Speaker
Description
The Spatial Data Science across Languages (SDSL) Community brings together developers and users of common and emerging programming languages for spatial data science. It aims to foster understanding and address common issues while discussing language-specific problems. We focus broadly on geospatial and geographic space, with some applications to general image spaces and local reference frames ranging from microscopic to astronomical scales.
Open-source programming languages commonly used in spatial data science include R, Python, and Julia. Our community is also interested in JavaScript and TypeScript, C++ and Rust. These languages are used by millions of users daily to solve spatial problems. We face challenges beyond particular programming languages, such as the interpretation of underlying data, the representation of data in computers, visualisation, the scalability and efficiency of implementations, the use of upstream libraries such as GDAL, GEOS, and PROJ, GIS interfaces, software distribution, and open-source software community building. The r-spatial community is committed to investigating these cross-language challenges posed by SDSL.
Our main activity since 2023 has been a series of annual workshops organised across different parts of Europe that provide a space to bridge programming-language communities and establish cross-language interaction between developers and users. In 2026, we established the Lorena Abad Crespo Award for Innovation in Spatial Data Science, to be awarded annually to individuals who have made significant contributions to open spatial data science. It honours those who have pushed the boundaries of open source software for SDS and offered their ideas, transformed into tools, to the wider community.
If you used AI tools or services to support the preparation of this submission, please state the name and reason for using each of them.
No AI tools/services were used.
Additional Material or Paper
Community website: https://spatial-data-science.github.io/
| Keywords: Please list up to 5 keywords to help us find the right session for your contribution. | spatial data science, geospatial data, cross-language, r-spatial |
|---|---|
| Virtual Option | This submission is for onsite presentation only |
| Video Recording | Video sharing is fine |
| The author(s) agree(s) to take responsibility and be accountable for the contents of the submission and is/are authorized to present it. | Confirm |