Mapping Geospatial Data
Geospatial data, analysis and visualization are increasingly important components of humanities and social sciences research. Location and references to parts of the Earth can allow researchers to better understand the often complex interrelationships existing between humanity and context as they occur over space-time.
Examples applications include:
- Geocoding addresses or place names from historical artifacts
- Georeferencing tables to join with statistical boundaries
- Overlaying transport data on maps or imagery
- Spatial analysing of city populations and changes in density
- Mapping geographic features in an interactive, online map
- Advanced visualisation of 3D scan data to communicate key findings
Various tools exist to help researchers prepare, process and visualise geospatial data. The tools available through the Tinker website include:
- R (+spatial libraries)
- Python (+spatial libraries)
- Geocoder chooser
External tools include:
There is a huge range of geospatial datasets freely available through online search engines and data portals. Explore the range of Australian and International datasets curated by the Tinker team.
How do I get started?
Methods to prepare and use geospatial data are numerous. The following example recipes are offered to help you get started:
- Geocoding street addresses using AURIN
- Joining data with geospatial boundaries from the ABS
- Georeferencing historical place names and resolving ambiguities
- Creating an interactive map of locations using the R statistics platform