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Research Data Management

RDM refers to the active curation of data throughout the research life-cycle.

Research Data Management (RDM) is "how you look after your data throughout your project. It covers the planning, collecting, organising, managing, storage, security, backing up, preserving, and sharing your data and ensures that research data are managed according to legal, statutory, ethical and funding body requirements" (Whyte, A. & Tedds, J., 2011).

Research data management happens throughout the research lifecycle (not only at the end of a research project) to preserve the usability and reliability of the research data (taking confidentiality and data protection issues into account).

Source: University of California, Santa Cruz: The Research Data Management Lifecycle

Research data is created, collected and observed during a research project. Research data can vary widely: it can be qualitative, quantitative, numerical, descriptive, visual, physical, digital or print. Research data can be raw or analysed, simulated, experimental or observational, confidential or publicly accessible.

Why should you manage your data?

Managing research data have many benefits for you and your fellow researchers:

  • Research data that are correctly formatted, described and attributed increase your research impact.
  • Managing your data from the start of your project can save you time.
  • RDM maintains data integrity and research results may be replicated
  • You will be able to easily find and access your data over the lifespan of your project.
  • RDM enhances data security and helps avoid the risk of data loss.
  • RDM helps you meet funder and other regulatory requirements.
  • Duplication of effort is minimised.
  • Interdisciplinary research and new discoveries are enhanced.
  • RDM helps in the long-term preservation of your research data.
  • It helps make your data FAIR.

Data management plans

A generic data management plan (DMP) usually contains the following information:

  • What data will you collect or create?
  • How will the data be collected or created?
  • What documentation and metadata will accompany the data?
  • How will you manage any ethical issues?
  • How will you manage copyright and intellectual property rights?
  • How will the data be stored and backed up during the research?
  • How will you manage access and security?
  • Which data are of long-term value and should be retained, shared and/or preserved?
  • What is the long-term preservation plan for the dataset?
  • How will you share the data?
  • Are any restrictions on data sharing required?
  • Who will be responsible for data management?
  • What resources will you require to deliver your plan?

Visit our DMP guidelines for more information.

Source: Digital Curation Centre

Data storage

Storage and backup of research data is a crucial part of data management to avoid loss and corruption of data. Keep multiple copies of your data in safe and secure storage you can access readily. Consider the following when selecting your data storage:

  • What data formats are you going to use?
  • What is the anticipated volume of data you are going to collect or generate?
  • When and where will you need to access your data?
  • Will anyone else need to access your data?
  • Will the storage meet privacy and security requirements?
  • Will the storage provide for long-term preservation?

Source: Charles Darwin University

Storage options:

  • PC/laptop
  • Portable media, e.g. external hard drives, DVDs, USB drives*
  • Cloud services (always read and understand the End User License Agreement)
  • Research data repositories

*These are convenient, but risky and vulnerable to loss or damage. Use them only for temporary copies and data you can afford to lose.

Here are some tips by the UK Data Service on selecting safe and secure storage. And read more about solutions at the UFS.

Data sharing

Sharing your research data will increase your research impact and citation rates, promote new research and collaborations, reduce duplication of research, and support validation and replication of research. Not all data can be shared due to legal, ethical and practical reasons, and researchers should consider all legal and ethical issues when making their data available to others.

If your funder or publisher does not indicate a discipline-specific data repository for sharing your data, here are a few general-purpose data repositories you could use:

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