What are the best ways to make simulation models transparent and reproducible?

1 Document your assumptions

One of the first steps to make your simulation models transparent and reproducible is to document your assumptions. Assumptions are the simplifications and approximations that you make to represent the real-world system in your model. They can affect the validity and reliability of your results, so you need to justify and communicate them clearly. You can use a table, a diagram, or a text file to list your assumptions, their sources, and their impacts on your model.

2 Use standard formats and tools

Another way to make your simulation models transparent and reproducible is to use standard formats and tools for your data, code, and outputs. Standard formats and tools are widely recognized and accepted by the simulation community, and they can facilitate the sharing and reuse of your models. For example, you can use CSV files for your data, Python or R for your code, and HTML or PDF for your outputs. You can also use open-source software and libraries that are well-documented and maintained.

3 Apply version control and testing

A third way to make your simulation models transparent and reproducible is to apply version control and testing to your model development and execution. Version control is a system that tracks the changes and history of your code and data, and allows you to revert to previous versions if needed. Testing is a process that checks the functionality and accuracy of your code and data, and detects any errors or bugs. You can use tools like Git or SVN for version control, and tools like PyTest or RUnit for testing.

4 Share your model and results

A fourth way to make your simulation models transparent and reproducible is to share your model and results with other researchers and stakeholders. Sharing your model and results can increase the visibility and impact of your work, and invite feedback and collaboration. You can use platforms like GitHub or Zenodo to host your code and data, and platforms like Figshare or OSF to publish your outputs. You can also use tools like Binder or Shiny to create interactive web applications that allow others to run and explore your model.

5 Follow ethical principles

A fifth way to make your simulation models transparent and reproducible is to follow ethical principles in your modeling practice. Ethical principles are the norms and values that guide your conduct and responsibility as a simulation modeler. They can help you avoid bias, plagiarism, fraud, and harm in your work, and respect the rights and interests of others. You can follow ethical principles such as honesty, integrity, accountability, quality, and fairness in your simulation modeling.

6 Learn from others

A sixth way to make your simulation models transparent and reproducible is to learn from others who have experience and expertise in simulation modeling. Learning from others can help you improve your skills and knowledge, and discover new methods and tools for your modeling. You can learn from others by reading publications, attending workshops, joining online forums, and participating in peer review. You can also seek mentorship, feedback, and collaboration from other simulation modelers in your field or domain.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?