Data Management

Data Management

This module will discuss the importance of appropriate data management regarding organization, storage, sharing, and protection.

Learning Objectives

  • List the benefits of effective data management.
  • Describe strategies to organize, store, protect and share data.


Data management is a vital part of responsible research. Effective data management helps researchers create, organize, document, store, and share their data. It is also important for the protection and backup of data, as well as confidentiality when necessary. Specific examples of the benefits of an effective data management plan include:

  • Increases research efficiency
  • Ensures that records are accurate, complete, and reliable
  • Ensures the integrity of the data and the research project overall
  • Saves time and resources
  • Improves data security and protects against loss
  • May be necessary to meet the requirements of the funding organization
  • Helps researchers comply with industry or discipline standards


Once a researcher has developed a research design and has a full understanding of the type of data that will be collected, there are several factors that must be considered to develop a data management plan. Some of these include the following:

  • What type of data will be collected?
  • How much data will be collected?
  • Who is the audience and how will they use the data? Who has access to the data?
  • How should the data be stored?  For how long? How will it be backed up?
  • What format will be the data be and is it long-lived?
  • Will the full data be shared? If so, is there an industry or discipline standard?
  • Are there special privacy, security, or confidentiality considerations?
  • Does the funding agency have specific requirements?
  • When and where will the data be published?


It is also important that the data plan allows for some flexibility, adjustments, and updates as the project progresses. Depending on the research question and the type of project, information learned along the way may create a feedback loop whereby, additional, or new information is collected and incorporated. Researchers must be able to adjust to the needs of the project.  

Researchers will also need to decide whether to share their data collections. Some reasons to share the data may include advancing scientific knowledge, funding requirements, to increase the impact of the research, and for teaching purposes. However, there are times when it is not appropriate or necessary to share the data. For example, the data may contain sensitive, personal, or confidential information. Parts of the data may be owned by someone else, or the research may not have the right to share. Or perhaps, the data has financial value. Regardless of the situation, the results of research project should be shared with the rest of the community or within that discipline at the very least.

Learn more about managing research data through the following YouTube video - including a discussion regarding the importance of data management. 


Suggested Readings: 

  •  Devlin A. (2006)  Research Methods.  Thompson Wadsworth.
  • Goodhue, D. L., Quillard, J. A., & Rockart, J. F. (1988). Managing the data resource: a contingency perspective. MIS quarterly, 373-392.
  • O'Leary, Z. (2004). The essential guide to doing research. Sage.
  • Ryan, G. W., & Bernard, H. R. (2000). Data management and analysis methods.

Resource Links

Why Manage Research Data? - These two resources contain links for all aspects of managing research data - documentation, file type, storage, backup, protection, confidentiality and many others.

 What is "Research" Data? - This link provides a definition of research data as well as a list of different types of data.

 Managing Your Research Data - This resource provides links for more information regarding a variety of issues related to data management. It also contains a helpful collection of video resources for learning more.

 Seven rules of successful research data management in Universities - The website discusses seven guiding principles for working with data management and emphasizing the benefits of planning ahead.

 Research Data Management - A list of basic data management steps is included in this website, as well as links to other resources.


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