Research Data Management: Research Data Management

For all types of data you are collecting, you will need to think about how you will preserve the data and control who has access to it during and after your research. This may affect the data collection (e.g. you may need to get consent from research participants).

Before you start collecting data ensure the following:

1. Know the relevant procedures and policies
2. Create a data management plan
3. Clear all ethics, privacy, and ownership issues
4. Plan and implement the storage and security of your data
5. Retain your data and provide access to it

A Data Management Plan (DMP) may include:

• What data will be created and in what format
• Where will it be stored
• How will it be described
• Who will have access to the data
• How will the data be preserved
• How will sensitive data be managed
• Who owns the data

Many Australian universities have data management policies, procedures, and tools available for researchers who need to create a DMP at the start of a research project.

See the Digital Curation Centre's DMPOnline tool for more information.

Creating a research data management plan at the start of the research project will help save time in the:

• collection
• description
• analysis
• re-use

of data.

Effective data management means you can:

• verify your research results
• replicate the research
• provide future access to data
• ensure participant privacy is respected
• ensure that data is not lost

This is important as grant and funding bodies will require research data to be managed throughout its lifecyle (see below). You may need to provide the data or information about the data in order to publish your research, for example.

Research Data Lifecycle. Adapted from UK Data Service Model 2017. Queensland University of Technology, Advanced Information Research Skills . CC BY-NC-SA 4.0

The FAIR and CARE principles are frameworks that guide data management. They ensure that your research data maximises its impact, and is respectful to the people and purpose behind the data.

FAIR

The FAIR principle requires data to be:

• Findable
• Accessible
• Interoperable
• Resuable

It is a framework for sharing data in a way that maximises its use and reuse. See the Making Data FAIR page at the ARDC for more information on the FAIR principles and how to apply them.

CARE

If your research involves the handling, management, and/or analysis of Indigenous data, you should consider applying the CARE Principles for Indigenous Data Governance.

CARE:

• Collective benefit
• Authority to control
• Responsibility
• Ethics

For more information about the CARE principles and how to apply them, see the CARE Principles page at the ARDC.

The FAIR and CARE principles are complementary: FAIR ensures that the data is easier to share and reuse, CARE ensures that the data is used ethically.

Security and storage of your data is vital. See below for some basic advice. Be aware that funding institutions may have specific requirements for the storage of your research data

For digital data:

• investigate if your institution or organisation has regulations on the storage of data
• investigate your storage options and their security
• duplicate your data and store it in multiple locations (if possible)
• be careful with easy-to-misplace items like USBs and hard-drives
• set a schedule to back-up your data
• enable its re-use
• make preparations to destroy any confidential or disused data

For non-digital data:

• ensure the storage space is climate-controlled and free of pests
• ensure it has an adequate disaster plan
• devise, communicate, and enact a plan for the authorization and access of the data

It is essential to come up with a plan in advance and implement it for how you will document and describe your project and your data. Information about data (e.g. dates, descriptions, titles) is called metadata. Metadata is essential for enabling your data to be found and used. You may like to begin by thinking about how you would describe the data you have obtained and how it was obtained.

Common information included in metadata:

• creators
• purpose
• content
• filenames
• dates
• places of generation
• terms/requirements of re-use
• method of capture

Try and be consistent with information like filenames as this will allow for easy retrieval of your data in the future.

Some data repositories have the ability to generate and assign unique identifiers to data (such as DOIs), which can help with citing, finding, and reusing of data.