What Is Research Data? Types and Examples
Research data is more than spreadsheets. A clear overview of the main types — observational, experimental, simulation, and derived — with examples and why classifying yours matters for sharing.
More than spreadsheets
"Research data" is any material collected, observed, or created to validate research findings. It spans far more than tables of numbers — images, audio, code, survey responses, sensor readings, and more all count.The main types
- Observational — captured in real time and often impossible to recreate (field surveys, sensor logs, telescope readings). The most precious to preserve.
- Experimental — produced under controlled conditions (lab measurements, gene sequences). Usually reproducible, but costly to repeat.
- Simulation — generated by models (climate models, economic forecasts). Often the model + inputs matter more than the output.
- Derived / compiled — built by processing existing data (text-mined corpora, aggregated indicators).
Why the type matters
The type shapes how you should manage and share it. Irreplaceable observational data demands the most careful preservation; simulation data may be regenerable from code and parameters, so sharing those can matter more than the raw output.The common thread
Whatever the type, the same principles apply: describe it with metadata, give it a persistent identifier, license it clearly, and deposit it somewhere that keeps it findable.By Super Admin