Research Data Management is essential for responsible research and should be introduced when starting a new project or joining a new lab. Managing data across a project and/or a team allows for accurate communication about that project. Setting up a clear data management plan and strategy for consistent data documentation makes the research process throughout the entire lifecycle smoother. So, where do you start?
We have created guidance that outline the important steps for onboarding new employees and/or trainees to a lab or new projects. While the principles are general, these documents focus on Harvard policies and resources. You will find internal links to applicable practices, and external links as supplementary resources. For assistance with terminology, visit Data Management Terminology.
Once you have set up standard procedures for onboarding employees, ensure you close the lifecycle of their work with RDM Offboarding and Knowledge Transfer!
New Lab Onboarding: Data Planning
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Review Lab, Department, and University Data Management Policies
- Contact the PI and department Research Administrator for lab and department-specific data management policies.
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Create a Preliminary Data Workflow
- Review existing lab workflows, directory structures, and metadata standards.
- Develop a preliminary organizational workflow for your research, including a file (or directory) structure.
- Review Recommended Practices: Directory Structure
- Review Recommended Practices: File Naming Conventions
- Creating and following a data management workflow can substantially reduce the amount of storage needed by the lab by removing unnecessary and redundant files.
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Create Preliminary README File(s) for Each Dataset
You will use these files throughout your research to document your workflow. The metadata you record will help ensure your data are understandable, usable, discoverable, and reproducible.
- Document your data workflow(s) in a README file. The metadata you record will help ensure your data are understandable, usable, discoverable, and reproducible.
- Review Recommended Practices: README Files
- Be aware of the metadata required to complete a Knowledge Transfer File after completing your research. Plan to track the information throughout your workflow.
- Download and utilize the Knowledge Transfer File Template.
- Document your data workflow(s) in a README file. The metadata you record will help ensure your data are understandable, usable, discoverable, and reproducible.
New Lab Onboarding: Data Storage
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Review Storage Options
Harvard offers several storage options, allowing researchers to store data in different places, with varying behaviors, performance, and means of access.
- Review storage tools in compliance with University regulations and policy
- Review Recommended Practices: Storage.
- HMS: HMS Research Data Management
- HSPH: Research Computing & Data Resources
- Ensure data is properly backed up to prevent data loss (e.g., HMS IT Software and Backups)
- Review storage tools in compliance with University regulations and policy
New Lab Onboarding: Data Sharing
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Review Policies of Confidentiality, Data Security, and Intellectual Property (IP)
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 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.
- Review Harvard Policy: Harvard Research Data Security Policy (HRDSP)
- Review Harvard Policy: University’s Intellectual Property (IP) Policy
- Consult with your PI or lab manager for further guidance, as necessary.
- Complete the Harvard Research Data Security Training Course (University-Wide)
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Review Available Collaborative Tools
- Review collaboration tools in compliance with University regulations and policy
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Review Potential Data Repositories
- Compare and contrast general data repositories and data publication resources available to biomedical science researchers.
- Review Recommended Practices: Repositories
- Explore the repository finder: Registry of Research Data Repositories
- Ask your PI or colleagues about established, public data repositories relevant to the data types you are working with.
- Compare and contrast general data repositories and data publication resources available to biomedical science researchers.
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Review Electronic Lab Notebook (ELN) Resources
- An Electronic Lab Notebook (ELN) is a software tool that replicates an interface much like a page in a paper lab notebook.
- ELN’s allow users to enter protocols, observations, notes, and other data using a computer or mobile device.
- Review Recommended Practices: Electronic Lab Notebooks
New Project Onboarding: Data Planning
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Transfer Prior Data and Related Records to the University (if relevant)
- If transferring prior data or records to Harvard, contact the Office of Research Administration.
- The department Research Administrator will need to obtain Chair or Institute Director approval.
- Data Use Agreements (DUAs) govern access to and treatment of data: (i) provided by an outside organization to Harvard for use in Harvard research, or (ii) provided by Harvard to an outside organization for use in its research.
- When required, contact the Office of Research Administration to obtain a DUA.
- Review Recommended Practices: Data Use Agreements
- Review Harvard Policy: Harvard Data Use Agreement (DUA) Guidance
- If transferring prior data or records to Harvard, contact the Office of Research Administration.
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Review Project and Granting Institution Requirements
The grant program funding your project may have data management and sharing requirements. If you have non-federal funding, check with your granting agency.
- Review NSF Policy: NSF Data Management and Sharing requirements
- Review NIH Policies:
For projects involving human subjects research, review any project-specific requirements stipulated by Harvard’s Institutional Review Board (IRB).
- Review Harvard Policy: Harvard Longwood Medical Area Office of Regulatory Affairs and Compliance
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Write a Data Management Plan or Review Existing Data Management Plan
Construct a Data Management Plan (DMP) for the project.
- The document describes data organization, storage, data security, final dataset formats, documentation, analytic tools necessary to use the data, data sharing requirements, retention plans, and how and when the data will be made accessible to others.
- Creating and following a DMP can substantially reduce the amount of storage needed by the lab by removing unnecessary and redundant files.
- Review Recommended Practices: Data Management Plans
- Utilize the DMPTool and Countway DMP Review Service.
Many publishers and funders have data management and data sharing requirements.
- Review Recommended Practices: Share & Publish
Be aware of the metadata required to complete a Knowledge Transfer File after completing your research.
- Download and utilize the Knowledge Transfer File Template.
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Create a Data Workflow or Review Existing Data Workflow
Determine if you need to:
- Review existing project workflows and directory structures
- Develop a new organizational workflow, including a file (or directory) structure.
Creating and following a data management workflow can substantially reduce the amount of storage needed by the lab by removing unnecessary and redundant files.
- Review Recommended Practices: Directory Structure
- Review Recommended Practices: File Naming Conventions
Consider using an Electronic Lab Notebook (ELN).
- An ELN is a software tool that replicates an interface much like a page in a paper lab notebook. ELN’s allow users to enter protocols, observations, notes, and other data using a computer or mobile device.
- Review Recommended Practices: Electronic Lab Notebooks
Consider recording protocols and methods in protocols.io so they can be shared, when appropriate.
- Review Recommended Practices: Scholarly Products
- Utilize Countway Protocols.io Service
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Establish a Metadata Standard or Review Existing Project Metadata Standards
Well thought-out metadata facilitates better understanding, use, and sharing of experimental data now and in the future, helping researchers to discover, access, use, repurpose, and cite data over the long-term, facilitating lasting archival preservation of data.
- Determine whether a metadata standard is already in place for the project or whether a new metadata standard is needed.
- To establish a new metadata standard, review existing metadata standards relevant to the project to determine suitability for adoption/adaptation.
- Establish controlled vocabulary or adapt existing controlled vocabulary for the project.
- Determine where metadata are stored or should be stored for the project so that metadata are appropriately linked to experimental data.
- Review Recommended Practices: Metadata
- Determine whether a metadata standard is already in place for the project or whether a new metadata standard is needed.
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Create Preliminary README File(s) for Each Project Dataset
Document your data workflow(s) in a README file. You will use these files throughout your research to document your workflow. The metadata you record will help ensure your data are understandable, usable, discoverable, and reproducible.
- Review Recommended Practices: README Files
New Project Onboarding: Data Storage
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Review Storage Options
- Review storage resources in place for the existing project or choose relevant storage options for a new project in compliance with University regulations and policy.
- Review Recommended Practices: Storage
- HMS: HMS Research Data Management
- HSPH: Research Computing & Data Resources
- Review storage resources in place for the existing project or choose relevant storage options for a new project in compliance with University regulations and policy.
New Project Onboarding: Data Sharing
-
Review Policies of Confidentiality, Data Security, and Intellectual Property (IP)
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) 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)
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Review Publisher and Funder Requirements
Your funder and/or the journal in which you publish your research may have data sharing requirements.
- Review Recommended Practices: Data Sharing
- Review NSF Policy: NSF Data Management and Sharing requirements
- Review NIH Policies:
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Review Available Collaborative Tools
- Review collaboration tools in compliance with University regulations and policy.
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Review Potential Data Repositories
- Review public data repositories already established for an existing project, or choose a relevant data repository for a new project.
- Review Recommended Practices: Repositories
- Explore the repository finder: Registry of Research Data Repositories
- For some projects or scientific areas, established data repositories are not available for the data types produced. You may need to develop a new repository for your project.
- Compare and contrast general data repositories and data publication resources available to biomedical science researchers.
- Review public data repositories already established for an existing project, or choose a relevant data repository for a new project.
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Consult or Initiate Data Use Agreements (DUAs)
Data Use Agreements (DUA) govern access to and treatment of data: (i) provided by an outside organization to Harvard for use in Harvard research, or (ii) provided by Harvard to an outside organization for use in its research.
Consult your DUA, if your data are subject to one, to understand requirements or restrictions around sharing relevant data. Under some circumstance, you may need to initiate a DUA with collaborators or entities with which you are planning to share your data.
- Review Recommended Practices: Data Use Agreements
- Review Harvard Policy: Harvard Data Use Agreement (DUA) Guidance
