FAIR in (biological) practice: Glossary

Do not be shy

Be nice

Remember, you can do better research if you plan to share your outputs!

Open Science increases transparency in research

Publicly funded science should be publicly available

While both You and the research community benefit from open practices, they are costs involved in making outputs open

FAIR stands for Findable Accessible Interoperable Reusable

FAIR assures easy reuse of data underlying scientific findings

A license is a promise not to sue - therefore attach license files

For data use Creative Commons Attribution (CC BY) license (CC0 is even more permissive)

For code use open source licenses such as MIT, BSD, or Apache license

Metadata provides contextual information so that other people can understand the data.

Metadata is key for data reuse and complying with FAIR guidelines.

Metadata should be added incrementally through out the project

Public identifiers and ontologies are key to knowledge discovery

Automatic data aggregations needs standardised metadata formats and values

Never use formatting to encode information

Include only one piece of information in a cell

It is easier to store data in the correct form than to clean data for reuse

Good record keeping ensures transparency and reproducibility.

Record keeping is an integral part of data FAIRification.

Record keeping is key to good data management practices.

Having experimental details already in electronic form makes it easier to include them in READMEs or repository records

A good file name suggests the file content

Good project organization saves you time

Describe your files organization in PROJECT_STRUCTURE or README including naming convention

Jupyter Notebooks are useful tools to share analysis with non-programmers

One single document can visualise background, results, formulae/code and metadata

One single document helps to make your work more understandable, repeatable and shareable

Version control system helps maintaining good practices

Version control system keeps your work safe

Templates save time

Templates enforce best practices and ensure consistency

Templates allow for automatisation of processes

Repositories are the main means for sharing research data.

You should use data-type specific repository whenever possible.

Repositories are the key players in data reuse.

Data within a project undergo a set of steps known as the research data life cycle.

Planning can help make your data FAIR.

Data management is a continuous process during a project.

A DMP is the best way to prepare for a new project.

There are simple steps to help make your data more FAIR throughout the research data lifecycle

Implement these steps throughout to keep track of your data and changes