This is the "Overview" page of the "Research Data Management" guide.
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Research Data Management   Tags: data  

Resources for learning about best practices in research data management across a variety of disciplines.
Last Updated: May 7, 2015 URL: Print Guide RSS UpdatesEmail Alerts

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What is research data?

Research data is loosely defined as information collected, observed, or created for purposes of analysis to produce original research.

This includes observational variables like rainfall, wind speed, water quality, or survey data; simulated data from earthquake models; experimental data from lab instruments; and derived or compiled data for text mining or testing algorithms. Research data can take almost any digital file format (video, text, photographs, numbers), so managing it effectively can be a challenge.

If you've found this page, it's likely that you manage some form of research data, either your own, your lab's, or your advisor's. Many researchers are not taught data management skills in their graduate courses. This guide and accompanying workshops aim to help fill this gap with the expertise that librarians and data specialists can offer.


Why is managing research data important?

Good data management:

  • ensures integrity of data
  • ensures that data is findable and usable when grad students leave projects over the years
  • makes the data of a project readily understandable to people outside the project
  • enables the sharing of data within and across disciplines
  • makes it easier to archive and preserve data in the long term
  • encourages data citation to increase the impact of the research

Science & Social Science Data Librarian

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Michelle Hudson
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Data Librarian

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Kristin Bogdan
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