This scientific meeting aims to bring together scientists holding a solid experience in the broad field of spatial data science. The main objective is to share their vision and initiate a dialogue about the different issues we face when performing and developing innovative methodologies of data mining, analysis, modelling and visualisation for spatial systems.
The main theoretical topics include, but are not limited to, three principal axis:
- Spatial statistical methods using a strong statistical/mathematical framework, especially focused on the quality of formalism of the method;
- Geovisualisation, with a major accent on visual and computational data mining techniques focused on high-dimensional attributes;
- Pattern recognition and modelling with special emphasis on approaches based on data-mining machine learning;
We welcome applications related to environmental science, especially focused on natural and anthropogenic hazard, natural resources, but also to socio-economic science if characterized by the spatial dimension of the data.
Complementary one-day short courses will be offered in the direct connection with the SDS2020 main event. It is foreseen that participants will do practical exercises using different software tools including open source packages (QGIS, GRASS, Python and R).