Research data management overview

Within the University, research data are defined as the evidence that
underpins the answer to a research question and can be used to validate
findings, regardless of their form (e.g. print, digital, or physical). This includes interviews, images, surveys, observations, audio/visual recordings, medical records, maps, instrument data, spreadsheets, bibliographies, and more.

While research data differ across disciplines and are unique to each project, a set of general principles and best practices can be applied to guide their management.

Research data management (RDM) is the process of planning and undertaking the collection, organisation, management, storage, backup, preservation, and sharing of data before, during, and after the research project.

Good research data management helps you to:

• Understand the requirements, complexities, and policies which apply to your research project
• Maintain the integrity of your research process and ensure your outputs are verifiable
• Store your research data securely, and publish or share it when you're ready
• Maximise the visibility and impact of your work and ensure you receive recognition for your outputs

The research data lifecycle separates the research process into:

• Plan and design
• Create and collect
• Analyse and interpret
• Publish and report
• Discover and reuse

Each stage of the research data lifecycle requires different data management practices.

The Centre for eResearch offers in-person and online consultations free of charge to researchers (including doctoral students and their supervisors) who need advice or customised solutions to manage their research data.

Consultations can offer expert advice on collecting, organising, storing, sharing, and archiving research data, including:

• Creating a Data Management Plan (DMP) and compliance with policies impacting research data management
• Working with sensitive or restricted research data
• Using data collection and generation tools, and advice on policies impacting the use of AI in research
• Organising and describing data with metadata-rich README files to enable the FAIR principles for research data
• Identifying appropriate options for research data storage and collaborative sharing
• Accessing research compute services, including High-Performance Computing (HPC) and GPUs
• Publishing datasets and increasing the visibility of your outputs

Working in collaboration with Digital Services, we can assist in developing tailored solutions or recommending options from the wide range of services available at the University.

To request a consultation, email researchdata@auckland.ac.nz.

Ensure you understand the requirements and expectations of funders, institutions, and participants.

The University's Research Data Management Policy applies to all staff, students, supervisors, and other members of the University community who are involved in the management of research data. It outlines responsibilities relating to planning, storing, governing, publishing, retaining, and disposing of research data appropriately.

Research Data Support Services
Email: researchdata@auckland.ac.nz

eResearch Engagement Lead
Email: Laura Armstrong