With a low barrier to entry and large ecosystem of tools and libraries, Python is the lingua franca for geospatial development. Whether you are doing data acquisition, processing, publishing, integration or analysis, there are no shortage of solid Python tools to assist in your day to day workflows.

This workshop will provide an introduction to performing common GIS/geospatial tasks using Python geospatial tools such as OWSLib, Shapely, Fiona/Rasterio, using common geospatial libraries like GDAL, PROJ, pycsw, and other tools from the geopython toolchain. Manipulate vector/raster data using Shapely, Fiona/Rasterio. Publish data and metadata to OGC web services using MapScript, pygeometa, and pycsw. Visualize your data on a map using Jupyter and Folium. Plus a few extras in between!

The workshop is provided using the Jupyter Notebook environment with Python 3.

This workshop provides a practical, overview of key software used within a Spatial Data Infrastructure (SDI). It will be useful for a business people and techies with little or no experience with the range of Open Source Geospatial software, and who would like first hand experience with these tools.

In the workshop we will use OSGeoLive and the Open Source software and sample data shipped with it to get to know the components of an SDI. We will get our hands dirty using some of the leading applications, and will introduce the other applications on OSGeoLive and when they are used.

A Spatial Data Infrastructure (SDI) is a data infrastructure that provides geographic data and metadata, which is accessible for several users and incorporates a variety of tools to accomplish different processes. It helps make data accessible, maintainable and findable throughout your organization.

We will start with different types of geographic data and learn about how to store data in a PostgreSQL/PostGIS database.

As second step, we will have a look at a service based infrastructure and you will learn about OGC services like OGC Web Map Service and OGC Web Feature Service. You will learn how to create these services with software like QGIS Server, MapServer or GeoServer. We will practice with QGIS server.

A client is needed to view and analyse data from services. We will learn about Desktop GIS and WebGIS and load Services in QGIS and publish data to the web using OpenLayers, GeoNode and Mapbender.

We will learn about metadata and how to make data traceable in a metadata system like GeoNetwork or pycsw. We will practice with pycsw and GeoNode.

And you will learn how you can control the access to your data and setup a user management.

After the journey through all the components you will be familiar with the concept and the advantages of a Spatial Data Infrastructure, and will know where to look for deeper insights into the more powerful features of the various tools.