About Making Models FAIR

The goal of this initiative is to provide capacity-building opportunities to improve the skill, practices, and protocols to make computational models findable, accessible, interoperable, and reusable (FAIR).

We have selected a list of highly cited papers in different domains and developed a protocol for making those models FAIR. Our aim is to make over 100 models FAIR, with the help of the modeling community. We will stimulate activities to advance model analysis of those FAIR models using high throughput computing.


Learn more about the initiative and process below!

What is it?

A capacity-building, community driven initiative to increase the transparency and reproducibility of a selection of the most highly cited models across the social and ecological sciences. Learn more on the Details page.

Why get involved?

This initiative can be a great way to build your network and meet collaborators, introduce model replication challenges to your students, or simply contribute to a common good by making more models reproducible and interoperable. Learn more on the Details page.

How to get started

Learn about the FAIR principles, review the Making Models Fair Process, check out the Models list, and contact us with any questions. Learn more about the steps to get involved on the Getting Involved page.

Process for making a model FAIR

flowchart TD List(Check out model publications list) --> Identify(Identify what you would like to work on) Identify -- Choose from list --> Status(Check model status in making FAIR process) Identify -- Suggest new model --> Assess(Assess FAIR criteria and assign a score) Status -- Not yet started --> Create_repo(Create new GitHub issue, request repository) Status -- In process --> Collab(Collaborate on GitHub, contribute to community discussions) Create_repo --> Collab Collab --> FAIR(Make model FAIR!) Learn_GitHub([fab:fa-github Learn more about GitHub]) --- Collab Learn_FAIR([fas:fa-lightbulb Learn more about FAIR principles]) ---- FAIR Assess --> Create_repo FAIR --> Analyze(Do model analysis, replication studies) Analyze --> Paper(Write and publish paper or report) Paper --> Credit(Get credit for your hard work!) click List href "https://tobefair.org/docs/getting-involved/checklist/#one" _blank click Identify href "https://tobefair.org/docs/getting-involved/checklist/#two" _blank click Assess href "https://tobefair.org/docs/process/assessment" _blank click Status href "https://tobefair.org/docs/models/#selecting-a-model-and-getting-started" _blank click Create_repo href "https://tobefair.org/docs/getting-involved/checklist/#four" _blank click Collab href "https://github.com/orgs/make-models-fair/discussions" _blank click Learn_GitHub href "https://comses.net/education/intro-to-git-github/" _blank click Learn_FAIR href "https://comses.net/education/responsible-practices" _blank click Credit href "https://tobefair.org/docs/process/#__get-your-fair-share__" _blank class Learn_GitHub,Learn_FAIR,GitHub_tutorial,GitHub_intro learn class Analyze,Paper optional classDef node font-weight:bold,stroke-width:3px,stroke:#30638E,color:#403F4C classDef learn font-weight:bold,stroke-width:3px,stroke:orange,color:#403F4C classDef optional stroke-dasharray: 5 5 linkStyle default stroke:#403F4C,color:#403F4C

New to Git and GitHub?

Please refer to this step-by-step tutorial to get started with GitHub, and read this introduction from GitHub Docs to dig a bit deeper.