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Research data management is the organization, documentation, storage, and preservation of the data resulting from the research process, where data can be broadly defined as the outcome of experiments or observations that validate research findings, and can take a variety of forms including numerical output (quantitative data), qualitative data, documentation, code, images, audio, and video.

Planning touches all aspects of your research lifecycle.

As shown in Figure 1: Basic Research Data Life Cycle with Management Actions, data management begins with the planning and design of your project, continues as you conduct your project through documentation, storage and security of your data, and finishes with how your data will be shared and preserved post-project.

Figure 1: Basic Research Data Life Cycle with Management Actions

Research Data in Context

During research, the context of data creation is essential to understanding the content. We can loosely define research data as recorded bits of information that have been collected, observed, generated or created to answer research questions or validate findings. It is often digital,  but takes many forms. As shown in Figure 2: Venn Diagram of Data in Context, specific practices in managing research data rely heavily on subject matter, data characteristics, and disciplinary community practices. We can help you with customizing your data creation workflows and methods. 

Figure 2: Venn Diagram of Data in Context

Data Characteristics

Consider these aspects of content you generate.

Is your data...

• Active (dynamic, constantly changing) or Inactive (static, one event, complete)
• Open (public, for further use) or Proprietary (for monetary gain)
• Non-identifiable (no human subjects) or Sensitive (containing personal information)
• Preservable (to save long term)  or to discard in 3 years (not for keeping)
• Shareable (ready for reuse) or Private (not able to be shared, not for reuse)

These characteristics are contingent upon subject, format, and content and will guide your management choices.

Source: Four rising areas of concern in Research Data Management  by Andrea Chiarelli

University of Houston Data Management and Sharing Policy

Policy Highlights

• All university research projects require a formalized, written data management plan.  
• Data must be archived in a controlled, secure environment in a way that safeguards the data.
• The archive must be accessible by scholars analyzing the data, and available to collaborators.
• Investigators are expected to share data with researchers within a reasonable time frame.

Read the entire Data Management and Sharing Policy 

University of Houston Data Retention Policy

Research data generated while individuals are pursuing research studies as faculty, staff, or students of the University of Houston, and data generated by visiting scientists utilizing the facilities of the University of Houston, are to be retained by the institution for a period of three (3) years after submission of the final report on the research project for which the data were collected, unless a longer retention period is specified by the sponsor. 

Read the entire Data Retention Policy