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Writing a data management plan: Classification of research data

Research data can be generated for different purposes and through different processes in a multitude of digital formats. The following classification was compiled by the Research Information Network:

Observational: data captured in real time, usually unique and irreplaceable, for example brain images, survey data

Experimental: data from lab equipment, often reproducible, but can be expensive, such as chromatograms, microassays

Simulation: data generated from test models where model and metadata may be more important than output data from the model, for example economic or climate models

Derived or compiled: resulting from processing or combining 'raw' data, often reproducible but expensive, such as compiled databases, text mining

Reference or canonical: a (static or organic) conglomeration or collection of smaller (peer reviewed) datasets, most probably published and curated, for example gene databanks, crystallographic databases

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PILOT - Writing a data management plan by Edina, University of Edinburgh modified by Marion Kelt, GCU is licensed under a Creative Commons Attribution 4.0 International License. Based on a work at http://datalib.edina.ac.uk/mantra/introduction.html