Data may be grouped into four main types based on methods for collection: observational, experimental, simulation, and derived. The type of research data you collect may affect the way you manage that data. For example, data that is hard or impossible to replace (e.g. the recording of an event at a specific time and place) requires extra backup procedures to reduce the risk of data loss. Or, if you will need to combine data points from different sources, you will need to follow best practices to prevent data corruption:

• Observational Data.Observational data are captured through observation of a behavior or activity.
• Experimental data are collected through active intervention by the researcher to produce and measure change or to create difference when a variable is altered.
• Simulation Data are generated by imitating the operation of a real-world process or system over time using computer test models.
• Derived data involves using existing data points, often from different data sources, to create new data through some sort of transformation, such as an arithmetic formula or aggregation.