Stuart Lynn
Stuart Lynn is a Research Director and Senior Principal Software Engineer at the Center for Spatial Data Science at University of Chicago. His interests include widening the participation in scientific discussion and inquiry to non-traditional communities through the development of tools and active participation in citizen science and collaborative processes. He holds a Master in Mathematical Physics and a PHD in Astrophysics from the University of Edinburgh. In previous roles he has worked with non-profits and NGOs with the Two Sigma Data Clinic, lead the Data Science team at CARTO and was the technical lead for the citizen science platform The Zooniverse.
Sessions
Geospatial data and analysis is more central than ever to data science, research, and policy analyses. This is especially evident in the explosion of tools, both open source and proprietary that have been developed over the past 5 years to help users manage and gather insights from their data. However many of these powerful tools, like geopandas (analysis and modeling) and deck.gl (visualization)— are technically inaccessible to analysts and researchers without the available time or skills for advanced coding. A number of commercial ventures (Carto, ESRI etc) attempt to overcome this limitation by bringing these tools together as part of polished, graphical user interface driven platforms. While these platforms offer ease of use, they raise concerns about longevity, data ownership, and academic support.
Matico is a new free and open-source platform we are developing at the Spatial Data Science center that seeks to fill the gap between open but technically focused tools and commercial platforms. Consisting of a suite of interoperable components, Matico enables organizations and individuals to manage and visualize their geospatial data while easily maintaining their own infrastructure. A backend server allows users to easily load, clean, analyze, and distribute data through APIs, queries, and in-browser data editing tools while a powerful app builder allows users to develop their own rich applications that target diverse audiences.
This talk will demonstrate the current features of Matico, our future roadmap , and demonstrate relevant use cases. Matico is now and will forever be open through a permissive MIT open-source license. Learn more at https://matico.app/
The proliferation of client-side analytics and on-going vulnerabilities with shared code libraries have fueled the need for better safety standards for running executables from potentially unknown sources. WebAssembly (WASM), a compilation target that allows lower-level languages like Rust, C, and Go to run in the browser or server-side at near-native speeds. Much like Docker changed the way we run virtualized workflows, WASM runtimes create safe virtual environments where access to the host system is limited.
In combination with a new free and open source full-stack geospatial platform, Matico, efforts are underway to enable portability across workflows and applications to more easily use WASM modules. WASM implementations of GDAL are in the works, and powerful open source Rust geospatial libraries are easily packaged for web usage through Wasm-Pack. Additional geo WASM libraries like jsgeoda provide spatial indices, binning, and autocorrelation functions. Shareable code can be a recipe for security vulnerabilities and attack vectors, potentially exposing personal or critical information, particularly if there is the opportunity to run code server-side. WASM implementation alleviates this by requiring access from the Virtual Machine (VM) to be limited and explicit, and for Javascript developers the lightweight AssemblyScript language is relatively familiar.
An upcoming Javascript feature called ShadowRealms may enable even simpler and more familiar implementations to safely run Javascript code shared between module authors. These developments lay the groundwork for a hybrid front- and backend geospatial ecosystem of shareable code snippets and analytic functions, much like have emerged in the UI component Javascript ecosystem. The combination of emerging features positions web geospatial analytics and This talk explores the implementation and performance of running geospatial analytic modules through a WebAssembly virtual machine and through the upcoming Javascript ShadowRealm specification.