Beschreibung:
As a PhD candidate and research within OpenGeoHub Foundation, Carmelo focuses on data science projects such as GeoHarmonizer and the MOOD H2020 project. During the 2023 MOOD Summer School, he gave a session on covariates data for SDM. The goal of this lecture was to learn how to select and explore the variables to include in predictive models. By the end of the lecture, the students learned how to search for additional datasets in literature and open repositories, how to select the proper variables based on the topic of their research and how to conduct exploratory analysis of messy datasets. They finally learned how to prepare a dataset ready for modeling by including information coming from their response variable (treated in the previous lecture) and the predictive variables. Please find the link to the material here https://drive.google.com/drive/folders/1Ec7pjdyY_FBqt3B0aY49qthiLunMoTAx?usp=sharing