GIS-Box: Data Factory

Meaningful maps are based on a solid foundation of information. But what does this look like? Data formats such as CSV, JSON or GeoPackage help to store information in a structured way, but how is it best processed? OpenStreetMap offers a wealth of geoinformation, but how can this information be accessed and easily processed?

Beyond applications like QGIS (GIS Basics), information can be customized, adapted, visualized and analysed by using Python programming. In this course, we show the basics of object-oriented modelling as well as different data formats. We also deal with data transformation and scripting, data modelling and work out basic algorithms of spatial analysis. We will query OSM for information and create simple analysis maps and graphs. The aim is to understand the structure and composition of spatial data in order to be able to process and analyse it.

Skills and goals: • Analysis and modelling of data • Basic understanding of data structures generic / GIS-specific • Basic Python programming skills • Data transformation and linking • Data examination and investigation

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