Learn GIS the semantic way
An open learning path: for anyone learning GIS on their own, at their own pace. See Learning paths for how paths work.
Most GIS courses start with the software: this button buffers, that one clips. This path starts with the world. You learn to say what you are looking at and what question you are asking of it, to find the data that can answer the question, and to choose the operation that turns the data into an answer. The software comes last, as the Recipe that carries the operation out. Once you work this way, changing tools (QGIS, ArcGIS Pro, Python) changes only the last step.
You need: a computer that can run QGIS (free), and curiosity about a place you know. No earlier GIS experience.
Afterwards you can: turn a question about a place into a documented GIS workflow: what you observe, which data stand for it, which operations answer the question, and why you chose them.
The path
Each stage starts with the question it answers. Read the notes in the “Read” column first, then work through the Tasks and Examples.
1. Seeing the world as data
What is in the world, and how does it become data?
| Step | Read | Work through |
|---|---|---|
| What GIS is for | GIS, Geospatial data, 1.1 Introduction | |
| The workflow | 1.2 The workflow, GIS project | |
| Observing before recording | Ontology, world of observation, world of discourse, From Reality to Geospatial Data | |
| What kind of value is it? | The Four NOIR Data Types | |
| Objects or fields | Entity-based modelling, Field-based modelling, vector representation, raster representation | |
| Where on Earth | Coordinate Reference System (CRS), ESPG code, Shortlist of Danish, European and Global CRS, Projection |
2. Finding data the semantic way
Which datasets stand for the thing I am asking about?
| Step | Read | Work through |
|---|---|---|
| From question to data | SPHERE: start from a leaf (a question you can ask of the data) and follow it to the datasets that realise it | |
| How data are served | Geographical Web Services, [[Supporting concepts/Data and representations/Geospatial Data Access Methods/WFS | WFS]], Where to Find Danish Data |
| Getting started in QGIS | QGIS, Managing QGIS plugins (the SemanticGIS plugin loads SPHERE data directly) | Placing register units on the map (Task) |
| Good data habits | FAIR principles, Snapshot packages |
3. Operating on space
Which operation turns the data into an answer?
The Operators are the families of spatial operations. Each Task below is written with Operators, and its Recipe shows how to carry it out in a specific tool.
| Step | Read | Work through |
|---|---|---|
| Making your own data | Basemap | Georeferencing (Task), Backdrop digitalisation |
| Selecting by location | Spatial relations, Selection | |
| Summarising to areas | Aggregation, Modifiable areal unit problem, Square and hexagonal grids | Aggregating points to zones (Task); example: Dwelling size by construction period in Copenhagen (Example) |
| Distance and neighbourhood | Proximity | Distance to habitat (Task) |
| Combining layers | Overlay | Aggregating a categorical raster to zones (Task) |
| Surfaces | Slope and flow direction (Task), Aggregating a continuous raster to zones (Task) | |
| Seeing from above | Remote sensing | Vegetation index from satellite imagery (Task); example: Vegetation greenness at Ledreborg (Example) |
4. Communicating
How do I show the answer so that it is read correctly?
| Step | Read | Work through |
|---|---|---|
| The map as an argument | General-purpose Map, Visual hierarchy and figure-ground, scale | |
| Classes and colours | Classification for maps | Comparable choropleth maps (Task) |
5. Specialising
What do the questions of my field look like?
Choose a Domain hub close to your interests: landscape ecology, biodiversity, soil, climate, housing, hydrology, urban design, transport, energy, land use planning or ethnography. Each hub lists the questions the field asks, the data it often uses, and worked Examples. Work through one Example from start to end, and write down your choices as a Design Rationale.