Speaker
Description
Abstract:
Spatial data are central to understanding environmental change, social processes, and their interactions. Maps are not only visual products of analysis, but tools that shape how problems are framed, how phenomena are perceived, and how decisions are made. R has become a widely used environment for spatial data science because it combines interactive analysis, open development, statistical rigor, and strong visualization within reproducible workflows.
This keynote will review the current state of spatial work in R, highlighting mature and interoperable tools, intuitive workflows, and available documentation and learning resources -- developments that support reliable and integrative spatial analysis across disciplines. It will then turn to what is still missing, pointing to methodological, technical, and community challenges that limit what can currently be done.
The keynote will also reflect on both the potential and the limits of current approaches, and on what they depend on in practice, including the availability of high-quality data and domain knowledge.
It will conclude by discussing how spatial methods act as integrators across fields, shifting the focus from tools to problems, and by considering how education, open-source practice, and emerging computational approaches may shape the future of spatial data analysis in R.
Bio:
Jakub Nowosad is an associate professor at Adam Mickiewicz University in Poznań and a visiting scientist at the University of Münster. He is a computational geographer working at the intersection of geocomputation and environmental science, where he develops spatial methods to understand complex environmental and ecological patterns and processes. He is a co-author of the Geocomputation with R book and an active contributor to the #rspatial and open-source geospatial communities. He works to make spatial data analysis more accessible and impactful for people working with spatial data.