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Research Data Management

This guide provides best practices and resources for managing your research data for any discipline.

Research Data Lifecycle

  • Proposal Planning & Writing
  • Conduct a review of existing data sets
  • Determine if project will produce a new dataset (or combine existing)
  • Investigate archiving challenges, consent and confidentiality
  • Identify potential users of your data
  • Determine costs related to archiving
  • Contact Archives for advice (Look for archives)
  • Project Start Up
  • Create a data management plan
  • Make decisions about documentation form and content
  • Conduct pretest & tests of materials and methods
  • Data Collection
  • Follow best practice
  • Organize files, backups & storage, QA for data collection
  • Think about access control and security
  • Data Analysis
  • Manage file versions
  • Document analysis and file manipulations
  • Data Sharing
  • Determine file formats
  • Contact Archive for advice
  • Document (more) and clean up data
  • End of Project
  • Write Paper
  • Submit Report Findings
  • Deposit Data in Data Archive (Repository)














Remember: Managing Data in a research project is a process that runs throughout the project. Good research data management is the foundation for good research, especially if you intend to share your data. Good management is essential to ensure that data can be preserved and remain accessible in the long-term, so it can be re-used and understood by other researchers. When managed and preserved properly research data can be successfully used for future research purposes. Begin thinking about your data before you start collecting.

Parts on this webpage taken from: Van den Eynden, V., Corti, L., Woollard, M. & Bishop, L. (2009). Managing and Sharing Data: A Best Practice Guide for Researchers. Retrieved 02/06/2010, from