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Health Data - Secondary Datasets

A Subject Guide to finding Health Data Secondary Datasets

What is plagiaism?

Referencing is important in academic work to inform others the source of your ideas and make sure you are not copying or plagiarising. When referencing other’s work (e.g.: ideas, theories, quotes, methods, data), you are required to acknowledge the original sources and cite them in your work with the recognized citation style to avoid plagiarism.

You may also use bibliographic management tools to help generate the in-text citations and reference list entries, and organise the references better in a few clicks to save your time and effort.

Please visit our Referencing & Citation page to learn more.

How to cite Data and Statistics?

Data requires citations for the same reasons journal articles and other types of publications require citations: to acknowledge the original author/producer and to help other researchers find the resource. Though standards for the citation of data are not uniformly agreed upon, many data providers and distributors and some style manuals do provide guidelines.

APA Style:

O’Donohue, W. (2017). Content analysis of undergraduate psychology textbooks (ICPSR 21600; Version V1) [Data set]. ICPSR. https://doi.org/10.3886/ICPSR36966.v1

[See Reference site]

MLA Style:

Since MLA has not developed a specific citation style for datasets, the general rules for citing a web document may be applied. 

  • Author Last Name, First Name. Title of data set. (Version). Publisher location: Publisher name, Date of publication. Medium of publication. Date accessed. doi/url of data

Chicago:

  • NASA/IPAC Extragalactic Database (object name IRAS F00400+4059; accessed April 6, 2016), http://ned.ipac.caltech.edu/

[See Reference site]

Useful Resources on Referencing & Citation

Citation Styles

User Guides of Bibliographic Management Tools

Self-help Materials on Referencing & Citation

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