Welcome to the repository for Making (this model) FAIR. This model is part of the larger Making 100 Models FAIR project. This is a community effort to revisit widely used models, assess their alignment with current FAIR standards (see our scoring rubric here), and work to bring them closer to the best transparency and reusability standards that we can.
📝 Refer to the guidance on making a model FAIR
🔍 Find a summary of the status of this and other models, listed by category (Ecological Systems, Land Use, Cooperation, and Crowd Dynamics)
Join the community discussion to share your questions, insights, and experiences in the making FAIR process
✉️ Suggest a model that is not in our list by emailing [email protected]
Each model is assessed against the five FAIR criteria and given an associated set of scores and a status (e.g., "Not yet started", "In progress", etc.). The status is labeled in green in the associated GitHub issue of the same name in the coordination repository.
The five FAIR criteria are detailed on our scoring rubric here. The five criteria are:
- Available Code - Is the model code available in a publicly accessible repository?
- License - Does the model have a license?
- DOI - Does the model code repository have a DOI?
- Model Documentation - Does the model has detailed documentation?
- Clean Code - Is the model code cleaned up and well commented?
The status of each of these five criteria for this model can be found in the table of models. The first three criteria are a Yes/No, while the fourth and fifth criteria are a grade from A-E. Our goal is to have all "Yes" and "A" grades for a model to be considered "FAIR".
This is a community-led project that welcomes contributions from everyone, regardless of experience level. Refer to the issue associated with this model in the coordination repository to find out details about the current state of the project and identify where you can help. To contribute to this project, introduce yourself in the issue and provide any details on how you plan to contribute. Afterwards, you can start commenting on open discussions or contributing new content.
To submit a contribution, use the fork -> clone -> edit -> push -> create pull request workflow for this repository.
🍴 Fork this repository
🔨 Commit your changes to your forked repo, adding license information, documentation, and code
🎉 Open a new pull request with changes from your forked repo and get it approved!
- If this is your first time using GitHub, welcome! To take your first steps in learning more about the basic functionality of this collaborative platform, please refer to this tutorial, or navigate directly to this short course. You will need to create a GitHub account to participate.
- If this is not your first time on GitHub in general, but you have not contributed to an open source project before, here is a handy guide on how to do so.
- For general information about GitHub and Git, you can also refer to these helpful GitHub Docs
Collaborating and sharing Document your progress in the associated issue (with the same title as this model repository) in the coordination repository. Here, you can indicate when you have met a new criteria (e.g., acquiring the model code from the author). Eventually, we will develop a checklist to automate some of the documentation of progress.
This model repository is comprised of two main directories (docs and code) and one main file in the root directory (LICENSE). If there is another structure that better fits with convention for your discipline / model code, please feel free to adjust. Just make sure to include these core elements to the repository in the making-FAIR process.
You may use whatever programming language makes most sense for the model (or was provided by the model author) -- e.g., NetLogo, Python, etc. In the case that this model will be replicated in multiple programming languages, please create a subdirectory in code with the name of the language (e.g., code/python, or code/netlogo) to keep things organized and easy to navigate. Many programming platforms have a variety of dependencies, packages, and versions to keep track of in order to keep things running smoothly. Consider adding these details in your documentation.
Every contribution to this repository and the making-FAIR process has immediate benefits to the community! By making widely cited and used models more findable, accessible, and reproducible, the speed and scale of learning and innovation can grow. Consider replicating the results of the study, or exploring the parameter space of this model (potentially learning new skills and tools such as high-throughput computing).
Thank you for making such a valuable contribution to the scientific community!! 👏 👏 👏