Data and the FAIR Principles: Reference

There are a number of practical guidelines and best practices for ensuring data supports reproducible research

This module is in line with our overall goal of making science (including scientific training) more open by ensuring that data is made FAIR (Findable, Accessible, Interoperable, and Reusable).

Understanding the FAIR Data principles

Understanding identification of FAIR data

Understanding ethics surrounding the data ecosystem

There exist well defined recommendations for publishing data.

There are practical guidelines and tools to assist in the publication of data.

There are a number of tools, developed by the research community and also by companies, to assist in stewardship of laboratory data.

There are a number of options for developing your own custom database solution.

How to develop a semantic data representation for your data.