Getting started with research data management

by Sarah Elichko

There’s a lot of buzz around research data.  A recent blog post in the Chronicle of Higher Education asks who will pay for the organization, maintenance, and storage of “Big Data”?  The whole post is worth reading, but to summarize:  libraries are at the top of the list.  A small ethnographic study from the UK recently concluded that data management skills are in high demand and low supply.  And as more funders like the National Science Foundation require data-sharing plans from grant recipients, the demand for assistance with data planning and management seems likely to increase.

With so much discussion about data and libraries, I’ve collected a few of my favorite resources in one place.

In the hospital library where I work, clinicians and researchers often want to know how many cases of an illness have occurred in the past year, or how widely used a particular treatment is.  To answer these questions, we look for relevant statistics.  Yet the resources discussed in this post will look at working with data, not just statistics.  Confused about the distinction between data and statistics?  Hailey Mooney from Michigan State University has put together a concise and useful explanation of the differences.

Flip through this presentation (PDF) from the MIT Libraries to learn the basics of research data.  You’ll follow the creation of research data from the microscope to the archive.  (There are a lot of slides, but most are very concise.)

Health sciences librarians face particular data management challenges when conducting literature searches for systematic reviews and meta-analyses.  Search strategies must be documented and reproducible.  Connie Schardt of the Duke University Medical Center Library provides a valuable resource with data management tips for working on a systematic review.  (If you’re interested in reading more about librarians as coauthors on systematic reviews, check out this Medlib-l discussion from earlier this year.)

ICPSR (Inter-university Consortium for Political and Social Research) is a major resource for finding raw data in the social sciences.  If you have access to a program like SPSS, SAS, or Excel, you can look at some datasets from completed research.  Download the zip file for a study and use the codebook to make sense of the data files themselves.  ICPSR offers a New User Guide that walks you through the process.  If you prefer a video-based approach, check out ICPSR’s recorded webinars.

Finally, if you’re really committed to learning about data management, consider setting aside a few hours to go through MANTRA, the University of Edinburgh’s free online data management course.  It’s an interactive online course aimed at graduate students preparing to start their research. MANTRA walks you through data management concerns at each step of the research process, looking at issues like file naming, version control, formats for long-term storage, and planning for retrieval of your research data.


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