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In computing, GeoServer is an open-source server written in Java that allows users to share, process and edit geospatial data. Designed for interoperability, it publishes data from any major spatial data source using open standards .
Versions 2.0.0, 2.0.1 and 2.0.2 are subtly different, and different vendors implement them with variations. [5] Typically a CSW server will accept requests in one CSW version only, and it is up to the client to be flexible. e.g. ESRI Geoportal can be configured to harvest documents from CSW servers of a variety of versions and vendor variants [6] such as "GeoNetwork CSW 2.0.2 APISO".
Written in Scala, GeoMesa is capable of ingesting, indexing, and querying billions of geometry features using a highly parallelized index scheme. GeoMesa builds on top of open source geo (OSG) libraries. It implements the GeoTools DataStore interface providing standardized access to feature collections as well as implementing a GeoServer plugin.
QGIS is a geographic information system (GIS) software that is free and open-source. [2] QGIS supports Windows, macOS, and Linux. [3] It supports viewing, editing, printing, and analysis of geospatial data in a range of data formats.
MapServer is an open-source development environment for building spatially enabled internet applications, built in the C language, and is widely known as one of the fastest Web mapping engines available.
A spatial data infrastructure (SDI), also called geospatial data infrastructure, [1] is a data infrastructure implementing a framework of geographic data, metadata, users and tools that are interactively connected in order to use spatial data in an efficient and flexible way.
DescribeLayer – returns the feature types of the specified layer or layers, which can be further described using WFS or WCS requests. This request is dependent on the Styled Layer Descriptor (SLD) Profile of WMS. [12] GetLegendGraphic – returns an image of the map's legend image, giving a visual guide to map elements.
GPlates also supports integration with GeoServer and PostGIS databases. By incorporating this technology stack, GPlates simplifies and streamlines data processing, integration, analysis, and visualisation to ease the workload for geoscientists.