Data exists in a myriad of formats, such as text, numerical, multimedia, models, software, and can be discipline-specific and instrument-specific.
When we talk about data we are referring to:
Data captured in real-time, usually irreplaceable.
Examples: Sensor data, telemetry, survey data, sample data, neuroimages.
Data from lab equipment, often reproducible, but can be expensive.
Examples: gene sequences, chromatograms, toroid magnetic field data.
Data generated from test models where model and metadata (inputs) are more important than output data.
Examples: climate models, economic models.
- Derived or compiled
Data that is reproducible (but very expensive).
Examples: text and data mining, compiled database, 3D models, data gathered from public documents.
The CPDN can help Arctic and Antarctic researchers manage the data that they produce. This site describes resources available for managing data throughout their lifecycle.
Credit: MIT Libraries for permission to use and adapt their pages.