Research Data Management - Research Guide

Research data is a valid form of research output and is increasingly being recognised as a valuable asset which should be managed and, when appropriate, shared. Some journals now require that data be made available to support research conclusions and the sharing of data or the provision of a data management plan may be required as a condition of research funding.

What is research data?
Research data can be anything that may be needed to validate the results of research. Not only is it the product of research, it could also be the starting point for future research.

Research data may include statistical data and analyses, measurements, questionnaires, interview transcripts, laboratory or fieldwork notes, images, sound or video recordings, and artefacts. The data could be physical or digital; it may be original, transcribed or anonymised. Research data may have been created by and for a range of people and services. Data collected for one purpose may be repurposed by another set of researchers.

Why is managing your research data important?
Good data management allows you to:

• Comply with the University's Responsible Conduct of Research Policy
• Work more efficiently
• Achieve greater exposure for your research through publication, citation and collaboration
• Improve grant funding opportunities
• Protect your data from misuse or loss
• Enable future researchers to build upon your work

The FAIR principles were developed to address the challenges of data-intensive research by making data:

F indable: The first step in (re)using data is to find it. Data should have a unique persistent identifier, be described using rich metadata and be easy to find for both humans and computers

A ccessible: Once the data is found, the user needs to know how they may access the data, including authentication or authorisation, as well as any conditions governing access and reuse

I nteroperable: The data need to integrate with other data, use community accepted languages, formats and vocabularies in the data and metadata, and interoperate with applications or workflows for analysis, storage and processing

R eusable: Data and metadata should be well-described so that they can be replicated and/or combined in different settings

The principles emphasise machine-actionability because humans increasingly rely on computational support to deal with data as a result of the increase in volume, complexity and creation speed of data.

This Piers Video Production documentary, Digital Curation Centre: Managing Research Data, offers an insight into the importance of providing access to research data and the risks of not managing data effectively. The Australian equivalent of the Digital Curation Centre is the Australian Research Data Commons (ARDC).

• Murdoch Research Portal
• Copyright Matters

Material from ANDS (Australian National Data Service), ARDC (Australian Research Data Commons) and other research institutions assisted in the compilation of this guide. They are gratefully acknowledged.