This presentation introduces the pg_featureserv program. It is lightweight, written in Go, and is used to publish vector data from PostGIS databases using the OGC API features standard. First, the main features of pg_featureserv are presented, including installation and setup.

Special attention is given to the tool's numerous filter functions, which allow precise and efficient queries of spatial data. The usage of these functions is explained with examples.

In addition, the OGC API Features standard is presented as an alternative to the traditional WFS for publishing spatial data. The differences between the two approaches are explained and the advantages of the new standard are highlighted.

This presentation describes the functionalities and integration of QGIS Server with a focus which features we are using in our company. A particular strength of QGIS Server lies in its ability to display geodata on the web in the same way as it is visible in QGIS Desktop. This is particularly relevant if an extensive selection of different map styles based on QGIS is available. The QGIS Server is configured exclusively via a QGIS project, which makes it very easy to set up. However, it should be noted that no automated settings are currently possible, for example via API.

The QGIS Server supports various OGC standards, including WMS (Web Map Service), WFS (Web Feature Service), WCS (Web Coverage Service) and WMTS (Web Map Tile Service). In addition, it offers a prototype implementation of OAF (OGC API - Features) and integrates many features of QGIS, including the export of maps prepared in the desktop.

This presentation will also cover the installation of QGIS Server using Docker. Furthermore, the integration of QGIS Server into middleware solutions will be discussed to enable its use in complex GIS environments.

Another focus will be on the configuration of published layers and the selection of published attributes. We will also discuss how to store projects in a database and how to connect to the database using PG_SERVICE files.

For developing geospatial applications often some sample data of a specific region is needed. This lightning talks presents a web application that allows to create random vector data of a required extent. The data can be exported as GeoJSON or Shapefile and runs completely in the browser without any connection to a backend. The application itself is created with Vue.js and OpenLayers. The source code and the website are freely available.

The programming language Go has established itself in various IT areas. This lightning talk offers a brief overview of Go with a focus on the existing ecosystem for processing geodata.

Go is known for its speed and accessibility. Numerous geospatial projects like pg_featureserv, pg_tileserv, and tegola already make use of Go. This presentation showcases additional tools and libraries in this language.

DuckDB has established itself in the data science community as a lightweight tool for data analysis of all kinds. It now has an official extension that can work with geospatial data. In this talk we will introduce the basic features.

DuckDB can read data from various sources, such as files (CSV, JSON, ...), the Internet or other databases. The imported data can be combined and processed using SQL. The "spatial" extension of DuckDB now also supports spatial data types such as points, lines or polygons. In addition, the GEOS library integrated in the background provides geographic analysis functions such as area calculation, intersection or buffer calculation. GDAL is also integrated in the background and allows reading and writing of many other formats from the geographic world.

There are many ways to include an OpenLayers map into a Vue web application. This presentation will explore a few techniques such as vue3-openlayers, vue-ol-comp, and Wegue. The primary emphasis is on how the state of the OpenLayers map and its layers can be reactively accessed across all components of the web application.