Open Science is a set of actions and principles designed to make scientific research more transparent. Spurred by a number of high-profile studies that could not be independently replicated, the Open Science movement encourages making data, research protocols, code, workflows, lab notes and other materials easily accessible for others to review and reuse.

Rigor and reproducibility are key concepts in open science. Rigor in research design and performance help to ensure that results are unbiased, and when results can be reproduced by multiple scientists, it validates the original research.

NIH Guidelines and Resources for Rigor and Reproducibility

Data Reproducibility Training Modules

HSL's guide to Rigor and Reproducibility in Biomedical Research

FAIR data is data that is Findable, Accessible, Interoperable and Reusable. In addition to available on the web, FAIR data also needs to have a persistent identifier (like a DOI), rich, machine-readable metadata, use an understandable, shared vocabulary, and have a clear provenance and data policy so it can be reused by others. More information about the FAIR principles can be found at these websites:

How to FAIR: A guide created by the Dutch National Forum for Research Data Management

Brock, J. (2019, February 11). 'A love letter to your future self': What scientists need to know about FAIR Data. Nature Index.

Multidisciplinary Open Access Repositories:
Zenodo
Figshare
Dryad

Other Tools:
Open Science Framework
OSF is operated by the nonprofit Center for Open Science, based in Charlottesville. It provides a website where researchers and research teams can store their data, protocols, references, and other materials. This site can be kept private for internal use or shared publicly.

ORCID
Many of repositories utilize ORCID IDs to verify contributors' identities and link their submissions to their ORCID profiles.

Data and Software License Selection
This tool can help you choose the appropriate license for the data or research software you want to share.

Syllabi on Open and Reproducible Methods
Faculty-contributed syllabi on these concepts