Data Management and Publishing

Manage Your Data

Managing your data before you begin your research and throughout its life cycle is essential to ensure its current usability and long-run preservation and access. Data management activities include:

A Data Planning Checklist | Create a Data Management Plan | Guides to Data Management

A Data Planning Checklist:

1. What type of data will be produced? Will it be reproducible? What would happen if it got lost or became unusable later?
2. How much data will it be, and at what growth rate? How often will it change?
3. Who will use it now, and later?
4. Who controls it (PI, student, lab, MIT, funder)?
5. How long should it be retained? e.g. 3-5 years, 10-20 years, permanently
6. Are there tools or software needed to create/process/visualize the data?
7. Any special privacy or security requirements? e.g. personal data, high-security data
8. Any sharing requirements? e.g. funder data sharing policy
9. Any other funder requirements? e.g. data management plan in proposal
10. Is there good project and data documentation?
11. What directory and file naming convention will be used?
12. What project and data identifiers will be assigned?
13. What file formats? Are they long-lived?
14. Storage and backup strategy?
15. When will I publish it and where?
16. Is there an ontology or other community standard for data sharing/integration?

Create a Data Management Plan

Planning for your data management needs ahead of time will save you time and resources in the long run and ensure that your data will be usable in the future. A formal plan can be valuable to you and may be required by your funding agency. Topics to cover in a written plan include:

• name of the person responsible for data management within your research project
• description of data to be collected and the methodology
• how data will be documented throughout the research project
• data quality issues
• backup procedures
• how data will be made available for public use and potential secondary uses
• preservation plans
• any exceptional arrangements that might be needed to protect participant confidentiality or intellectual property

For tips on creating a data sharing or management plan, see the:

• Australian National University Data Management Manual
• NIH examples of data sharing plans
• RELU-DSS Data Management Plan

Guides to Data Management

The following guides cover general principles for managing your data, plus select information related to particular formats or disciplines.

• Australian National University: Data Management:
  Information from courses and a manual on data management.
• CIESIN: Geospatial Electronic Records: Resources on managing and preserving geospatial data and related electronic records.
• ICPSR Guide to Social Science Data Preparation and Archiving (pdf): Outlines best practices throughout the research process, including applying for a research grant, collecting data, and preparing data for deposit in a public archive.
• Oak Ridge National Laboratory: Best Practices for Preparing Environmental Data Sets to Share and Archive: Describes the practices to make data sets ready to share with others.
• UK Data Archive: Manage and Share Data: Provides best practice strategies and methods for creating, preparing and storing shareable datasets. See also Managing and Sharing Data:a Best Practice Guide for Researchers (pdf).

This page was last updated on Thursday, 16-Jul-2009 08:02:27 EDT

Faculty Successes:

"I've had thousands of downloads of my published data--I am impressed that it's been so useful to others!"

Esther Duflo, Abdul Latif Jameel Professor of Poverty Alleviation and Development Economics, MIT