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.
Spring 2016 workshop series on Data Management topics on March 7 or March 8. Click here for details.
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.
In addition, there are many Centers at Rutgers with major data collections, such as: