Geospatial data management

Learn to define the concept of open data, and how to discover and use it as a research resource. Learn about about terms and conditions of accessing and using open data,as well as practical measures which help to decide whether to share data openly or not, and what part of it could be shared openly. […]

This learning module introduces different location data collection methods using smartphone GPS. This is especially interesting and important since they amount of people owning a smartphone nowadays is increasing as we speak.

Understand the geometric and statistical properties/nature of geospatial data. Learn the skills to operate common analysis of geometric properties and basic statistics in QGIS. Gain deeper understanding on the nature and possibilities & limitation of geospatial data.

Learn to apply data visualisation skills via a Data Visualisation Challenge, which is a real-world need-based competition, targeted to make geovisualisations with societal impacts.

9 hours Learn what geospatial data sets and open-source tools can be used to make geo-visualisations and digital maps. Know how to use open source GIS software and different geovisualisation tools for static and dynamic geodata visualisations and students know the opportunities and limitations related to these tools.

13 hours Learn the principles of geospatial data visualization and what elements form a good data visualization solution.

15 hours Learn principles of Spatial Data Infrastructures (SDIs) and practical skills in using SDI and sharing your own data via CRD Geonode.

10 hours Learn principles and practical skills to use metadata standards for good quality geospatial data management. After completing the module, you are able to use metadata standards based on ISO19115 and recommendations of the OSGEO, and you are skilled in creating and evaluating the quality of the data based on the metadata, as well