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Research Data Management

Why is research data important?

Research data management (RDM) will help you:

  • Save valuable time and resources
  • Preserve your data
  • Maintain data integrity
  • Meet grant requirements
  • Promote new discoveries
  • Support open access and open data

RDM is the compilation of small practices that make your data:

  • Easier to find & understand
  • Less likely to be lost
  • More likely to be usable during a project or 10 years later

Most importantly you don't want to lose your data!

What is data?

What is data?

Data is anything you perform analysis on.

Data can:

  • Be both digital and physical (i.e. computer files and paper survey responses)
  • Be from many fields - sciences, humanities, etc
  • Include research notes or lab notebooks, survey responses, software, code, measurements, images, audio, video, and physical samples.

- Data Management for Researchers by Kristin Briney    

Types of research data

Quantitative vs. Qualitative

  • Quantitative - numeric data (social sciences, physics, etc.)
  • Qualitative - descriptive in nature and deals with the quality of things (anthropology, history, etc.)

Primary vs. secondary data

  • Primary data - data that is collected by the researcher for a particular project. This is original data that is created from an experiment or observation. Gathered and maintained by the researcher. 
  • Secondary data - data originally created by someone else. For instance, census data or data via open access repositories. 

Other types of data

  • Experimental data - derived from controlled, randomized experiments
  • Observational data - gathered in instances where it is not possible to conduct a controlled experiment
  • Computational data - the output of a computer that has taken a large set of data and run it through a simulation
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