In GIS, we work with three categories of data - primary, secondary, and derived data. These aren't unique to GIS - many sciences use similar classifications - but within our field, they have specific meanings.
Primary data is what you collect yourself, either by digitizing features from aerial and satellite imagery or gathering field measurements with GPS devices. Both methods involve direct interaction with the landscape in a deliberate, hands-on way.
Secondary data comes from other sources - existing datasets created by someone else that you download or obtain for your own purposes.
Derived data is anything you create by running geoprocessing tools on primary or secondary data (we'll dig into geoprocessing in Chapter Seven).
Primary data generally carries more weight in analysis because it hasn't passed through processing steps where errors might creep in from improper tool use, misunderstandings about the data, or other mishaps (Chapter Eight covers this in detail).
In this chapter, we'll explore manual and heads-up digitizing, get a basic understanding of remote sensing, learn methods for converting paper maps to digital formats, turn postal addresses into coordinates through geocoding, collect data using smartphone GPS apps and commercial receivers, create data through crowdsourcing, and modify existing datasets. Creating and correcting data are the two most common tasks GIS technicians do every day, so having a solid grasp of the what and why behind data creation and editing is essential.