Research data management toolkit

Use this guide to assist in your data management planning.


This Toolkit will help you to determine your research data management needs and create a data management plan that documents how data will be managed during the research process and after the project is completed. 

The appropriate management of research data means that you will:

  • ensure its long term preservation and access - you and others can easily find and access data when and where you need it
  • guarantee the authenticity of research data
  • facilitate validation and verification of your results
  • meet the requirements of funding bodies, publishers and The University.

What is Research Data?

Research Data is "data generated throughout and beyond the research life-cycle. Data that are in the form of facts, observations, images, computer program results, recordings, measurements or experiences on which an argument, theory, test, hypothesis or another research output is based. Data may be numerical, descriptive, visual or tactile. Data may be raw, or analysed, experimental or observational and may be held in any format or media. Data include records that are necessary for the reconstruction and evaluation of reported results of research and the events and processes leading to those results."

Research data management

ACU policy


The University's Research Data Management Policy is effective 13 September 2017.

The Policy forms part of the University's governance framework for research data management and outlines responsibilities with respect to storage, retention, accessibility for use and reuse, and/or disposal of the University Research Data.

The main points are:

1. Research data management must be consistent with:

2. To optimise research outcomes, research data must be:

  • documented and/or described
  • stored securely to protect against theft, misuse, damage or loss
  • held in appropriate facilities that allow access to be managed as required
  • made accessible for use and reuse, and/or disposed of, according to legal, statutory, ethical and funding bodies' requirements

3. Ownership of research data must be determined based on existing University policies, procedures and agreements

The Policy must be read in conjunction with other related University polices:


Research funding agencies and data management


In Australia, the Australian Research Council and the NHMRC both have requirements for data management and planning to be addressed as part of their application process and funding rules for research projects.

The Australian Research Council policy statement on research data management and funding guidelines each include a section on managing research data.

The NHMRC supports the sharing of outputs from NHRMC funded research including publications and data. The NHMRC is a signatory to the Wellcome Trust's joint statement on Sharing research data to improve public health.

A Research Data Management Plan is a document that describes how you will collect, organise, manage, store, secure, back up, preserve and share your data during and beyond the project life cycle. It deals with matters such as retention and disposal, archiving, accessing, sharing or publishing the data, and conditions or restrictions for data reuse.

A Research Data Management Plan allows you to document your strategy for managing your research data. It reflects your data management decisions and can also be used to record questions and items for action. It is a living document and can be updated as your project develops and your data management strategy is refined.

You can use the ACU RDM Planning Template Brief (DOC, 106KB) to develop your Research Data Management Plan.

Consider the questions below when developing the research data management plan for your research project.

Data capture and formats

Providing a description of the data your project will capture, create or use will help you and subsequent users understand why and how the data was created.The choice of format for your data will affect the lifespan of the data, and will determine how that data may be used, analysed, backed up, stored and potentially re-used in the future:

  • How will data be captured? eg interview, questionnaires, images, measurements, etc
  • What data formats will be used? eg file formats such as open source, pdf
  • Will there be special hardware or software requirements for this data?
  • Will the project use existing or third party data? Are there any requirements pertaining to the use of the data?
  • Is there adequate metadata within the dataset, eg descriptive field labels or column headings?
  • Will you create supporting documentation (data dictionary, data definitions, and codebooks) to ensure understanding of the data?
  • How will you identify different versions of the data?

You should save your research data using standard, durable formats that most software can easily interpret (or that can be migrated to a new format easily at a later date), to avoid being unable to use the data, either during the project or in the future.




Ethics, intellectual property and copyright

Ownership and rights issues for research data should be clarified at the very beginning of a research project, as these will affect any future storage, sharing and re-use of the data. Refer to the relevant ACU policies and, if your project is collaborative, discuss and document an agreement with all partners.

Find out more about copyright and data in the Australian Research Data Commons Research Data Rights Management Guide (PDF, 1.3MB):

  • What are the requirements of the funding body? What University guidelines and policies are relevant?
  • Intellectual property rights. eg is the dataset covered by copyright? Are there licencing or ownership issues?
  • Are there any issues related to human or animal subjects?
  • What steps will you take to protect privacy and confidentiality? eg de-identifying or anonymising data
  • Have you met obligations under the Code for the Responsible Conduct of Research?
  • Have you met obligations under the relevant state legislation?

Data storage and long-term preservation

Providing plans for the storage and management of your data is important for data security and preservation. Providing a plan for the long-term preservation of your data is important in order to meet regulatory requirements for the long-term storage and access to your data.

Data storage for the duration of your project:

  • What is the estimated size of data?
  • What file naming convention will you use?
  • Where will your data be stored during the project?
  • Who will be responsible for storage?
  • Are there any commercialisation, ethical or confidentiality restrictions relating to storing the data?
  • How often will your data be backed up?
  • Who will be responsible?
  • How will data security be guaranteed, eg data encryption, password, etc?
  • How will the data be shared during the project?

Data storage/archiving following project completion:

  • How long will your data be kept?
  • Will the final format of your data files be in a sustainable format, supporting long-term access?
  • Where will you store the data? eg archive, data repository?
  • Who will manage the long-term data?
  • What related information will be stored with the data?
  • Who will be responsible for metadata creation and documentation?
  • Which metadata standard/s will you use?

Data publication, sharing and re-use

Consider how the data will be used by yourself and others, both now and in the future, as that will effect the way you manage your data now. Consult the Australian National Data Service's Data sharing considerations for Human Research Ethics Committees (HRECs) guide and the Publishing and sharing sensitive data guide for more information:

  • Are there any reasons why the data cannot be shared?
  • Are there funding obligations to make data available?
  • How and when will the data be shared?
  • Will there be embargo periods? Will there be right-of-first-use for the data collector/creator/chief investigator?
  • Are there any restrictions, eg charging for access?

Sensitive data are data that can be used to identify an individual, species, object or location that introduces a risk of discrimination, harm or unwanted attention. The major categories of sensitive data are:

  • human medical/health and personal data, including information about secret or sacred practices
  • ecological data that may place vulnerable species at risk

See Australian National Data Service: Safely sharing sensitive data

What is anonymisation?

Anonymisation is the process of turning data into a form which does not identify individuals and where identification is not likely to take place. Anonymisation may be needed for ethical reasons,for legal reasons or for commercial reasons. Personal data should not be disclosed from research information, unless a participant has given consent to do so.

Sensitive data that has been anonymised can be openly published and shared. You will need to obtain informed consent from the participants in your study to allow for publication/sharing or their anonymised or de-identified data from the research.

The Australian National Data Service: Safely sharing sensitive data guide outlines best practice for the publication and sharing of sensitive research data in the Australian context. This guide provides straightforward, step-by-step advice about what you need to know and do before publishing and sharing your sensitive data, including:

  • confidentialising your human and sensitive ecological data
  • what's legal
  • what to include in a consent form requesting data publication and sharing
  • sharing sensitive data that you did not collect (ie third party data)
  • making data discoverable: metadata
  • conditional access to data: what is it; how do I do it?
  • licensing your data
  • depositing your data
  • a comprehensive guide on most things you need to know about publishing sensitive data



Data storage for the duration of the research project

You should ensure that all research data is stored securely and backed up or copied regularly. It is recommended that you store your research data in storage facilities provided by the University rather than rely on personal, portable storage devices.

At ACU you have a range of digital storage options (for data during the life of the research project):

  • ACU Storage - ACU IT offers secure and backed up storage for your research group or project. The amount of storage required can be discussed with eResearch first but it is likely to be in the order of 100GB maximum available. Please note that this is assessed on a case by case basis.
  • AARNet CloudStor - allows you to store and share files in the cloud. Provides up to 1TB of data free of charge. Sign in with your ACU username and password.
  • Intersect Space -A storage solution by Intersect for large-scale projects with complex requirements. Accessible via AAF (Australasian Access Federation) using your ACU credentials. This is a paid service and so may only be relevant to large multiyear projects or research institutes

Contact ACU eResearch Services for more information.

Data Retention

Consideration needs to be given to retaining data at the end of the project. Retention periods for research data may be influenced by a number of factors, such as:

  • funding body requirements (generally a minimum of 5 years)
  • legislative or regulatory requirements, for example, statutory retention periods, set by governments, for records
  • university policies on data management
  • agreements or contracts with research and industry partners
  • likely interest in the data from other researcher
  • the needs of the research project team

Retention periods

The minimum period for keeping research data is usually 5 years from the completion of the project or the time that the results of the research are published (whichever is later). Different retention periods apply (up to 25 years) to research involving clinical trials, psychological testing or intervention with adults, medical research involving children.

Archiving your research data (following project completion)

ACU Research Bank is the institutional research repository of Australian Catholic University. You may choose to deposit a copy of your data set in Research Bank or alternatively deposit the metadata about your dataset. Datasets in Research Bank may be available open access or via mediated access. The description of your data is fed to Research Data Australia, a national collection of metadata describing datasets.

Archiving your research data in Research Bank will mean that your data will be:

  • safely stored
  • backed up regularly
  • discoverable
  • preserved for the future
  • made available to others for re-use, if possible

Contact your Librarian if you would like to deposit your data in ACU Research Bank.

Benefits of sharing data

The benefits of sharing data include:

  • Increases visibility of research, ensuring that your data can be accessed and cited in the long term.
  • Increases efficiency of research due to reusability and exposure.
  • Promotes scientific integrity and replication.
  • Enhances collaboration.
  • Provides opportunity for others to build on your data, leading to new research outcomes.

Incorporating sharing data into your Data Management Plan

If you are working with research partners, sharing data and datasets will happen. When you are developing your Data Management Plan you need to consider how you intend to share your files. The ACU isilon drive (or shared drive) is not accessible to external researchers and CloudStor is the preferred option.

If you are working with survey data and clinical trials in REDCap and need to share this data with external collaborators, you can request an account for your research partner by contacting EResearch.

Publishing data is actively making your research data accessible to others and can include:

  • Submitting the data that underpins a journal article (together with the manuscript) to a publisher. An increasing number of publishers/individual journals require submission of datasets. ACU authors should check a journals' Data Policy before submitting their manuscript.
  • Depositing research datasets in an online repository.
  • Submitting the data for publication in a data journal. Read the ANDS Data and journals guide for more information.

Some funding schemes from the Australian Research Council require researchers to make data publicly available within a specified time frame, generally through deposit in an institutional or discipline-specific public repository.

Assign a Digital Object Identifier to your dataset

Assigning a Digital Object identifier (DOI) to your dataset will ensure that the data will always have a persistent link to the original source, ensuring that the original source can be cited and the impact of your data measured.

DOIs should be applied to your data when it is:

  • in a finalised form (with no further changes required)
  • being made available via open or mediated access
  • going to be cited in a publication or as an output in its own right

Frequently Asked Questions about the DOI System.

If you would like to mint a DOI for your dataset contact Library Research Services.

Citing datasets

Data citation is the practice of providing reference to datasets. Like traditional bibliographic references, data citations acknowledge the original creator and help other researchers find the dataset.

If you publish an article and have published the data separately, remember to cite your dataset in your article.

Further information on data citation:


Contact the Library

Library Research Services 
Eresearch Support Services 

Last reviewed: 28 February 2020