The concept of data is discussed more broadly in Introduction to Data. Here we take a quick look at spatial data in particular. In short, spatial data adds a geographic dimension to a qualitative and/or quantitative data set, situating it in a particular location within a coordinate system relative to other data points. (The coordinate system can be a real-world system or a locally created one used to meet the needs of a particular project.)
For example, the project, Mapping Islamophobia, demonstrates how geospatial data can be combined with other data points (i.e., date, gender, and type of incident). Collectively, the data brings to light, from a geospatial perspective, trends in hostility and hate toward Muslim Americans.
The following represent questions that would benefit from a spatial data-oriented analysis and DS mapping methods.
How has the spatial patterning or characteristics of Hmong immigration to Minneapolis–Saint Paul changed over time?
Where in the city has the increased number of health clinics had the greatest impact on reducing diabetes-based illnesses? How does this data correlate with race and economic status?
How do characters in War and Peace move around a physical environment over the course of the book, and how does this connect with larger themes?
How are historical monuments clustered in downtown Boston in comparison to other major cities?
How can we visualize the movement of Jesuit missionaries travel over the course of the 18th century?