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Good research data management makes it easier to locate, access, share, and use or reuse data. This guide breaks data management practices down into the key phases of working with data throughout your research project and also takes you through the things you might need to consider after your project is completed.
Good data management:
- Makes your data easier to find, understand & analyse
- Allows you and others to use your data in the future
- Demonstrates research integrity and validates findings
- Reduces the risk of data loss
- Ensures compliance with funder, publisher, and/or institutional policies (see Otago's Responsible Practice in Research - Code of Conduct)
- And, as a bonus, your datasets can be cited!
PLAN & CREATE
Planning is essential. Write a data management plan (DMP) that covers the life of your research data from creation to preservation.
BACK UP & STORE
How will you ensure the security and integrity of valuable research data? Data need to be backed up and stored to provide safe current and future access in reliable formats.
DOCUMENT & DESCRIBE
Document and describe your research at the project and data-levels to ensure your work is findable and reusable.
SELECT & PRESERVE
How can you prepare your data to be preserved, and where can you deposit it for safe-keeping?
ACCESS & SHARE
Consider who will have access to your project data, how, and for how long? What limitations might apply when it comes to sharing your data?
MANTRA is a free, online non-assessed course with guidelines to help you understand and reflect on how to manage the digital data you collect throughout your research.
Support for data management @ Otago