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Planning for Data Management

How can I best manage my data throughout the lifecycle of my research to save time and money in the future?

Goals:

Learn about Planning for Data Management

Utilize DMP Checklist for work

Planning: Discussion Questions

We talk about a Data Management Checklist. What is this in lieu of?

What is the purpose of this checklist?

What research artifacts is it targeted towards?

Who should be using this? And for how long?

Data Management Checklist

  • The checklist will help you define:
    • How the data will be created
    • How it will be documented
    • Who will be able to access it
    • Where it will be stored
    • Who will be back it up, and how & when
    • Whether and how it will be shared & preserved
  • Planning is not simply naming files and folders so that only your research team understand their content. Instead…
    • Putting standards and guidelines into action
    • Documenting detailed metadata for better data discovery and illumination
    • Ensuring the value and accessibility of your research long after your project is complete.
  • The checklist can inform a Data Management Plan (DMP), which is often required by funding agencies or philanthropic funders
    • E.g. NSF, NASA, Gates Foundation, Sloan Foundation

Use the Checklist for routine work

What should you manage?

Any data, code, documentation used throughout the research lifecycle:

Quantitative and qualitative data

Primary and secondary data

Notebooks

Codebooks

Records and notes

Code or software used to run analysis

Workflows or pipelines

Metadata or documentation describing the data (’data dictionaries’)

Record and retain sufficient information to enable others to understand and reproduce your work (aka winning the lottery scenario)

Planning: Recap & References

  • Talk to your department’s library and research computing staff early in the planning process
  • Use the Data Management Checklist to plan for your research
    • NB ! Some funders may require a Data Management Plan
  • Manage all notes, code, data, etc. to enable others to understand and reproduce your work
  • References:
  • Whyte, A., Tedds, J. (2011). ‘Making the Case for Research Data Management’. DCC Briefing Papers. Edinburgh: Digital Curation Centre
  • Briney, K. (2015).  Data Management for Researchers: Organize, maintain and share your data for research success . Pelagic Publishing Ltd.
  • 'Everyone Needs a Data Management Plan', Nature 555, 286 (2018); doi: 10.1038/d41586-018-03065-z
  • http://sites\.nationalacademies\.org/sites/reproducibility\-in\-science/index\.htm

Planning