Starting your own research from the existing data collected by other researchers can have some major benefits:
However, careful consideration is required before reusing data.
Licenses and user agreements
Considering these aspects will help you determine if the data is suitable for you to reuse.
For guidance on finding and reusing datasets, consult the How To Find Datasets library guide below.
How To Find Datasets
The Curtin library guide to finding and reusing datasets.
Can I reuse someone else’s research data?
Information and issues around data reuse from OpenAIRE.
When reusing the data of others, it’s critical to give proper attribution to the work of the original creator. This is called data citation and refers to the practice of referencing data to acknowledge it’s source, in the same way as referencing a book or journal article.
Citing data is important because it:
However, because the citation of data is a relatively new practice, the standards to follow are often unclear - referencing software like Endnote does have a template for datasets, but other requirements may mean the generated references need to be modified.
You should consider the following in order of precedence:
If these requirements are unclear or informal, DataCite recommends including the following elements:
Creator (PublicationYear). Title. Version. Publisher. ResourceType. Identifier
How To Cite Datasets and Link to Publications
A guide from the Digital Curation Centre to the principles and issues around data citation with How-To instructions for authors.
A Description of Data Citation Instructions in Style Guides [PDF, 714kB]
This poster from Purdue University summarises the data citation requirements of the major style manuals and academic associations.
Datacite - Cite Your Data
An outline of the default format of data citation.