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Data Management

a guide to best practices for curating your research data

Chemistry & Physics Librarian /
Science Data Specialist

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Laura Palumbo
Library of Science and Medicine
Piscataway, NJ 08854


This guides discusses several stages of data management:

And there are 

  • More Links to further resources on data management

Why Data Management?

If you are generating and/or using data in your research, a well-thought out approach to data management will save you time and frustration, maximize the impact of your work, and is an important component of the responsible conduct of scholarship.  A data management plan can help you: 

The Data Management Presentation (Powerpoint) summarizes the important factors in data management.

What is Data?

Research data can be any systematic collection of information that is used by the researcher for their analysis.  Typical examples of data include sensor readings, experimental result recordings, survey results, or simulation output.  Numeric data in various formats abounds, but research data can also include video, sound, or text data, if it is used for systematic analysis.  For example, while a feature film would usually not be considered research data, a corpus of video interviews that had been tagged to identify gesture and facial expression would be considered research data.

Research data must be appropriately structured and documented in order for it to be used effectively for analysis.  Any unique programs or models needed to analyse the data stream should be preserved as well.


This guide is heavily modeled on the excellent data management guides at

MIT Libraries and the

University of Minnesota Libraries


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