Glossary Glossary

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The academic community is increasingly moving towards making research data more openly available, as reflected in funder requirements and journal guidelines. As a senior researcher, appropriately managing and sharing your data demonstrates research integrity by enabling you to adequately follow the necessary guidelines for your discipline and the type of data you collect, as well as supporting transparency and openness in research. You can further this by ensuring that your data are findable, accessible and interoperable, with further reuse value (also known as the FAIR principles: Wilkinson et al., 2016). When working with Indigenous communities, the CARE principles for Indigenous data governance also apply: those are that collection/use of data should be for collective benefit, Indigenous communities are given an authority to govern their data, relationships with Indigenous Peoples are nurtured respectfully and ethics are at the core of managing Indigenous data.

 Additional information Additional information

The process of going through the research lifecycle with data will involve different activities depending on the type of research and data collected. The guide to the Management of Data and Information in Research by the National Health & Medical Research Council, Australian Research Council and Universities Australia (2019) outlines the responsibilities of researchers and research institutions with respect to management of research data. In particular, the guide addresses the appropriate generation, collection, access, use analysis, disclosure, storage, retention, disposal, sharing and re-use of data in research.

Research data refers to any information that has been collected, observed, generated or created to answer a research question and or validate research findings. The concept of data can take many forms — both physical and digital — and hold different meanings depending on the context (Khan, 2021). Types of data can include:

  • Raw data generated from an experiment, such as proteins or genetic sequences
  • Text and multimedia files generated as part of qualitative data collection, such as audio and video tapes, photographs, films or text files extracted from a corpus of texts
  • Video or audio recordings of performing arts
  • Artifacts and samples from physical sites
  • Electronic health records or patient data
  • Software and code written to generate, process, analyse and validate research data, such as code to analyse a corpus of texts, models and algorithms
  • Derived data combining multiple sources.

Select each segment of the research lifecycle to explore the considerations to make in relation to data through the different stages.

Continue on to explore the considerations to make in relation to data through the different stages of the research lifecycle.

Consider the different parts of the research lifecycle and explore the considerations to make in relation to data through the different stages.

Considering the different stages of the lifecycle of data from the very beginning of your research project allows you to create a data management plan, as outlined in the guide to support the Code: Management of Data and Information in Research. This plan ensures that your project will comply with funder, legislative or contractual obligations, supporting the robust integrity of your research. It is important to consult with individual funders on their specific requirements for research data, such as how long data should be preserved after the research has happened. A good data management plan also ensures that:

  • Adequate data storage is in place
  • A secure mechanism is established for sharing data with collaborators
  • The data collection and storage methods are compliant with ethical considerations and appropriate for the context
  • An agreed system for data documentation will ensure that the meaning of data can be correctly interpreted by everyone involved
  • A data curation process outlines each step of collecting, managing and preserving data, as well as who is responsible for these tasks
  • The data can be discovered and used by others while giving credit to the data producers.

Read the situations involving research data management planning and select the response or responses that you think are most appropriate. Use the 'Check answer' to register your response(s) and get feedback on whether you are correct.

Consider the situations involving research data management planning and select the response or responses that you think are correct. Continue on for some feedback.

You have started planning the data management process for your upcoming research project. Which one of the following steps is less relevant to consider?

 The data collection process Where data will be held during research How data will be shared with the collaborators Which research papers will be published using the data How data will be processed

Publishing papers using the associated data is a key exercise in research. However, this does not need to be identified at the earliest stage of data management planning and is not a vital consideration when deciding how to collect, store and process your data.

You are collecting data in a digital format and need to store them securely. Which of the following options are suitable to store your data during research? Select more than one answer.

 Personal emails or cloud storage University's network drive Hard drive On your laptop desktop Data Safe Haven

If available, it is safest to use your university's network drive or Data Safe Haven services to securely store your data. Your data should be backed up in at least one other format, such as a hard drive that is physically stored in a secure place to avoid any data breach.

Which of the following aspects should be considered when choosing your data format? Select more than one answer.

 All of the planned uses and conversions Best practices for the data type Conversion to an open and interchangeable format Lossy or compressed file format to save space Preservation in a long-lasting format for accessibility

At the point of data collection, the format is often determined by the type of software used to collect data. During this phase, you will decide the most appropriate format for planned data analysis/use: for long-term preservation and access, data should be converted into an open, interchangeable and long-lasting format.

Which one of the following is not essential information to include in a file name?

 Creator name Version Date Subject or file content Participant/experiment/instrument identifier

The creator's name is not essential to include in a file or folder name. It can make the file name long and difficult to locate, so initials can be used as part of a version identifier instead. It is good practice to agree a file and folder naming convention to be followed by all team members throughout the project.

You have reached the end of your research project. What are the ways you can archive the data? Select more than one answer.

 A project website Your institution's research data repository Google Drive A journal's data archive A disciplinary data repository

For long-term access and usability, you should archive data at the end of the project in a data repository. This could be your institution's own research data repository or a disciplinary/interdisciplinary repository, such as Zenodo and Figshare. It could also be a journal's data repository if required for publication. Early engagement with your institution's research data management team will help you plan for an appropriate repository at the end of your project.

Ensuring that you have a pragmatic data management plan in place to support the reproducibility of your research project will also help you to efficiently handle data throughout the lifecycle of research data. This leads to further innovation and collaboration in research and maintains the integrity of the project throughout the research process.

 Useful links Useful links

For data management plans: