BEGIN:VCALENDAR VERSION:2.0 PRODID:-//pretalx//talks.osgeo.org//foss4g-europe-2026//talk//FZELJW BEGIN:VTIMEZONE TZID:EET BEGIN:STANDARD DTSTART:20001029T050000 RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=10 TZNAME:EET TZOFFSETFROM:+0300 TZOFFSETTO:+0200 END:STANDARD BEGIN:DAYLIGHT DTSTART:20000326T040000 RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=3 TZNAME:EEST TZOFFSETFROM:+0200 TZOFFSETTO:+0300 END:DAYLIGHT END:VTIMEZONE BEGIN:VEVENT UID:pretalx-foss4g-europe-2026-FZELJW@talks.osgeo.org DTSTART;TZID=EET:20260629T150000 DTEND;TZID=EET:20260629T153000 DESCRIPTION:The gap between desktop GIS and browser-based mapping is closin g fast. WebGIS solutions are increasingly taking on tasks that previously required dedicated desktop environments\, such as complex analytical proce ssing\, on-the-fly integration of massive datasets\, and workflow automati on. While proprietary systems have provided monolithic solutions for these tasks\, the open-source ecosystem is now catching up with more flexible\, modular approaches. \n\nHere\, we introduce [GOAT](https://github.com/pla n4better/goat)\, a refactored WebGIS platform built to bring analytical pr ocessing to the browser using modern open-source technologies. Traditional ly\, spatial analysis workflows are fragmented. Data is found on web porta ls\, downloaded\, processed locally\, and eventually pushed back to a visu alization tool. GOAT is designed to consolidate this cycle. Users can sear ch and load data via built-in catalogs\, direct uploads\, or OGC services\ , and apply styling directly in the browser. Beyond basic mapping\, the ap plication provides spatial modules for travel-time calculations\, geostati stics\, and general geoprocessing. To support reproducibility\, processing steps can be chained together in an automated workflow builder. This allo ws users to rerun complex analyses when new data arrives or parameters cha nge\, and includes support for custom SQL queries. These workflows can als o be mapped to UI inputs on the map\, allowing non-technical users to exec ute spatial pipelines by adjusting parameters.\n\nOnce the analysis is don e\, results need to be shared. GOAT includes a layout engine for designing and exporting high-resolution map series and PDFs. A dashboard builder le ts users combine maps with charts and metrics. Because the dashboards rema in linked to the underlying data\, they update automatically when the data changes\, turning static reports into interactive tools.\n\nUnder the hoo d\, the project is freely available under the GPL-3.0 license and managed as a monorepo. The frontend relies on React.js\, Next.js\, and MapLibre GL JS\, communicating over modern OGC protocols (Tiles\, Features\, Processe s). All endpoints are built in Python with FastAPI\, following both OGC st andards for spatial services and the OpenAPI specification. \n\nFor geopro cessing and data management\, the FastAPI backend leverages Python and Pos tgreSQL/PostGIS. One of our recent architectural shifts is the implementat ion of DuckLake\, a framework that combines the storage efficiency of Parq uet files with the analytical speed of DuckDB\, alongside PostgreSQL for m etadata. Due to scaling issues with PostgreSQL/PostGIS on large datasets a nd growing volumes of user data\, we adopted this hybrid approach. Parquet files allow us to store and query large spatial datasets efficiently\, wh ile DuckDB provides the processing speed needed for analytical workloads. This structure enables data to be stored in comparatively cheap volume sto rage and easily backed up in S3-compatible object storage. \n\nFor serving data\, we implemented a hybrid vector tile architecture. We rely on stati c vector tiles generated by Tippecanoe for maximum rendering speed\, while dynamic vector tiles are created on the fly using DuckDB for filtered or edited datasets. In practice\, this means we can render and interact with millions of building footprints or land-use parcels directly in the browse r through pre-generated tiles\, yet still maintain the flexibility to requ est dynamic tiles when users modify data or apply filters. \n\nTo prevent large analytical queries from slowing down the application\, we adopted an asynchronous architecture using Windmill to orchestrate Python jobs in th e background. Long-running geospatial tasks are defined in a core library powered by Python and DuckDB. Each tool is wrapped as a standard OGC Proce ss\, making it accessible from both the frontend and external APIs. This d esign ensures that processes run in isolation\, meaning individual tools c an be scaled independently based on their specific resource demands. As a result\, users can chain multiple processing steps into background workflo ws and continue interacting with the map uninterrupted. Finally\, the enti re platform is Dockerized and deployed via Kubernetes to ensure robust sca ling in production. \n\nWe have also built dedicated data pipelines to ing est base data\, such as street networks from OpenStreetMap\, spatial featu res from Overture Maps\, and public transit schedules via GTFS. Active mob ility is handled by custom algorithms\, while public transport routing is powered by the open-source Nigiri engine (from MOTIS). This combination al lows users to run complex\, large-scale spatial queries like spatial inter sections\, identifying gaps in public transit networks\, or evaluating nat ionwide accessibility.\n\nIn this talk\, we will share the technical chall enges we faced and the architectural decisions we made while building GOAT . Although GOAT has been primarily developed by Plan4better\, a core goal of this presentation is to encourage participation from the wider open-sou rce geospatial community. Alongside a live demo\, we will discuss practica l use cases in Germany. Finally\, we will touch on our latest technical ex periments\, such as integrating locally hosted open-weight LLMs to help us ers query spatial data via plain text\, and outline our roadmap for deeper integration with existing open-source GIS tools like QGIS. DTSTAMP:20260605T010941Z LOCATION:Auditorium SUMMARY:Presenting the novel analytical WebGIS GOAT - Elias Pajares URL:https://talks.osgeo.org/foss4g-europe-2026/talk/FZELJW/ END:VEVENT END:VCALENDAR