Research Data Australia (RDA) is a set of web pages describing data collections produced by, or relevant to, Australian researchers. It is increasingly recognised that data is as important an output of research as publications. The Australian Code for the Responsible Conduct of Research includes the proper management and retention of the research data. Section 2 of the Code outlines the responsibilities of institutions and of researchers and encourages making research data widely available where possible.
Research Data Australia helps you find, access, and reuse data for research from over one hundred Australian research organisations, government agencies, and cultural institutions. ANDS does not store the data itself here but displays descriptions of, and links to, the data held by our data publishing partners or contributors. See the RDA About page for more information on:
- how organisations can become a contributor
- how search works
- accessing and reusing research data
How RDA works
- Owners, managers or creators of data sets create descriptions of data collections in their institutional repositories. Collection descriptions can include rich metadata such as: related people, organisations, publications, software and projects; access conditions; keywords; Field of Research Codes and more. See an example of a collection record in RDA.
- ANDS publishes these descriptions in RDA. RDA is designed to be easily indexed by big search engines such as Google and Yahoo. ANDS also has reciprocal publishing arrangements with other data collection registries and discovery portals in Australia and internationally.
- Researchers use RDA to search for, reuse and attribute data collections
In all cases the data itself remains with the custodians. Only the descriptions are published on RDA and access to the data is always at the discretion of the custodian.
Finding data in RDA
What research data collection can be included in RDA?
- Data may be digital or non-digital.
- Examples of the kinds of data of interest to researchers include survey results, data collected automatically from computer programs, sensors or instruments, images, audio and video, text corpora, even web pages and blogs.
- Some of this data will be irreplaceable, perhaps because it is part of a time series like much meteorological data, or because it relates to a particular event which has occurred only once in a specific time and place, such as the eruption of a volcano.
- Some may be costly to duplicate, perhaps because of the special instrumentation required or the difficulty of the experiment.
- All data is valuable, at least for the duration of a project, but often long after the project has been completed:
- Some of the data might be raw data, the unprocessed observations of particular phenomena. Some might be processed data, the data produced when raw data has been calibrated or corrected.
- Some might be derived data, which present a summary or specific view of the raw data.
- Some might be textual data, the publications which result from a research project or the textual data (texts, bibliographies, surveys etc.) which forms the basis of a research project.
- A good quality data collection can be enhanced by the inclusion of contextual information:
- for example, reports, grey literature, software, algorithms, workflows, calibrations etc - relating to the study, observation or investigation.
- This contextual information gives re-use value to what might otherwise be simply an unusable set of numbers or images.