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Research Data Management Guide: Share your data

This guide aims to provide information and resources to support best practice in managing research data at Charles Darwin University (CDU).

Sharing through CDU eSpace

CDU eSpace serves as a stable repository for the long term preservation, management and appropriate sharing of research outputs, including medium to small sized datasets (no more than 5GB). Researchers can upload descriptions of their data and related data files through the Self Submission Portal. Datasets can be assigned a persistent identifier (DOI) to facilitate easy citation. 

The eSpace repository is especially configured to maximize exposure of metadata to the web, including the National Library of Australia. Research metadata records, along with relevant information about researchers, is fed to Research Data Australia

Uploaded data files can be assigned an embargo period or made available only by mediated access in cases where immediate open access is not appropriate. These metadata records and attached files are stored in the eSpace's DATASETS AND PRIMARY RESEARCH MATERIALS collection. 

Considerations for sharing data

In making their data available to others, researchers need to consider several ethical and legal issues.


Determining access to the data is dependent on the type of data collected and stored:
 Personal data - data which relate to a living individual who can be identified from the data.
• Confidential data - data given in confidence or data agreed to be kept confidential that are not in the public domain such as information on business, income, health, medical details and political opinion.
• Sensitive personal data - data on a person‘s race, ethnic origin, political opinion, religious or similar beliefs, trade union membership, physical or mental health or condition, sexual life, commission or alleged commission of an offence (alleged to have been) committed, disposal of such proceeding or the sentence of any court in such proceedings.


Clarifying data ownership and intellectual property rights is an important part of data management as this will determine how the data can be managed and used, both during the project and in the future.  The ownership and management of intellectual property at Charles Darwin University is governed by:
• Intellectual Property Policy 


All confidentiality agreements between the researcher and participants must be respected. It is advisable for researchers to include information about data storage and data access to participants during the consent process.

The Privacy Act 1988 (Cth) requires Commonwealth agencies to comply with the Information Privacy Principles (IPPs) regarding personal information.


Researchers creating data typically hold copyright. Most research outputs - including spreadsheets, publications, reports and computer programs - fall under literary work and therefore are protected by copyright. The creator is automatically the first copyright owner unless there is a written transfer of copyright signed by the copyright owner.  For information and advice regarding copyright, visit CDU's copyright webpage.


Ethical treatment of data applies not just to the collection or generation of data, but also to how the data will be stored, and if and how it will be made available.  Professional bodies, institution or funding organisation, including the Australian Code for the Responsible Conduct of Research may require measures to maintain confidentiality of research data and primary materials by protecting the data from unauthorised access and use.

For information on ethics processes and committees at Charles Darwin University, visit the Ethics website.


Third party research data is any data that has been obtained from research created by external agents such as the Census data created by the Australian Bureau of Statistics. This data may be sourced directly from the creator in raw formats or from other resources such as journal articles, books, blogs or websites. Third party data may be protected by intellectual property rights such as copyright, patent and trademark.

If researchers purchase access licences to reuse third party data, they are limited in sharing their data due to possible restrictions.


Options for sharing - levels of access

There are a number of different options for sharing data with other researchers. CDU research datasets have been entered into the Research Data Australia discovery service (see the 'showcasing your data' tab) with the following levels of access available.

Restricted access
The data can be described in Research Data Australia but access is restricted to certain groups of people such as fellow researchers or students. The owner can determine the level of access:

  • Confidential information is not shared
  • Non-confidential information has restricted or open acces

Consider providing a mix of access levels where certain data may be restricted including:

  • Medical research records that disclose highly sensitive personal information
  • Information of cultural and ethnic sensitivity
  • Material subject to commercial, political or legal requirements

Mediated access
Access to the data is granted by contacting the person nominated in the Research Data Australia record. This option can also be used in cases where reuse is allowed but requires approval from a project steering group or human ethics committee.

Open access data
The data can be stored securely in a website or repository/data store and provides open access via a link. This option enables access to your data, provided there are no legal, ethical or commercial barriers.

Licensing and reuse

To share and reuse data, permissions and conditions of use need to be attached to the data. Applying an appropriate licence will ensure the copyright owner retains ownership of their work and anyone reusing the data knows exactly what they are permitted to do.

The Australian National Data Service (ANDS) supports the use of the Australian Government's Open Access and Licensing Framework (AusGOAL) suite of licences, which include the:

  • Australian Creative Commons licences
  • Restrictive Licence Template
  • BSD 3-Clause Software Licence

The Licence Chooser available from the AusGOAL website will help determine the most suitable licence to attach to the data.

Creative Commons (CC) is an international non-profit organisation that provides free licences and tools that copyright owners can use to allow others to share, reuse and remix their material, legally.

You can use a free tool developed by the CC to assess a CC license that might be applicable to your data.

De-identification of data / data anonymisation

Care should be taken before sharing certain kinds of data. Personal identifiers, both direct and indirect, should be removed from datasets.  Where the dataset cannot be shared, consider creating a public use version which may involve:

  • Removing direct identifiers, e.g. name or address
  • Agrregating or reducing the precision of information or a variable, e.g. replacing date of birth with age groups
  • Generalising the meaning of detailed text, e.g. replacing a doctor's detailed area of medical expertise with an area of medical specialty
  • Using pseudonums
  • Restricting the upper and lower ranges of a variable to hide outliers, e.g. top-coding salaries

 A person's identity can be disclosed from:

  • Direct identifiers, e.g. name, address, postcode information of telephone number
  • Indirect identifiers that, when linked with other publically available information sources, could identify someone, e.g. information on workplace, occupation or exceptional values of characteristics like salary or age

Special attention may be needed for:

  • Relational data, where relations between variables in related datasets can disclose identities
  • Geo-referenced data, where identifying spatial references such as point co-ordinates also have data related to those co-ordinates

 How to manage anonymisation:

  • Plan for anonymisation early in the research as part of your data management plan
  • Retain original unedited versions of data for use within research team and for preservation
  • Create an anonymisation log of all replacements, aggregations or removals made
  • Store the log separately from the anonymised data files
  • Identify replacements in text in a meaningful way, e.g. in transcribed interviews indicate replaced text with [brackets] or use XML mark up tags <anon>.....</anon>

Contact us

Related resources

 A Good Practice Guide to Sharing Your Data with Others  - joint publication of the Australian Bureau of Statistics and National Statistical Service.

• ANDS De-identifying Your Data - information and links to resources about de-identifying data

• ANDS Guide to Ethics, Consent and Data Sharing - guide intended for people engaged in research involving human subjects or members of committees overseeing such research

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