This guide was developed by the CUNY Office of Library Service to assist with Research Data Management.
Observational: data captured in real-time, usually irreplaceable (e.g., censor data, telemetry, survey data, sample data, neuroimages)
Experimental: data from lab equipment, often reproducible, but can be expensive (e.g., gene sequences, chromatograms, toroid magnetic field data)
Simulation: data generated from test models where model and metadata (inputs) are more important than output data (e.g., climate models, economic models)
Derived or compiled: data that is reproducible, but very expensive (e.g., text and data mining, compiled database, 3D models, data gathered from public documents)
Data description
Standards
Access, Sharing, and Re-use
All CUNY faculty members, postdoctoral scholars, graduate and undergraduate students involved in research are required to complete the CITI RCR training within six weeks of initiating their research. A list of Research Integrity Officers by campus is available on the CUNY website.
This guide was developed by the CUNY Office of Library Services and is based on (and, in some cases, pulls from) guides created at the libraries at the CUNY Graduate Center, New York University, Massachusetts Institute of Technology, University of Massachusetts, University of Michigan, and Stanford University.
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