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Research Data Management: Working with data and materials

Working with data and materials

 

To securely collect, process and analyse your research data, you need to have a plan in place for organisation and storage. The Australian Code for the Responsible Conduct of Research 2018 requires researchers to retain clear, accurate, secure, and complete records of all research data and primary materials. The supporting guide, Management of Data and Information in Research, assists researchers to adhere to the principles of the Code. 

UTS provides policies, guidance and data storage options for UTS researchers according to the research data's security classification.  As outlined in the UTS Research Data Management Procedure, researchers are required to understand and apply the appropriate security classification to their data, and to use appropriate infrastructure to store their data. 

UTS Information Security Classification Standard

 

UTS Researchers should classify their data according to the UTS Information Security Classification Standard, which governs how data can be stored, accessed, and shared, based on the level of risk involved. In terms of research data, examples include:

Use the UTS Research Data Classifier Decision Support Tool to classify your data and select the appropriate storage option.

How to choose the right storage for you

 

UTS has several storage solutions that can be tailored to your research needs during a project. The table below describes some key storage platforms and the data classifications they support.

Table of data storage options at UTS

OneDrive storage is automatically available through Office365. Ensure you are using UTS OneDrive for your data storage (accessible using your UTS sign in details); not a personal OneDrive account.
eResearch store can be requested via the final section of your Research Data Management Plan created in Stash.

Secure and efficient data practices

 

Setting up effective practices for organising your data is a crucial aspect of Research Data Management. Proper organisation helps facilitate efficient data analysis, and improves data integrity, reproducibility.  It is especially important when the project involves multiple people. Key components of data organisation include: