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Collect, manage, and analyze data

Need assistance with data collection or management?

Ideally, your plans for data collection, management, and analysis should be developed during the planning phase of your project. Once your project is underway, it is more difficult to create or change your data management plan while ensuring your scientific aims are met and the findings are reusable and reproducible.

The "Related Resources" on this page will guide you to specific policies, tools, and training options that may be helpful in guiding the data needs of your project once it is already underway. This page also provides guidance for determining data collection methods, management and storage solutions, and developing analysis plans if you need to develop or revisit any of those aspects of your project.


Data collection

Your data collection strategy should be based upon what data outputs are essential for the aims of your project, and what appropriate and approved methods are needed to obtain this data. Access the Develop the data management plan page for best practices and considerations for research methods to help think through your data collection needs.

  • If you are looking for specific policies or guidance around data collection methods, explore the "Related Resources" on this page.
  • If you need further assistance with data collection methods or operational needs of your project, access the Plan the project or methodology page to explore which consultative services best fit your project needs.


Data Management

The classification and size of data you are collecting or obtaining will determine the options available for appropriate data management and storage solutions. Refer to the Duke services and data classification guide to determine appropriate storage options or cloud solutions based on the classification of the project data. 

The Develop the data management plan page and the Determine compute and data storage solutions page provide best practices and considerations for determining the appropriate data storage, organization, and documentation for your project.


Data Analysis

Utilizing appropriate data analysis methods, with data that have been cleaned and vetted for quality assurance, are critical to ensuring your results are accurately interpreted.