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Research essentials

A guide for Higher Degree by Research, Masters and Honours students, and Early Career Researchers. Book sessions in our training calendar.

Working with research data

Research data is a valuable product of research activity. It complements research outputs and publications.

How your research data will be managed should be a key consideration when planning your research project. The ACU Research Data Management Policy outlines your responsibilities.

Use this guide, in conjunction with the ACU research data management toolkit, to identify where to start and what you need to have in place to ensure your research data is effectively managed.

Plan your data management

In accordance with the Australian Code for the Responsible Conduct of Research (The 2018 Code) and the ACU Research Data Management Policy, ACU researchers are responsible for maintaining accurate, complete, safe, secure and retrievable records of research approach, sources, data and primary materials.

A research data management plan will ensure you meet your responsibilities, including ethical decisions concerning the research data, and provide you with the answers to these questions:

  • What data will you produce?
  • Who will have access to the data?
  • How will you obtain informed consent from your study participants (if applicable)?
  • Are you aware of best practice for file naming and version management?
  • How will you document and organise your data and what file formats are most appropriate?
  • Where will your data be stored during the project?
  • What is the plan for retention or disposal of your data?
  • Does your data require de-identifying or anonymising?

Our research data management toolkit contains a template, and all the tools to assist you.

Ensuring your research data is FAIR

Ensuring your research data is FAIR (Findable, Accessible, Interoperable & Reusable), provides research transparency, promotes inquiry and debate and enables innovative uses of data that may not have been foreseen by the researchers at the time the data was generated.

FAIR data principles

The FAIR Data Principles (Findable, Accessible, Interoperable and Reusable) are a set of guiding principles proposed by a consortium of scientists and organisations to support the reusability of digital assets. Learn more about making your data FAIR.

CARE principles

The CARE Principles for Indigenous Data Governance are people and purpose-oriented, reflecting the crucial role of data in advancing Indigenous innovation and self-determination. These principles (Collective Benefit, Authority to Control, Responsibility and Ethics) complement the existing FAIR principles encouraging open and other data movements to consider both people and purpose in their advocacy and pursuits.

Ethics and Consent

How and why you manage your research data are ethical decisions.

Ethics approval is required for all research conducted at Australian Catholic University, involving people, personal data, and human tissue, as well as research involving animals.

When you are completing your research data management plan, you will need to document your ethical decisions concerning the research data you will be collecting. Read more at ethics and consent.

Tools for creating and analysing data

ACU researchers are provided with access to a range of tools and services to enhance data workflows across the research lifecycle. There are also many free and open-source data tools available. Explore options early and adopt a TRUST framework for tool evaluation:

Transparency - Does the tool explain how it works? Are its methods and algorithms documented?

Relevance - Is it suited to your data type, research questions, and audience?

Usability - Is it intuitive? Are there guides, support, and communities to help you learn it?

Security and ethics - Does it align with ethical research practices? How does it handle sensitive data?

Trustworthiness - Who developed it? Is it widely used or cited? Are there known issues or biases?

Adapted from Good Data Practices (ARDC, 2025) and TRUST principles (ARDC, 2025)

Quantitative data

ACU-supported tools for researchers working with quantitative data and statistical analysis include:

  • Microsoft 365 suite of online and offline tools, including Excel (available for installation on ACU and personal computers)

  • SPSS - IBM's advanced statistical software platform (installed on ACU computer labs; available via Software Centre, home license by request)

The following tools are free or open source. Seek assistance from IT or Service Central if required.

  • R and RStudio (now Posit) - a programming language and environment for statistical computing and graphics.
  • Python - open-source programming language that enables data and network analysis.

Survey tools

ACU provides access to a range of survey tools to help researchers collate and analyse data including:

Qualitative data

  • NVivo - qualitative and mixed methods data analysis software (available for installation on ACU and personal computers)
  • Leximancer - specialist analytics software for unstructured, qualitative textual data (available for installation via ACU Software Centre)

Australian Research Data Commons

The ARDC provides an abundance of tools and services to support collaborative research data workflows, including cloud-based computing, secure access research environments, and discipline-specific platforms and tools:

AI and ML Tools for research are currently being developed via the ARDC Nectar Research Cloud and partner services.

Expand your research data opportunities

Visit eResearch to discover more tools and additional support.

See our text and data mining and data visualisation guides for more ways to discover and communicate research data.