index.qmd

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# title: "Spatial Data Science across Languages Community"
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![](img/sdsl-logo.svg)

The Spatial Data Science across Languages Community brings together developers and
users from the common and emerging programming languages used for spatial data
science.

Spatial data science (SDS) concerns the analysis of spatial data in various contexts.
We focus broadly on geospatial and geographic space, with some applications to general
image spaces, local reference frames - everything from microscopical to astronomical space.

Open source programming languages commonly used in spatial data science for
analysis include Python, R and Julia. Our community is also interested in
JavaScript and TypeScript, C++ and Rust. These languages are used by millions of
users on a daily basis to solve spatial data problems, visualise and analyse
spatial data.

A number of the challenges that we face transcend the particular programming
languages. Such challenges range from: the interpretation of the underlying
data; the way the data are represented in computers; visualisation; scalability
and efficiency of implementations; the use of upstream libraries like GDAL, GEOS
and PROJ, GIS interfaces; software distribution; and open source software
community building.

The **Spatial Data Science Across Languages Community** aims to bring developers
and users together to help build understanding and solve common problems, as
well as discussing problems specific to particular language communities.



## Annual Workshop

Our main activity since 2023 has been a series of annual workshops, which
provide a space for bridging the various programming-language communities and
establishing cross-language interaction between developers and users.

[More details about our workshops](/workshops.html)

## Discord

SDSL has a Discord server for discussions and communication during the
workshops. Please join via <https://discord.gg/HJRKEJsmrr>.