A key motivation for the ready4 software framework is standardisation. Defining and adhering to a common set of standards is important because:
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explicit, measurable standards are good modelling practice;
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to implement a modular computational model, ready4 model modules need to be interoperable (ie they can easily and safely be combined);
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as an open source project with multiple users and contributors, consistency in implementation and documentation facilitates collaboration and ease of use;
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standardised workflows are easier to partially automate.
The ready4 software framework supports implementations of computational models that are transparent, reusable and updatable.
Transparent
Model code and data are publicly available in online code repositories and data collections. Algorithms are documented and transparently and regularly tested. Model development occurs in the open and invites community participation, with each individual’s contribution publicly identifiable. Analyses are reproducible and replicable.
Reusable
Model modules and datasets originally developed in one modelling project can be independently reused in other projects. As they share a common framework, model modules can be combined in other models and analyses to address multiple topics. Due to ready4’s code implementation paradigms, model modules are easier to transfer for use in other decision contexts.
Updatable
Model code, data and analyses are versioned, with an ongoing program of making new and updated releases. Software is maintained, with opportunities for users and contributors to flag issues, request features and supply code contributions.
Our criteria for assessing transparent, reusable and updatable implementation of computational models are described in a manuscript being prepared for publication.