alterlab-open-science

Preregistration on OSF involves selecting an AsPredicted or OSF Registries template to document hypotheses and analysis plans before data collection. This Skill provides templates and platform recommendations to initialize your project.

FAIR data principles ensure research outputs are Findable, Accessible, Interoperable, and Reusable. This Skill guides you through implementing FAIR data sharing, including repository selection and applying appropriate licenses to datasets.

Green, Gold, and Diamond open access represent different routes for publishing research, varying by repository archiving versus journal fees. This Skill helps you navigate these publishing routes and implement rights retention strategies.

Creating a data management plan for NSF or NIH requires outlining how data will be managed, shared, and preserved according to funder guidelines. This Skill provides structured guidance to align your data management plans with specific funder requirements.

Registered reports involve a two-stage process where Stage 1 accepts your proposal based on methodology before data collection, and Stage 2 publishes results after peer review. This Skill mentors you through Stage 1 IPA and Stage 2 follow-up workflows.

Reproducible computational workflows use containers, notebooks, and code sharing to ensure analyses can be reliably executed by others. This Skill offers best practices for computational notebooks and reproducibility workflows to implement transparency.