Fundamentals of Geospatial Data Science

Catalog description

Quantitative analysis and data-science skills are increasingly crucial for the study of geography. Emerging technologies, 'big data' and increased computational power have transformed our ability to understand patterns and relationships, enabling sophisticated analyses at the click of a button. However, given that basic knowledge about computing, statistics and data-science are rarely presented within a geographical context, it can be difficult to know where to begin when learning these advanced techniques, especially because the characteristics of space/time data make it easy to misunderstand results. This course is designed to bridge that gap, applying the fundamentals of programming and data analysis to real-world problems within geography. Its aim is to provide a technical foundation both for those progressing onto intermediate Geographic Information Science (GIS) courses, and also for those who wish to explore the fundamentals of data science within the context of people and place. The course begins by introducing data science, data management and programming best-practice, with a particular focus on the challenges posed by the complexities of space-time datasets. This is supported through practical experience using real-world examples and a variety of tools such as spreadsheets, GIS software and programming languages. As part of this process, students will gain practical experience in project workflow, finding and reading-in data, quality control, data analysis and visualization. Finally, each stage of the course is underpinned by discussion about key concepts in the geographies of data ethics, providing students with a space to critically assess the implications of their work, and to explore how advancements in data science might impact society.