Research Data Management: What and Why

What Counts as Research Data?

Research Data are the recorded observations created, collected or observed in the process of conducting an original research project.  Research data can be either qualitative or quantitative in nature and may come in a wide range of formats, among them:

  • Qualitative Data (text; e.g. TXT, DOC, PDF, RTF, HTML, XML)
  • Quantitative Data (numerical data; e.g. CSV, MAT, XLS, SPSS)
  • Spatial Data (e.g. raster, vector, grid)
  • Multimedia – (e.g. JPEG, TIFF, MPEG, MP3, Quicktime, Bitmap)
  • Models – (e.g. 3D, statistical, similitude, macroeconomic, causal)
  • Software – (e.g. Scripts written in Java, C, Perl, Python, Ruby, PHP, R, GIS)
  • Instrument specific – (e.g. field surveying equipment)
  • Others (all other digital or non digital content have the potential to become Research Data)

Borrowed from the Portage Primer

What is Research Data Management?

Research Data Management (RDM) is the intentional process, throughout the entire lifecycle of a research project, of keeping data organized. This extends through:

  • planning the method(s) of data collection
  • to collecting and describing the data in a transparent structure
  • to ensuring its secure storage
  • to preparing it for analysis
  • to analyzing the results
  • to sharing the both the findings and the data itself
  • and then ensuring the data's long term storage upon completion of the research project.

Why is Research Data Management Important?

  Proper data management will help you:

  • satisfy grant, journal, or research ethics board requirements. For example the Tri-Agency has signaled they are getting more serious about enforcing the adherence to data management plans
  • ensure that your data is complete, documented, and accessible to you and to future researchers
  • raise the profile of your research

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Will Meredith
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Data Management Dictionary

Confused by some of the language around research data? You are not alone. This glossary will shed some light on the terminology around research data management.