
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