FOSS4G - OSGeo in the browser: Advances in client-side WebAssembly-based Geospatial Analysis...

In-browser analytics have grown in popularity as personal computers and mobile devices have increased capabilities in CPU and GPU performance to handle and represent geospatial data. Efficient data transfer formats, in-memory analytics, and cheap static or serverless web infrastructures set the groundwork for robust client-side data handling, parsing, and visualization. Additionally, the ongoing development of WebAssembly libraries, a web technology to wrap and translate existing modules from C, Go, Rust, Python, Java, etc. into a JavaScript virtual machine with near-native performance, opens the door to integrate existing work into new web applications.

This talk outlines the infrastructure used in the US Covid Atlas project and the capacities of jsgeoda (Xun Li, CSDS) to perform a variety of clustering and binning algorithms in the browser. Code demonstrations for main thread and worker implementations will be presented, along with a series of template Github repositories available for use licensed under GPL. By the end of this talk, viewers will be able to understand and replicate the US Covid Atlas’s web infrastructure, implement a simple jsgeoda instance for spatial clustering, and build from open source templates for their own geospatial analytics web application that does not require backend services.

Building on the lessons learned through the US Covid Atlas project, the Center for Spatial Data Science is developing a series of easily replicable templates to create in-browser geospatial data exploration tools based on jsgeoda. This talk will outline the work so far and major infrastructure elements, then demonstrate how these templates can be utilized with a simple JSON configuration to read and join geospatial and tabular data, as well as generate normalized columns and define symbology options.

The US Covid Atlas project is headed up by Dr Marynia Kolak (CSDS), Dr Qinyun Lin (CSDS), and Dr Xun Li (CSDS). Dylan Halpern (Presenter, CSDS), is the Principal Software Engineer for the project.

Authors and Affiliations –
Kolak, Marynia (1)
Lin, Qinyun (1)
Li, Xun (1)
Halpern, Dylan (1)

(1) Center for Spatial Data Science, The University of Chicago

Requirements for the Attendees –
Attendees with a basic knowledge of web infrastructures and servers, and javascript/web mapping may find this talk most useful.

Track –
Use cases & applications

Topic –
Data visualization: spatial analysis, manipulation and visualization

Level –
1 - Principiants. No required specific knowledge is needed.

Language of the Presentation –
English