This guide will help you get started with the basics of data management as a researcher. It includes important terms, evaluating your data needs, creating a data management plan, and storing and preserving your data.
It is becoming the norm for publishers and funding agencies to require researchers to share their data in a clear and concise manner. Learning how to develop good data management practices early in your career will make it easier to keep your data organized, meet funder requirements, and prepare sustainable data for sharing with others!
Staaks, J. (2013). Research Data Management. CC BY-NC 2.0 Retrieved from https://www.flickr.com/photos/jannekestaaks/14391226325
"Data is the output from any systematic investigation involving a process of observation, experiment or the testing of a hypothesis which when assembled in context and interpreted expertly will produce new knowledge." Pryor, G. (2012). Why manage research data? In G. Pryor (Ed.), Managing research data (pp. 1-16). London, England: Facet.
Research data is data that is collected, observed, or created, for purposes of analysis to produce original research results. The word “data” is used throughout this site to refer to research data. Research data can be generated for different purposes and through different processes, and can be divided into different categories, as shown below.
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