Open data

Data sharing is fundamental to open research. Open data practices improve access to research datasets by making them findable, accessible, reusable and interoperable (FAIR). FAIR and open research data can: 

• improve integrity of research and accountability 
• validate research findings 
• reduce the cost of duplication 
• accelerate knowledge discovery, generate collaborations, and benefit society.

Data should be 'as open as possible, and closed as necessary' in line with ethical and legal obligations.

About FAIR data

Many funders and journals now require research data to be shared in line with the FAIR principles. Consider how you will adopt and apply them to any datasets you generate.

Findable

Published with rich, descriptive metadata and with a permanent direct object identifier (DOI).

Accessible

Use machine readable metadata records online and open protocols to download datafiles.

Interoperable

Use standard vocabularies/ontologies, and data is stored in open standard formats for reuse and integration.

Reusable

Have clear license conditions for access and use, and well described provenance on where the data came from. Dataset can be cited.

Visit Making Data FAIR to learn more.

Indigenous research data

Researchers working with Indigenous research data (for example data related to Aboriginal or Torres Strait Islander peoples) should apply the CARE Principles of Collective Benefit, Authority to Control, Responsibility and Ethics.

Visit: 

• CARE Principles for Indigenous Data Governance to learn more
• Indigenous research data management for a guide and resources for the ethical management of Indigenous research data.

Manage your research data

Visit Manage your research data to read about:

• creating a data management plan
• storing and publishing your data
• sharing research data.