In this module, we have explored open workflows, their importance in reproducibility and replicability in research across disciplines and best practices for organizing files and documentation. An open workflow, generally, has the following elements:
- Publicly accessible documentation of research process and outcomes, including experimental design details, data, analysis conducted, code, etc.
- The use of best practices around file naming conventions, project metadata, file formats, tools used, etc. to enable long term preservation and access of files
As you begin the process of creating an open workflow, consider the following questions:
- Can you find existing open projects that can inspire your workflow?
- For each step in your process, are there relevant/disciplinary-specific open tools and open file formats that you should keep in mind? If your discipline does not have best practice protocols, which ones could you incorporate into your work?
- As your project moves forward and you start creating outputs, how will you keep track of things? Consider preregistering your study design and analysis information to increase transparency.
Key Takeaways
- A research workflow is a documentation of every step taken and decision made as part of a research project. By creating an open workflow, you ensure that enough information is shared about how you got from an idea to a conclusion or output, and the tools that you used along the way, to allow someone else to replicate or reproduce your findings.
- Open workflows are incredibly important for minimizing the impact of the reproducibility crises happening across many disciplines.
- Using open workflow tools (i.e., OSF) provides a central landing place for all research collaborators, project files, and versions of project documentation.
