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Research Data Management

Make a plan for your data

Data Management Planning (DMP)

Why do I need a DMP?

  • Save time for the research over the long term
  • Link personnel roles, responsibilities, activity, and support over the life of a project.
  • Prevent upheaval brought about by staffing changes
  • Assist with data queries

In general, a DMP should include:

  • Type(s) of data being collected (size, format, etc.)
  • Plans for documenting your research (including metadata)
  • Plans for data storage
  • Plans for data sharing and preservation

DMP main components

  1. Description of data and metadata
  2. Discussion of security, ethics, and intellectual property
  3. Plans for data access, sharing and reuse
  4. Plans for short-term management and storage
  5. Plans for long-term management, storage, and preservation
  6. Any resources needed or available

Funding agency considerations

Funding agency requirements vary widely so check their website before starting to write your DMP.

Data and metadata description

Basic information about the data being collected or produced (i.e. brief, general and nontechnical)

  • What types of data will be produced (e.g. experimental, observational, raw or derived, physical collections, models, simulations, curriculum materials, software)
  • How will it be acquired?
  • When and where will the data be acquired?
  • How much data will be acquired?
  • How much data will be processed?

Information about existing data

  • Will any existing data be used? Include information about its origins
  • What is the relationship between the existing data and data to be collected?

Information about files, formats, and directories that will be used during data collection, including file naming conventions, software that will be used to gather data, and file formats

Data and metadata description 2

Quality assurance and quality control

What will be done during:
  • sample collection
  • analysis?
  • data processing?

Project personnel

  • Who will be responsible for data management DURING the project, and what does that entail?
  • AFTER the project?

Metadata considerations

  • What contextual details are needed to make the data meaningful?
  • How will this metadata be created or captured?
  • When and by whom will the metadata be created or captured?
  • What form will the metadata take (standards) and why?

Security, ethics & intellectual property

Security

  • Are there ethical/legal obligations for privacy and protection?
  • How will the data be managed to protect privacy?
  • How will the data be stored, paying special attention to security measures?
  • Who will have access to the data, and at what stage of the project?

Intellectual property

  • Who owns the rights to the data created?
  • Will the data set(s) be covered by copyright?
  • If the data set(s) will be covered by copyright, who owns the copyright?
  • How will the data set(s) be licensed?
  • If any existing data sets are used, what are their licensing restrictions?

Ethics

  • Are there ethical and privacy issues that may prohibit sharing some or all of the data sets?
  • If these issues exist, how will they be resolved?

Resources / examples for writing a DMP

General outline for writing a DMP:

DMP Tool: ​​a free, online resource that guides you through writing the necessary sections of the DMP:

Data Management Planning: Self Assessment provides a list of questions to consider when writing a DMP:

Framework for creating a data management plan (ISPCR):

Best practices for DMPs

  • Write a DMP before starting a research project and write a separate DMP for each project
  • Write a DMP even if you funding agency doesn't require one
  • Share you DMP with all collaborators
  • Your DMP should be a living document (i.e. update it throughout the project lifecycle)

Examples of DMPs

Funding agency requirements

Why do funding agencies require DMPs?

  • Increased transparency and reproducibility of research
  • Increased awareness that data is a valuable part of research that need to be shared and preserved
  • Want to fund projects with well defined research data management practices

Resources for funding agency guidelines

 

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