinformatics command-line software

Multiscale Modelling Tool: Mathematical modelling of collective behaviour without the maths

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