POSE: Phase II: An Open Source Ecosystem for Spatial Data Science

This project is funded by Pathways to Enable Open-Source Ecosystems (POSE) Program which seeks to harness the power of open-source development for the creation of new technology solutions to problems of national and societal importance. In today’s rapidly evoving world, it is important to understand location data as related to complex societal issues. From urban planning and environmental management to public health and economic development, spatial data science stands at the forefront of decision-making processes, enabling the visualization and analysis of data in ways that reveal relationships, patterns, and trends across various geographies.

This project, spearheaded by an interdisciplinary team at the San Diego State University in collaboration with the University of Chicago, the University of Maryland, and the University of North Texas, aims to improve the field of spatial data science through the development and enhancement of the Python Spatial Analysis Library (PySAL) open-source ecosystem. With a focus on expanding accessibility, functionality, and collaborative potential, the initiative is poised to democratize spatial data analysis, making powerful tools available to researchers, policymakers, and the public. The project’s dedication to open-source principles fosters innovation and ensures that advancements in spatial data science are shared freely, promoting transparency and inclusivity in research and application.