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Data Management Toolkit

This toolkit provides guidance for writing a data management plan. It also includes information about services and tools for data management.

Description of Data

Tips for this section of the DMP:

  • Identify what data will be collected in your project.
  • Determine how that data should be described and labeled.
  • Think about standards and formats relevant to your data.

Types of data

What types of data will be generated by your research?a clipboard with the word "discovery" on the metal clip, holding a piece of paper displaying data in columns

"Data" are the recorded, factual material commonly accepted in the scientific community as necessary to validate research findings.

 

Examples of research data:

  • observational (e.g., sensor data, data from surveys) 
  • experimental (e.g., gene sequencing data) 
  • simulation (e.g., climate modeling data) 
  • derived or compiled (e.g., text mining, 3D models)
  • reference or canonical (e.g., static, peer-reviewed data sets, likely published and curated)

 

For more examples of research data and an explanation of the difference between research data management and records management, see this resource, linked below, from the U. Oregon Libraries.

Data and metadata

How will you describe your data?

Documentation of data - how they are described - is an important factor when developing a data management plan. 
the word "meta" burned into a piece of wood

"Metadata" is essentially description or documentation about data - e.g., "title," "format," "specimen," "date," "location," etc.

Data that are well documented are more easily discovered and re-discovered by others interested in your data. Complying with an accepted standard will also help in the indexing and retrieval of data.

An important best practice for creating metadata is to use a controlled vocabulary (definition linked below), a standardized terminology for your community of interest.

Points to consider:

  • What information about your data will you need to save (i.e., experimental design, environmental conditions, global positioning information, etc.)?
  • What metadata standard will you use to document your data?
    • If you're not sure, the Libraries can help. Contact us via the email address at left - see the "Need data management help?" box.
  • Some research domains have widely accepted standards, others may not.
    • The Libraries can help you navigate the complex terrain of data standards.
    • Contact us via the email address at left - see the "Need data management help?" box.
  • How do you plan to record or enter your metadata?