Step 3 - Archive

Consent is required from human participants before data can be collected or published. Obtaining informed consent to facilitate data sharing and publication involves:

• Developing an information sheet about maintaining confidentiality, data sharing and publication so participants can make an informed decision before consenting to participate. Your information sheet should be approved by JCU's Human Research Ethics Committee (HREC) as part of the ethical clearance process (refer below).
• Stating the possibility of future data publication and sharing,  de-identification processes and conditions for access (refer below)
• Seeking prior approval from HREC for consent forms and information sheets.

The Australian Research Data Commons (ARDC) provides some example sentences in their guide (pp. 14) - the examples listed below are appropriate in different contexts (e.g. open and conditional access respectively):

The information in this study will only be used in ways that will not reveal who you are. You will not be identified in any publication from this study or in any data files shared with other researchers. Your participation in this study is confidential.

I agree that research data gathered for the study may be published provided my name and other identifying information is not used. Other genuine researchers [may] have access to this data only if they agree to preserve the confidentiality of the information as requested in this form.

If explicit consent for sharing is not obtained at the time of the study, it may be possible to seek a waiver from reviewers or to go back to participants for additional consent.

Secondary use of data or information:

The National Statement on Ethical Conduct in Human Research (p. 36) raises the ethical issue of obtaining consent for secondary use of data or information. It is, for example, usually impractical to obtain consent for secondary use of data routinely collected during delivery of a service and respect for participants needs to be demonstrated in other ways.

Sharing existing data without explicit consent is a possibility if all of the following conditions for a waiver of consent, as outlined in Section 2.3.10 of the National Statement of Ethical Conduct of Human Research, are met:

• involvement in the research carries no more than low risk to participants,
• the benefits from the research justify any risks of harm associated with not seeking consent,
• it is impracticable to obtain consent (for example, due to the quantity, age or accessibility of records),
• there is no known or likely reason for thinking that participants would not have consented if they had been asked,
• there is sufficient protection of their privacy,
• there is an adequate plan to protect the confidentiality of data,
• in case the results have significance for the participants’ welfare there is, where practicable, a plan for making information arising from the research available to them (for example, via a disease-specific website or regional news media),
• the possibility of commercial exploitation of derivatives of the data or tissue will not deprive the participants of any financial  benefits to which they would be entitled, and
• the waiver is not prohibited by State, federal, or international law.

JCU researchers and HDR candidates should always consult their College / Centre Human Ethics Advisor, and the Research and Innovation Services Ethics and Research Integrity team for specific advice.

A contract is a legally binding agreement that defines and governs the rights and duties between or among its parties. A number of specific issues need to be addressed prior to the commencement of a research project relating to the use, management, sharing and ownership of research data and information.

Some examples of agreements include:

With research funders:

• The research funding agreement may stipulate that the funding organization has a claim to, or ownership of, the intellectual property (copyrights and other rights) created through the funded research;
• Alternatively, the agreement may grant licence rights to the funding organisation with respect to the use of the data. Even if the funding organization does not acquire full ownership, they may be granted specific rights to use, share, or commercialize the data as outlined in the agreement.

With collaborators:

• Research Collaboration Agreement (RCA): This agreement should specify whether data ownership is joint, shared, or retained by the originating party and clearly articulate the rights granted to each collaborator for using and disseminating the data. It should also address Intellectual Property (IP) rights including the ownership and potential commercialization of IP resulting from collaborative effort;
• Indigenous Culture and IP (ICIP) Agreements: Agreements related to Indigenous culture and intellectual property often prioritize community rights and control over the data. Ownership may remain with the Indigenous community, and researchers might be granted specific, limited rights for their research purposes.
  ICIP may also be relevant in the context of data providers (below)

With data providers:

Several types of agreements with data providers may be relevant, including:

• Confidentiality Agreement: Ownership usually remains with the data provider, and the receiving party (your research team) is obligated to keep the information confidential and not disclose it to third parties;
• Data Transfer Agreement: Ownership and rights are often specified in these agreements. They may grant the recipient certain rights to use the data for the intended purpose but restrict further dissemination or commercialization without explicit permission;
• Application under the Public Health Act 2005 (PHA): Ensure that you understand the terms related to data ownership, as some PHAs might allow specific uses for public health research while preserving certain rights for the data provider.

Make sure that any agreement you enter into makes the conditions for storing and sharing any derived data clear.

Always consult Research and Innovation Services for further information at contractsconnect@jcu.edu.au for specific advice.

In most jurisdictions, including Australia, copyright protection applies to the expression of ideas rather than the ideas or facts themselves. Datasets will be protected by copyright if they meet certain threshold criteria of human authorship, originality, or creativity. Compiling and presenting raw data (e.g. adding labels, units, performing calculations etc.) is often sufficient to attract copyright protection.

Copyright in research data produced at JCU is governed by JCU's Intellectual Property Policy and Procedure.

Here's an example: If a data logging machine placed in a creek generates 'raw data' about (for example) water quality, that data may not attract copyright protection, despite the fact that researchers may have used considerable skill, effort and expertise in siting the machine. Since the 'raw' data itself would have no human authorship and originality, it would not satisfy the legal basis of copyright. However, if a researcher were to examine the data from the data logging machine, notes certain errors and makes corrections to the data, or reforms the selection and arrangement of the dataset; that (sometimes relatively minor) act of human authorship, originality, and application of skill and judgment may be sufficient for the resulting dataset to attract copyright protection.

Even if your data does not meet the threshold for copyright there is no harm in applying a Creative Commons licence when publishing the data. It lets others know how you would like to be attributed and applies a limitation of liability and warranty clause to the data.

Refer also to Moral Rights and the Library website for further information about Copyright.

This section lists some of the repository options available for publishing research data or finding existing data for reuse at JCU.

Some researchers may also choose to publish a data paper - these are published research outputs in a specialist data journal (or section of a more generalist journal) with the primary purpose of exploring the research potential of a particular data set and deriving new research findings. While a published data paper would usually constitute a significant investment of time and effort above the deposit and publication of data through a repository, it may be an avenue worth exploring depending on the field of research.

Information about specific important repositories ...

Preserving the data and information after your research project has been finalised is critical to:

• Prevent data loss;
• Enable long-term access, discovery and reuse; and
• Ensure researchers and institutions can defend their research outcomes if they are challenged.

Preservation activities need to be planned and should take into account file formats and data quality, data ownership (refer to Copyright, Intellectual Property and Moral Rights), retention periods, preferred data repositories and ways to share data safely.

Retention rules are defined by the research funding body or the university. Key documents for JCU researchers include the guide 'Management of Data and Information in Research' which supports the 2018 Code and the University Sector Retention and Disposal Schedule for Queensland universities.

In general, the minimum period for retention of data is five years from the end of the year of publication of the last refereed publication or other form of public release to an audience outside of the University that is based on the data. However, in any particular case the period for which data should be retained should be determined by the specific type of research e.g. for areas such as gene therapy, research data must be retained permanently.

For more information refer to the retention rules for specific data types.

De-identifying data is the process used to prevent someone’s personal identity from being revealed. Data that has been de-identified no longer triggers the Privacy Act.

For example, data from the PALS (Pregnancy and Lifestyle Study) has been de-identified and is available for download. The risk of re-identification via triangulation has also been considered and managed.

Although the study contains highly sensitive data, several techniques have been used to de-identify the dataset e.g. identifiers and dates of birth have been removed, ages have been aggregated into bands - and postcodes have been excluded. It would be possible to re-identify (triangulate) participants by combining (for example) a rural postcode with an occupation.

Think about de-identifying your data early as it can be time consuming and difficult later. The Australian Research Data Commons (ARDC) has some tips on de-identification, listed below and in their Identifiable Data guide. You should also seek discipline-specific advice as required.

• plan de-identification early in the research as part of your data management planning
• make sure the consent process includes the accepted level of anonymity required and clearly states what may and may not be recorded, transcribed, or shared
• retain original unedited versions of data for use within the research team and for preservation
• create a de-identification log of all replacements, aggregations or removals made
• store the log separately from the de-identified data files
• identify replacements in text in a meaningful way, e.g. in transcribed interviews indicate replaced text with [brackets] or use XML markup tags
• for qualitative data (such as transcribed interviews or survey textual answers), use pseudonyms or generic descriptors rather than blanking out information
• digitally manipulate audio and image files to remove identifying information