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Data must be able to be discovered and accessed before it can be reused. The value in data resources is in the discovery and knowledge that are built from them, not necessarily in the data themselves. Not all data that is discoverable can be freely accessed. Often there are embargoes, access controls, permissions or licences associated with data due to a variety of issues such as confidentiality, reuse permissions, commercial interests etc. Other issues that could be perceived as blockers to sharing data may be overcome.

Research Data Australia

Research Data Australia logo

Research Data Australia is a discovery service for Australian research data. It provides access to thousands of research datasets from Australia and around the world. It is a mesh of searchable web pages describing (and where possible linking to) Australian research data collections.
The records in Research Data Australia come from Australian research institutions and contain metadata about the data collections. The record may link directly to the described data, or to a resource or web page that describes how to access the data.

There are many data discovery portals and data catalogues maintained by other organisations.

Connection Strategy

Research Data Australia is part of our connections strategy. It is designed to allow researchers and research organisations to publish the existence of research data and to allow prospective users of that data to discover it and evaluate its possible applicability to new research.

The data connections strategy incorporates common referencing methods for researchers, research groups, research activities, places, research datasets, research fields, scholarly or scientific terminology, data tools/services, and data themselves. We believe rich connections amoung the above mentioned entities will increase discoverability, accessibility and reuseability of data.


FAIR data are a set of community generated guiding principles intended to be high-level principles that are concise and domain independent, which apply equally to metadata as to data i.e. to “facilitate knowledge discovery by assisting humans and machines in their discovery of, access to, integration and analysis of, task-appropriate scientific data and their associated algorithms and workflows”.

The four FAIR "facets" are that data should be:

  • Findable
  • Accessible
  • Interoperable
  • Reusable

More information on FAIR: Nature article, and at Force 11.