Polygons extend the lines and include 3 or more points (i.e. the area, city or ward that street belongs in).
Raster data normally refers to imagery or satellite data that are formed from a grid of pixels.
Once you have established your type of data then attribute data can be added; this would depend on your area of interest, but it can consist of spatial data (which refers to the size, shape and location of the feature) and non-spatial data (which refers to other attributes linked to the feature).
Taking an example from my dissertation, I china rcs data produced a map displaying different areas across the county of Cheshire (i.e. spatial data), but each of these areas had additional attributes, for instance the urban/rural makeup (i.e. non-spatial data). data focused on the polygon level, as the original dataset I worked with contained information on the number of missing incidents across different LSOAs (Lower-Layer Super Outputs, which are essentially small-scale geographic areas). I then matched the different LSOAs to different environmental correlates, including the levels of deprivation and mental health issues in each area. By joining the dataset to these attribute files, I was able to create a new dataset specifically tailored to help answer my research questions and aims.