Now the spatial data has had attribute data added to it, we refer to it as a spatial object. Spatial objects are stored via data formats known as shapefiles, which can include points, lines and polygons. They represent digital vector storage formats that contain geometric information and attribute information. Shapefiles can represent different measures of the population from large-scale country boundaries to small-scale LSOA boundaries.
In order to narrow the dataset to just the Cheshire county, I used china rcs data the Boundary Data Selector interface (BDS). The BDS, a fantastic resource provided by the UK Data Service, is a piece of open software providing digitised boundary datasets representing the underlying geography of the Census. Users have the choice to select which boundaries they want (e.g. census, electoral, postal), the areas they want (within the UK), and in which format (e.g. shapefiles, CSV). These datasets can then be combined with other datasets to create new and richer data.
In my case, I selected LSOAs in Cheshire and then joined these to the dataset described above, so now I had data on missing person incidents and levels of deprivation and mental health issues for LSOAs specifically within Cheshire. As a result, I had a useable spatial object, also known in the field as an ‘sf object’, which would run alongside all of R’s spatial packages (more on R and other GIS software later on!).