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.

Spatial manipulation and cartography with R software has been made easy and fun in recent years.

R is an open source language and environment for statistical computing and a major player in the field of data science.
Its community is one of the most welcoming and inclusive communities for programmers.
In this respect, it is very similar to the OSGeo community.

Until recently, although possible, geospatial manipulations or creating nice maps were not easy in R.
But things have changed for the best! Packages like {sf} that allow easy Simple Features manipulation with direct connection to GDAL, GEOS, PROJ,
and geospatial functions offer a new tidy and easy way to manipulate spatial data.
R is a powerhouse for geostatistical analysis with tried and tested algorithms for spatial auto-correlation (Moran's I, Geary indices), spatial interpolation (kriging, etc),
and many more. Many packages allow one to create nice and decent maps, even interactive ones for the web!

This workshop is aimed at all levels of participants, from newcomers to GIS veterans and R users who want to get a grasp on spatial data and spatial analysis!
It will cover R basics, data manipulation, spatial operations, and cartography.

Detailed Outline: this tutorial will cover a variety of techniques that will help the user to manipulate geospatial data within R to produce insightful output.

An overview of the topics covered are:
* Understanding R basics (dataframes, functions, etc)
* Understanding spatial data in R
* Loading and manipulating spatial data (vector, raster, projections)
* Using spatial algorithms
* Creating maps and web maps