290002 PS Spatial Data Science (2022W)

This course will introduce students to Spatial Data Science as a "fourth paradigm" of science. We will also discuss the role of FAIR principles (findability, accessibility, interoperability, and reusability). The course will cover all stages from the initial conceptualization and representation of data to their creation, entry, and cleaning as well as their analysis, e.g., using clustering.

The course will start with foundational literature about different kinds of regions in geography and then introduce a novel, data-synthesis-based method to replicate the findings of these classical papers.

Topics will include introductory materials in knowledge representation, data engineering, geographic information retrieval, clustering, classification, and so on. We will also touch on several application areas, such as social sensing and place recommendations.

Students will then develop their own experiments (as a series of assignments) and present them during the class.