5 Things Every Data Management Plan Should Include
Basic questions to ask yourself before you start writing a data management plan
- Data Types
- What types of data will your project produce (samples, specimens, records, etc.)?
- What file formats will you use?
- Are those formats sustainable for the long-term?
- How will you label and describe your data?
- How will you name and organize your files?
- How will you ensure consistency across your team?
- Access and Sharing
- Who will have access to your data during and after the research process?
- What forms of your data can you publish?
- What security, confidentiality and intellectual property requirements apply to your data?
- If you publish your data, which license will you use?
- Who can re-use your data and for what purpose?
- How should your data be cited?
- How will you backup and preserve your data?
- What if software changes? Will you need to update your files to a new format?
DMP Self-Assessment Tool
More in-depth questions to guide the planning process
This tool includes 30 questions to ask yourself and your research partners when establishing data management procedures for a lab, center or research project. The questions are broken into sections that correspond to the five areas the NSF and most other funders require in data management plans: data types, metadata, sharing, re-use, and archiving.
Researchers should cite this work as follows:
Jake Carlson (2011), "DMP Self-Assessment Tool," https://purr.purdue.edu/dmp/self-assessment
Developed by Purdue librarians, these library guides provide an introduction to key terms and concepts, information about Purdue resources, and links to online materials, resources, and standards. You can also find contact information for research data support providers who can answer your questions and consult with you about data management.
A guide that provides general information about data management including Data Management and Data Sharing Plans to meet funder requirements.
A guide addressing issues and policies for research data involving human subjects, personally identifiable information, and other sensitive data sets.