From d13b7bd63daf4f3de67ddabbdeb12537694d8c1b Mon Sep 17 00:00:00 2001 From: Quarto GHA Workflow Runner Date: Mon, 13 Nov 2023 15:39:39 +0000 Subject: [PATCH] Built site for gh-pages --- .nojekyll | 2 +- cookbook/deegree.html | 8 +-- search.json | 2 +- sitemap.xml | 134 +++++++++++++++++++++--------------------- 4 files changed, 73 insertions(+), 73 deletions(-) diff --git a/.nojekyll b/.nojekyll index 61677ca..43c7be3 100644 --- a/.nojekyll +++ b/.nojekyll @@ -1 +1 @@ -4732889d \ No newline at end of file +d9a76229 \ No newline at end of file diff --git a/cookbook/deegree.html b/cookbook/deegree.html index 524c365..28d460d 100644 --- a/cookbook/deegree.html +++ b/cookbook/deegree.html @@ -207,7 +207,7 @@

Step

Latest minor version

docker pull deegree/deegree3-docker:3.5

Specific version (example)

-
docker pull deegree/deegree3-docker:3.5.2
+
docker pull deegree/deegree3-docker:3.5.3

Info: All available images of deegree version 3.5.x are built with Apache Tomcat 9.x and OpenJDK 11. Check the deegree Docker Hub project for details and other deegree versions available.

@@ -223,11 +223,11 @@

Step 2: S

Step 3: Set up the local deegree docker container

Simple configuration (recommended for beginners)

-
docker run --name deegree_inspire_soil --network="inspiresoil" -d -p 8080:8080 deegree/deegree3-docker
+
docker run --name deegree_inspire_soil --network="inspiresoilnetwork" -d -p 8080:8080 deegree/deegree3-docker

or with a specific version:

-
docker run --name deegree_inspire_soil --network="inspiresoil" -d -p 8080:8080 deegree/deegree3-docker:3.5.2
+
docker run --name deegree_inspire_soil --network="inspiresoilnetwork" -d -p 8080:8080 deegree/deegree3-docker:3.5.3

Advanced configuration

-
docker run --name deegree_inspire_soil --network="inspiresoilnetwork" -v /path/to/.deegree:/root/.deegree -d -p 8080:8080 deegree/deegree3-docker:3.5.2
+
docker run --name deegree_inspire_soil --network="inspiresoilnetwork" -v /path/to/.deegree:/root/.deegree -d -p 8080:8080 deegree/deegree3-docker:3.5.3

Tip: Using the docker parameter -v (volume), all prior created deegree workspaces that are stored in /path/to/.deegree can be accessed.

diff --git a/search.json b/search.json index 698b565..53cbcce 100644 --- a/search.json +++ b/search.json @@ -522,7 +522,7 @@ "href": "cookbook/deegree.html", "title": "deegree", "section": "", - "text": "deegree is an open source java server implementation of WMS, WMTS, CSW, WCS, WFS, WPS.\nThis cookbook gives step-by-step instructions on the deegree WFS setup for serving rich GML data, in this case an INSPIRE soil data set.\nThere are two options in which deegree can be used to publish rich GML data.\n\nUsing a relational database and a mapping configuration to generate the GML\nUsing a blob storage to provide individual features without any processing\n\nThe second approach is easy to setup and efficient when users request full datasets. However, it may still be problematic if users use advanced filters to select subsets of the chosen dataset.\n\n\n\nGet started with deegree\nStart a deegree instance locally using the Docker Hub image:\n\nStep 1: Pull the desired docker image\nLatest minor version\ndocker pull deegree/deegree3-docker:3.5\nSpecific version (example)\ndocker pull deegree/deegree3-docker:3.5.2\n\nInfo: All available images of deegree version 3.5.x are built with Apache Tomcat 9.x and OpenJDK 11. Check the deegree Docker Hub project for details and other deegree versions available.\n\n\n\nStep 2: Set up the docker network:\ndocker network\ndocker network create -d bridge inspiresoilnetwork\n\nInfo: A Docker network is a virtual network that allows containers to communicate with each other and with external networks.\n\n\n\nStep 3: Set up the local deegree docker container\nSimple configuration (recommended for beginners)\ndocker run --name deegree_inspire_soil --network=\"inspiresoil\" -d -p 8080:8080 deegree/deegree3-docker\nor with a specific version:\ndocker run --name deegree_inspire_soil --network=\"inspiresoil\" -d -p 8080:8080 deegree/deegree3-docker:3.5.2\nAdvanced configuration\ndocker run --name deegree_inspire_soil --network=\"inspiresoilnetwork\" -v /path/to/.deegree:/root/.deegree -d -p 8080:8080 deegree/deegree3-docker:3.5.2\n\nTip: Using the docker parameter -v (volume), all prior created deegree workspaces that are stored in /path/to/.deegree can be accessed.\n\nAfter an intial startup time, the deegree web console can be accessed under http://localhost:8080/deegree-webservices.\nThe deegree documentation contains a detailed quick start on how to import and operate a sample workspace.\n\n\n\nThe deegree GML tools CLI\nThe generation of SQL DDL scripts, deegree SQLFeatureStore configuration files from GML application schemas and import of GML data in a deegree SQLFeatureStore is managed via command line interface (CLI) tools.\nThe usage instructions of each CLI tool can be printed via:\ndocker exec -w /opt deegree_inspire_soil java -jar deegree-tools-gml.jar SqlFeatureStoreConfigCreator -h \nor\ndocker exec -w /opt deegree_inspire_soil java -jar deegree-tools-gml.jar GmlLoader -h\n\nTip: Instead of the parameter -h, -help or -? can be used as well.\n\nThe GML tools CLIs are described in further detail in the deegree documentation.\n\n\nExample workflow\nThe above mentioned GML tools must be executed in the following order:\n\nSqlFeatureStoreConfigCreator\nGmlLoader\n\nThe following example workflow is based on this INSPIRE soil dataset:\n\nhttps://fbinter.stadt-berlin.de/fb/atom/SO/SO_BoKw2015.zip\n\nDescription of the dataset (german-only):\n\nhttps://fbinter.stadt-berlin.de/fb_daten/beschreibung/SO_BoKw2015.html\n\n\nAttention: The example workflow makes use of the docker exec command, which can only be performed on an already existing docker container. Therefore, the completion of the previous chapter “Get started with deegree” is necessary to proceed further.\n\n\nStep 1: Using the deegree SqlFeatureStoreConfigCreator\nIn the following, the SqlFeatureStoreConfigCreator is used to create a SQL DDL statement that creates a database schema as well as a deegree SQLFeatureStore configuration of the INSPIRE soil schema.\ndocker exec -w /opt deegree_inspire_soil java -jar deegree-tools-gml.jar SqlFeatureStoreConfigCreator -format=all -idtype=uuid -mapping=relational -dialect=postgis -schemaUrl=https://inspire.ec.europa.eu/schemas/so/4.0/Soil.xsd\nIf run successfully, the SqlFeatureStoreConfigCreator will generate the SQL DDL statement as Soil.sql and the SQLFeatureStore configuration as Soil.xml.\n\nTip: The results reside in the directory /opt of the docker container and should be copied into the local filesystem in order to be accessed easily using following docker command: docker cp deegree_inspire_soil:/opt/Soil.xml /destination.\n\n\n\nStep 2: Creating a database\nTo use the previously generated Soil.sql, a database needs to be created. For this example a docker container with a PostgreSQL image (version 12) and the PostGIS extension (version 3.2) is created:\ndocker run --name postgis_inspire_soil --network=\"inspiresoilnetwork\" -d -p 5432:5432 -e POSTGRES_PASSWORD=postgres -e POSTGRES_USER=postgres -v /destination/Soil.sql:/ postgis/postgis:12-3.2\n\nInfo: The SQL DDL file Soil.sql is mounted onto the container by using the previously mentioned docker run parameter -v. This way, the file does not have to be copied onto the container after its creation.\n\nIn the next step, the database is established and the SQL DDL statement loaded into it using psql:\ndocker exec -it postgis_inspire_soil psql -U postgres -c 'CREATE DATABASE inspire_soil;' -c '\\c inspire_soil' -c 'CREATE EXTENSION postgis;' -f /Soil.sql\n\n\nStep 3: Configuration of the deegree workspace\nFor beginners, the easiest way to configure deegree is via the web console at\n\nhttp://localhost:8080/deegree-webservices.\n\n\nCreate a deegree workspace\n\n\nIn the web console, create a new workspace under\n\ngeneral > workspaces > Create a new workspace\n\nFor this example the workspace is called 'inspire_soil'. After creation, the workspace should appear under:\n\nAvailable workspaces.\n\nThen start the created workspace.\n\n\nCreate a SQL database connection\n\n\nCreate a new SQL database connection under\n\nconnections > databases > Create new.\n\nChoose an identifier, for example 'inspire_soil_db' and select type DataSource (preferred) with XML config example PostgreSQL (minimal) and click Create new.\nThe URL in the XML template needs to be adjusted according to the previously created PostgreSQL docker container as well as the database 'inspire_soil'. The set URL should look like this \"jdbc:postgresql://postgis_inspire_soil:5432/inspire_soil\". The previously chosen password and username also need to be adjusted. Click the button save to save your changes to the XML template.\n\n\nInfo: Since both, the deegree and PostgreSQL docker container, are in the same network, you can use the name of the PostgreSQL docker container as hostname.\n\n\nCreate a SQLFeatureStore\n\n\nCreate a new SQLFeatureStore under\n\ndata stores > feature > Create new.\n\nChoose an identifier, for example 'inspire_soil_fs' and select type SQL with XML config example minimal and click Create new.\nIn the XML editor, delete the existing content (CTRL+A, DEL).\nNext, open the in step 1 created file Soil.xml and select all of its content (CTRL+A, CTRL+C), then paste the content into the XML editor (CRTL+V).\nThe only change necessary is to use the individual identifier of the SQL database connection, which you set in step 2. For example <JDBCConnId>inspire_soil_db</JDBCConnId>. Click the button save to save your changes to the XML template.\n\n\n\nIn some cases, as in this example, the FIDMapping prefix of certain FeatureTypes needs to be adjusted manually.\nIn this example, the following FIDMapping prefix changes need to be made to the Soil.xml file to match those in the database schema (Soil.sql):\n\n“OMPR_PROCESS_” to “Process_”\n“SO_DERIVEDSOILPROFILE_” to “DerivedSoilProfile_”\n“SO_SOILBODY_” to “SoilBody_”\n“SO_SOILLAYER_” to “SoilLayer_”\n\n\n\nInfo: Alternatively, you can also copy the Soil.xml directly into the workspace with i.e.: docker cp Soil.xml deegree_inspire_soil:/root/.deegree/inspire_soil/datasources/feature/. Remember, that the above mentioned changes (identifier feature store and database connection) still need to be applied.\n\n\nCreate a Web Feature Service (WFS)\n\n\nCreate a new WFS under\n\nweb services > services > Create new.\n\nChoose an identifier, for example 'inspire_soil_wfs' and select service type WFS with XML config example complex and click Create new.\nNext, change the FeatureStoreId to the identifier set in step 3. For example <FeatureStoreId>inspire_soil_fs</FeatureStoreId>. Click the button save to save your changes to the XML template.\n\n\nReload the deegree workspace\n\n\nOnce the previous steps 1-4 are completed, reload your deegree workspace by clicking the button [Reload]. The button is located at top of the web console interface, right next to your active workspace.\n\nIf your configuration is valid, there should be no red exclemation visible on the web console interface.\n\n\nThis concludes the basic configuration of the deegree workspace.\n\n\nStep 4: Using the deegree GmlLoader\nAfter downloading and extracting the dataset mentioned at the beginning of this example workflow, the file Soil.gml needs to be copied onto the previously created deegree docker container using the following docker command:\ndocker cp path/to/Soil.gml deegree_inspire_soil:/\nLastly, the GmlLoader can be started using the following parameters:\ndocker exec -w /opt deegree_inspire_soil java -Xmx16g -jar deegree-tools-gml.jar GmlLoader -pathToFile=/Soil.gml -workspaceName=inspire_soil -sqlFeatureStoreId=inspire_soil_fs -disabledResources=https://inspire.ec.europa.eu/codelist/\n\nInfo: Setting the Java parameter -Xmx16g (value dependant on the resources provided) is highly advisable, to avoid an Java OutOfMemoryError. Further information regarding the parameters of the GmlLoader can be found in the deegree documentation.\n\n\nAttention: The deegree GmlLoader takes around 21 hours to run, since the dataset used in this example is quite large (854,2 MB).\n\nAfter the GmlLoader has run successfully, open the capabilities of the WFS configured in step 3 configured WFS under\n\nweb services > services > inspire_soil_wfs > capabilities.\n\nThe capabilties are also directly accessible at the following address:\n\nhttp://localhost:8080/deegree-webservices/services/inspire_soil_wfs?service=WFS&request=GetCapabilities\n\nLastly, QGIS or any other GIS can be connected the WFS resource. Multiple layers should be visible. Import the layer with the name SoilBody to the layer panel. The visualisation should be similar to the following screenshot:\n\n\n\nVisualisation of the deegree WFS data in QGIS\n\n\nAlternatively, you can prepare a GetFeature request to extract a sample of the data available through the configured WFS. For example:\n\nhttp://localhost:8080/deegree-webservices/services/inspire_soil_wfs?service=WFS&request=GetFeature&version=2.0.0&typeNames=so:SoilBody&count=10\n\n\n\n\nFeatured implementations\nSome implementations of INSPIRE soil data services based on deegree:\n\nBaden Württemberg, Germany\nBrandenburg, Germany\n\n\n\nRead more\ndeegree is maintained by the company lat-lon, among others\n\nWebsite: http://www.deegree.org/\nDocumentation: https://download.deegree.org/documentation/current/html/\nDownload: https://www.deegree.org/download/\nDocker: https://hub.docker.com/r/deegree/deegree3-docker/\nINSPIRE Data Specification on Soil: https://inspire.ec.europa.eu/Themes/127/2892\n\nContributions to the deegree open source project are always welcome!" + "text": "deegree is an open source java server implementation of WMS, WMTS, CSW, WCS, WFS, WPS.\nThis cookbook gives step-by-step instructions on the deegree WFS setup for serving rich GML data, in this case an INSPIRE soil data set.\nThere are two options in which deegree can be used to publish rich GML data.\n\nUsing a relational database and a mapping configuration to generate the GML\nUsing a blob storage to provide individual features without any processing\n\nThe second approach is easy to setup and efficient when users request full datasets. However, it may still be problematic if users use advanced filters to select subsets of the chosen dataset.\n\n\n\nGet started with deegree\nStart a deegree instance locally using the Docker Hub image:\n\nStep 1: Pull the desired docker image\nLatest minor version\ndocker pull deegree/deegree3-docker:3.5\nSpecific version (example)\ndocker pull deegree/deegree3-docker:3.5.3\n\nInfo: All available images of deegree version 3.5.x are built with Apache Tomcat 9.x and OpenJDK 11. Check the deegree Docker Hub project for details and other deegree versions available.\n\n\n\nStep 2: Set up the docker network:\ndocker network\ndocker network create -d bridge inspiresoilnetwork\n\nInfo: A Docker network is a virtual network that allows containers to communicate with each other and with external networks.\n\n\n\nStep 3: Set up the local deegree docker container\nSimple configuration (recommended for beginners)\ndocker run --name deegree_inspire_soil --network=\"inspiresoilnetwork\" -d -p 8080:8080 deegree/deegree3-docker\nor with a specific version:\ndocker run --name deegree_inspire_soil --network=\"inspiresoilnetwork\" -d -p 8080:8080 deegree/deegree3-docker:3.5.3\nAdvanced configuration\ndocker run --name deegree_inspire_soil --network=\"inspiresoilnetwork\" -v /path/to/.deegree:/root/.deegree -d -p 8080:8080 deegree/deegree3-docker:3.5.3\n\nTip: Using the docker parameter -v (volume), all prior created deegree workspaces that are stored in /path/to/.deegree can be accessed.\n\nAfter an intial startup time, the deegree web console can be accessed under http://localhost:8080/deegree-webservices.\nThe deegree documentation contains a detailed quick start on how to import and operate a sample workspace.\n\n\n\nThe deegree GML tools CLI\nThe generation of SQL DDL scripts, deegree SQLFeatureStore configuration files from GML application schemas and import of GML data in a deegree SQLFeatureStore is managed via command line interface (CLI) tools.\nThe usage instructions of each CLI tool can be printed via:\ndocker exec -w /opt deegree_inspire_soil java -jar deegree-tools-gml.jar SqlFeatureStoreConfigCreator -h \nor\ndocker exec -w /opt deegree_inspire_soil java -jar deegree-tools-gml.jar GmlLoader -h\n\nTip: Instead of the parameter -h, -help or -? can be used as well.\n\nThe GML tools CLIs are described in further detail in the deegree documentation.\n\n\nExample workflow\nThe above mentioned GML tools must be executed in the following order:\n\nSqlFeatureStoreConfigCreator\nGmlLoader\n\nThe following example workflow is based on this INSPIRE soil dataset:\n\nhttps://fbinter.stadt-berlin.de/fb/atom/SO/SO_BoKw2015.zip\n\nDescription of the dataset (german-only):\n\nhttps://fbinter.stadt-berlin.de/fb_daten/beschreibung/SO_BoKw2015.html\n\n\nAttention: The example workflow makes use of the docker exec command, which can only be performed on an already existing docker container. Therefore, the completion of the previous chapter “Get started with deegree” is necessary to proceed further.\n\n\nStep 1: Using the deegree SqlFeatureStoreConfigCreator\nIn the following, the SqlFeatureStoreConfigCreator is used to create a SQL DDL statement that creates a database schema as well as a deegree SQLFeatureStore configuration of the INSPIRE soil schema.\ndocker exec -w /opt deegree_inspire_soil java -jar deegree-tools-gml.jar SqlFeatureStoreConfigCreator -format=all -idtype=uuid -mapping=relational -dialect=postgis -schemaUrl=https://inspire.ec.europa.eu/schemas/so/4.0/Soil.xsd\nIf run successfully, the SqlFeatureStoreConfigCreator will generate the SQL DDL statement as Soil.sql and the SQLFeatureStore configuration as Soil.xml.\n\nTip: The results reside in the directory /opt of the docker container and should be copied into the local filesystem in order to be accessed easily using following docker command: docker cp deegree_inspire_soil:/opt/Soil.xml /destination.\n\n\n\nStep 2: Creating a database\nTo use the previously generated Soil.sql, a database needs to be created. For this example a docker container with a PostgreSQL image (version 12) and the PostGIS extension (version 3.2) is created:\ndocker run --name postgis_inspire_soil --network=\"inspiresoilnetwork\" -d -p 5432:5432 -e POSTGRES_PASSWORD=postgres -e POSTGRES_USER=postgres -v /destination/Soil.sql:/ postgis/postgis:12-3.2\n\nInfo: The SQL DDL file Soil.sql is mounted onto the container by using the previously mentioned docker run parameter -v. This way, the file does not have to be copied onto the container after its creation.\n\nIn the next step, the database is established and the SQL DDL statement loaded into it using psql:\ndocker exec -it postgis_inspire_soil psql -U postgres -c 'CREATE DATABASE inspire_soil;' -c '\\c inspire_soil' -c 'CREATE EXTENSION postgis;' -f /Soil.sql\n\n\nStep 3: Configuration of the deegree workspace\nFor beginners, the easiest way to configure deegree is via the web console at\n\nhttp://localhost:8080/deegree-webservices.\n\n\nCreate a deegree workspace\n\n\nIn the web console, create a new workspace under\n\ngeneral > workspaces > Create a new workspace\n\nFor this example the workspace is called 'inspire_soil'. After creation, the workspace should appear under:\n\nAvailable workspaces.\n\nThen start the created workspace.\n\n\nCreate a SQL database connection\n\n\nCreate a new SQL database connection under\n\nconnections > databases > Create new.\n\nChoose an identifier, for example 'inspire_soil_db' and select type DataSource (preferred) with XML config example PostgreSQL (minimal) and click Create new.\nThe URL in the XML template needs to be adjusted according to the previously created PostgreSQL docker container as well as the database 'inspire_soil'. The set URL should look like this \"jdbc:postgresql://postgis_inspire_soil:5432/inspire_soil\". The previously chosen password and username also need to be adjusted. Click the button save to save your changes to the XML template.\n\n\nInfo: Since both, the deegree and PostgreSQL docker container, are in the same network, you can use the name of the PostgreSQL docker container as hostname.\n\n\nCreate a SQLFeatureStore\n\n\nCreate a new SQLFeatureStore under\n\ndata stores > feature > Create new.\n\nChoose an identifier, for example 'inspire_soil_fs' and select type SQL with XML config example minimal and click Create new.\nIn the XML editor, delete the existing content (CTRL+A, DEL).\nNext, open the in step 1 created file Soil.xml and select all of its content (CTRL+A, CTRL+C), then paste the content into the XML editor (CRTL+V).\nThe only change necessary is to use the individual identifier of the SQL database connection, which you set in step 2. For example <JDBCConnId>inspire_soil_db</JDBCConnId>. Click the button save to save your changes to the XML template.\n\n\n\nIn some cases, as in this example, the FIDMapping prefix of certain FeatureTypes needs to be adjusted manually.\nIn this example, the following FIDMapping prefix changes need to be made to the Soil.xml file to match those in the database schema (Soil.sql):\n\n“OMPR_PROCESS_” to “Process_”\n“SO_DERIVEDSOILPROFILE_” to “DerivedSoilProfile_”\n“SO_SOILBODY_” to “SoilBody_”\n“SO_SOILLAYER_” to “SoilLayer_”\n\n\n\nInfo: Alternatively, you can also copy the Soil.xml directly into the workspace with i.e.: docker cp Soil.xml deegree_inspire_soil:/root/.deegree/inspire_soil/datasources/feature/. Remember, that the above mentioned changes (identifier feature store and database connection) still need to be applied.\n\n\nCreate a Web Feature Service (WFS)\n\n\nCreate a new WFS under\n\nweb services > services > Create new.\n\nChoose an identifier, for example 'inspire_soil_wfs' and select service type WFS with XML config example complex and click Create new.\nNext, change the FeatureStoreId to the identifier set in step 3. For example <FeatureStoreId>inspire_soil_fs</FeatureStoreId>. Click the button save to save your changes to the XML template.\n\n\nReload the deegree workspace\n\n\nOnce the previous steps 1-4 are completed, reload your deegree workspace by clicking the button [Reload]. The button is located at top of the web console interface, right next to your active workspace.\n\nIf your configuration is valid, there should be no red exclemation visible on the web console interface.\n\n\nThis concludes the basic configuration of the deegree workspace.\n\n\nStep 4: Using the deegree GmlLoader\nAfter downloading and extracting the dataset mentioned at the beginning of this example workflow, the file Soil.gml needs to be copied onto the previously created deegree docker container using the following docker command:\ndocker cp path/to/Soil.gml deegree_inspire_soil:/\nLastly, the GmlLoader can be started using the following parameters:\ndocker exec -w /opt deegree_inspire_soil java -Xmx16g -jar deegree-tools-gml.jar GmlLoader -pathToFile=/Soil.gml -workspaceName=inspire_soil -sqlFeatureStoreId=inspire_soil_fs -disabledResources=https://inspire.ec.europa.eu/codelist/\n\nInfo: Setting the Java parameter -Xmx16g (value dependant on the resources provided) is highly advisable, to avoid an Java OutOfMemoryError. Further information regarding the parameters of the GmlLoader can be found in the deegree documentation.\n\n\nAttention: The deegree GmlLoader takes around 21 hours to run, since the dataset used in this example is quite large (854,2 MB).\n\nAfter the GmlLoader has run successfully, open the capabilities of the WFS configured in step 3 configured WFS under\n\nweb services > services > inspire_soil_wfs > capabilities.\n\nThe capabilties are also directly accessible at the following address:\n\nhttp://localhost:8080/deegree-webservices/services/inspire_soil_wfs?service=WFS&request=GetCapabilities\n\nLastly, QGIS or any other GIS can be connected the WFS resource. Multiple layers should be visible. Import the layer with the name SoilBody to the layer panel. The visualisation should be similar to the following screenshot:\n\n\n\nVisualisation of the deegree WFS data in QGIS\n\n\nAlternatively, you can prepare a GetFeature request to extract a sample of the data available through the configured WFS. For example:\n\nhttp://localhost:8080/deegree-webservices/services/inspire_soil_wfs?service=WFS&request=GetFeature&version=2.0.0&typeNames=so:SoilBody&count=10\n\n\n\n\nFeatured implementations\nSome implementations of INSPIRE soil data services based on deegree:\n\nBaden Württemberg, Germany\nBrandenburg, Germany\n\n\n\nRead more\ndeegree is maintained by the company lat-lon, among others\n\nWebsite: http://www.deegree.org/\nDocumentation: https://download.deegree.org/documentation/current/html/\nDownload: https://www.deegree.org/download/\nDocker: https://hub.docker.com/r/deegree/deegree3-docker/\nINSPIRE Data Specification on Soil: https://inspire.ec.europa.eu/Themes/127/2892\n\nContributions to the deegree open source project are always welcome!" }, { "objectID": "cookbook/geoserver.html", diff --git a/sitemap.xml b/sitemap.xml index f1f6185..540966c 100644 --- a/sitemap.xml +++ b/sitemap.xml @@ -2,270 +2,270 @@ https://github.com/ejpsoil/soildata-assimilation-guidance/cookbook/codelist-iso19135.html - 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