Data Management Offboarding

Having carried out biomedical research, you have produced and/or acquired reagents and datasets, developed and used experimental and data analysis methods, and accumulated other important research records.

To ensure long-term accessibility and facilitate reuse of your reagents, data, and methods by colleagues, it is important to create a descriptive Knowledge Transfer File with relevant metadata. Refer to this document throughout the offboarding process.

• Your scientific advisor, lab manager, or department administrator may be able to provide a template or formatting suggestions to guide you as you create your Knowledge Transfer File.
• Further information about the creation of a Knowledge Transfer File is provided throughout this checklist.

The Knowledge Transfer File should include:

• Contact information related to projects, reagents, and datasets
• Location of reagents, datasets, and research files
• Documentation regarding publicly shared datasets (e.g., README Files)
• How the projects, reagents, and datasets relate to publications and grants
• Specific grant information relevant to projects, reagents, and datasets, including grant number, start, and end dates
• Project start and end dates, if known
• Other key dates associated with project timelines, reagent and dataset production, and publication
• Additional metadata addressing file naming conventions, directory structure, file formats, relevant software tools, access permissions, and versioning

Download and utilize the Knowledge Transfer File Template.

Harvard and many granting agencies have requirements addressing the timelines for data retention and maintenance. Determine the length of time the data produced must be retained per Harvard policy.

• Consult your PI, lab manager, or department administrator for specific policies related to your area of study.
• Include within your Knowledge Transfer File:
  • Grant information relevant to projects and datasets, including grant number, start, and end dates
  • The entity responsible for future maintenance of the data

• Review existing lab and departmental data storage protocols.
• Review and organize data in collaborative folders so they are easily accessible to colleagues.
• Create and/or update your README documents with basic metadata for each distinct dataset.
• Document in your Knowledge Transfer File, and/or other format requested by your PI or lab manager, the location of data (electronic or otherwise) related to your research.
  • Review recommended practices for data evaluation and appraisal
  • Retention and Maintenance of Research Records and Data: Principles and FAQs (PDF)

• Transfer file folder and webpage/website ownership, as appropriate.
• Review recommended practices around data security and access.
• Review recommended collaborative tools and software.

• Contact the group responsible for research data management at your institution to learn more about long-term storage options (e.g., HMS Research Data Management).
• Identify data for migration to long-term storage.
• Ensure residual data not moved to long-term storage is properly backed up to prevent data loss.
• Document the location of data moved to long-term storage in your Knowledge Transfer File and/or other format requested by your PI or lab manager.

• Discuss with your PI the deletion of duplicate or dispensable data to help reduce lab or departmental storage usage.
• Review guidance on Data Retention, Archives and Records Management, and Data Destruction.
  • Utilize the Harvard Library General Records Schedule (requires HarvardKey).

• Store your lab notebook and other lab records according to lab protocol.
• Confirm your lab notebooks are accessible to appropriate lab members and collaborators.
• Review options and guidance for Electronic Lab Notebooks.

Properly protecting research data is a fundamental obligation grounded in the values of stewardship, integrity, and commitments to the providers and sources of the data.

• The University's Harvard Research Data Security Policy (HRDSP PDF) addresses the need to protect confidential and sensitive information that is maintained in the various spheres of University administration, and the proper management and stewardship of research data.
• The University’s Intellectual Property (IP) Policy governs the ownership and disposition of IP including, but not limited to, inventions, copyrights (including computer software), trademarks, and tangible research property such as biological materials. The policy encourages the viewpoint that ideas or creative works produced at the University should be used in ways that are meaningful in the public interest.
• Consult with your PI or lab manager for further guidance, as necessary.
• Complete the Harvard Research Data Security Training Course (University-Wide).

• Identify publisher, funder and/or institutional requirements for data sharing and long-term maintenance.
• Consult Data Use Agreements (DUAs) to understand data sharing restrictions. When required, contact the Office of Research Administration to obtain a DUA.
  • Harvard Data Use Agreement (DUA) Guidance (PDF)

• Review appropriate data repositories to comply with data sharing requirements.
  • Explore the Registry of Research Data Repositories (re3data.org).
• Identify which of your datasets are or should be deposited and shared in public repositories.
• Identify which of your datasets are or should be deposited and shared in non-public repositories.
• Confirm that data in proprietary repositories is appropriately accessible to other lab members.
• Document shared datasets in your Knowledge Transfer File.

• Consult with your PI or lab manager prior to data transfer.
  • Note that, in most cases, it will be required that data generated at Harvard remain in your Harvard lab or department. However, copies of data may be transferred once appropriate permissions are obtained.
  • Review the Harvard Faculty Disclosure & Intellectual Property Protection Guidance for Researchers.
• If transferring data to another institution prior to your departure, ensure that sensitive data are securely stored.