What is Spatial Data Science?

Spatial Data Science is a subset of Data Science that focuses on the unique characteristics of spatial data, moving beyond simply looking at where things happen to understand why they happen there. (CARTO, 2021)

The terminology for the field that conducts analytics with spatial data has had historically many names and varying definitions that have evolved over time as the technologies and the world around them has evolved. Sometimes these various definitions and naming conventions flying around in the international arenas can be quite confusing. Nevertheless, the core in most of them has always been the same: using a collection of concepts and methods drawn from geography, (spatial) statistics and computer science. These techniques deal with accessing, transforming, manipulating, visualizing, exploring and reasoning about data where the locational component is important.

The following presentation aims to clarify a bit of these definitions and introduce how data science has become part of the geographical analysis and how it is shaping the field. In addition, we will learn how spatial data science is a fundamental part of ambitions and research aiming to achieve a more sustainable world: