Social Work: Research Overview

Data types generally fall into five categories:

Observational
- Captured in situ
- Can’t be recaptured, recreated or replaced
- Examples: Sensor readings, sensory (human) observations, survey results

Experimental
- Data collected under controlled conditions, in situ or laboratory-based
- Should be reproducible, but can be expensive
- Examples: gene sequences, chromatograms, spectroscopy, microscopy

Derived or compiled
- Reproducible, but can be very expensive
- Examples: text and data mining, derived variables, compiled database, 3D models

Simulation
- Results from using a model to study the behavior and performance of an actual or theoretical system
- Models and metadata, where the input can be more important than output data
- Examples: climate models, economic models, biogeochemical models

Reference or canonical
- Static or organic collection [peer-reviewed] datasets, most probably published and/or curated. 
- Examples: gene sequence databanks, chemical structures, census data, spatial data portals.