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Managing research data

Collecting and creating research data

In order to optimise project efficiency and avoid information loss and duplication, researchers should have a research data management plan in place and employ good management practices. These practices vary across disciplines, but the essential elements include:

  • stable storage formats and regular backup to an external source
  • a well-planned file naming and organisation scheme
  • version control and other relevant mechanisms for datasets, algorithms, models and software configuration management
  • workflow documentation with provenance information for instruments (use and calibration) and software used
  • adherence to appropriate national and international standards for scientific terminology and information encoding
  • recording of metadata to ensure your data is findable, reusable and reproducible
  • following cultural protocols and ensuring appropriate approvals are in place for the collection of the data

UOW have approved the use of REDCap (Research Electronic Data Capture) and Qualtrics for the collection and creation of research data. The following table shows some of the different features: 

Features REDCap Qualtrics
Complies with Australian privacy laws Yes Yes
Complies with UOW policies and procedures Yes Yes
Suitable for sensitive data Yes No
Secure access via VPN and multifactor authentication Yes No
Managed by UOW Yes No - Qualtrics
Data held at UOW Yes No
Data held in Australia Yes Yes
Data encrypted at rest and in transit Yes Yes

Researchers are responsible for routine back-up of their data and for their own archive/data retention in accordance with the UOW Records Management Policy and any other ethics, legislation or funding requirements. 

Note: Qualtrics and REDCap are tools designed for data collection and/or analysis and should not be regarded as long term storage platforms for research data. Post data collection, all data should be extracted from Qualtrics and REDCap, a PDF version of the project forms downloaded and saved with the data, and the projects closed. Researchers can request storage on an approved UOW Research Data Storage Platform for their research data by completing a Research Data Management Plan in ReDBox.

For more information, see KBAs here for and . 

To ensure the longevity of research data, it's crucial to choose a durable and accessible format that can withstand the lifetime of the project and any retention periods required by law or convention. This means selecting a format that is both readable and usable for the foreseeable future and taking into account the need for long-term readability. 

To make sure your data stays accessible, it's best to use standard, interchangeable formats that most software can understand. Open (non-proprietary) formats are especially good, because they don't rely on any particular software to read them. 

There are lots of different formats you can use, and it's up to you to decide what works best for your project. The UK Data Service has some recommendations for formats that are good for sharing and preserving data.

Here are some tips for file naming and organisation: 

  1. Agree on file naming conventions with your team before creating data. The conventions should be based on the nature and size of the project. 
  2. Use unique, persistent, and consistently applied file names without punctuation or special characters. Use hyphens or underscores instead of spaces, especially if files will be accessed via a web browser. Use the format YYYYMMDD for dates in file names to ensure chronological order. 
  3. Avoid lengthy file names and consider using version numbers or status information (e.g., draft or final) if there are multiple versions. 
  4. Always include titles, project name, author names, and contact details (including university/agency affiliation, dates, and version information) in documents. 
  5. Use clear and unambiguous column and row labels in spreadsheets. 

To make your research data easier to find, reuse, review, share and publish, you must record metadata in your Research Data Management Plan (using ReDBox). Metadata is information about your data – for example, who created it, when it was made, what it's about and if there are any rights or license terms and how to access the data. 

There are different types of metadata: 

  • Administrative metadata, which helps you manage your dataset. This includes file size, creator details, and retention periods. 
  • Descriptive metadata, which helps you find and retrieve your data. This includes title, keywords, and unique identifiers. 
  • Structural metadata, which explains how your data is organised and relates to other collections. 
  • Provenance metadata, which explains the instrument(s) used to collect the data and any calibration information. 

For example, if you have a photo, its metadata might include the camera used, how big it is and when it was created. If you have a text document, its metadata might include information about the author and when it was written. You can use simple templates to add or remove metadata elements, and sometimes you might need to use specific schemas or standards for different purposes or disciplines. More information can be found on the Australian Research Data Commons (ARDC) website

There is some helpful information on the ARDC website about things to consider when working with sensitive data and things to consider when de-identifying data. 

Refer to UOW ethical guidance for further information. 

The ARDC website has some helpful information about data versioning, in two locations online.

Please refer to our information online, regarding ethics at UOW.