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Research data management: Introduction

 

March 20, 2020 update: While the physical SFU Libraries are temporarily closed due to COVID-19 measures, we are happy to continue to support you with any research data management questions remotely. Please feel free to contact us by email at data-services@sfu.ca during this time, and we can set up a meeting via video conferencing or telephone.

 

What is research data?

Research data is the material you collect or create over the course of academic work, whose analysis supports published scholarship. This is the data that would be required for your results or findings to be properly reconstructed and evaluated.

Research data can take a wide range of forms, and can include both non-digital and digital material. Common types of research data include images, tabular data, audio or video interviews, music, experimental data, instrument data, models, and compiled data. 

Not all written records and computer files in a research lab are considered research data. For example, procedural information like lab schedules or timetables, or contact information, would not be considered research data. 

What is research data management, and why does it matter?

Research data management describes the activities that support the responsible handling and organization of data created as part of a research project. For example, data management can help you handle situations such as these: 

  • If you wanted to share your data with another researcher, would they be able to make sense of your work? 
  • If you needed to check your data or re-use it again five years from now, how easy would it be to find and use those records?

One good way to address these and other questions is to create a data management plan. Key components of such a plan include determining methodologies for responsibly organizing, securing, and sharing research data.

Responsibly managing your research data is important because it helps current and future users of the data interpret, interact with, and evaluate your work. In addition, a growing number of journal publishers, research grant funders, and research ethics boards are introducing requirements for the appropriate sharing of research data.

Key aspects of research data management

Access data

Information and resources relating to identifying, discovering, and accessing data produced and shared by other researchers or data providers.

Organize data

Best practices for research data file organization, naming, and documentation help ensure a high level of data accessibility.

Secure data

Data management strategies designed to protect the integrity of research data, with an emphasis on encryption, data backups, and accessible file format selection.

Share data

Key principles supporting the responsible sharing of research data, including research data repository recommendations, data sharing ethical considerations, and the requirements of research funders.