In many fields of science, managing and structuring data in FAIR, transparent, and discoverable ways can be a major barrier to fully using data collected from a study. This is especially true of larger studies, as experienced in many human health fields. This is largely a software and training issue, complicated by the fact that funding is often restricted for this type of work as it is often undervalued. For this project, we aim to build software tools and training documentation that make it easier to manage and work with data. More details are found on the landing page of the website.
Looking to contribute? Check out our contributing guidelines. Please note that the Seedcase project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.