4.1.1.  OGC SensorThings API

The OGC SensorThings API provides an open and harmonized way to interconnect devices, data, and applications over the web and on the Internet of Things (IoT). At a high level the OGC SensorThings API provides two main parts, namely Part I — Sensing, and Part II — Tasking. The Sensing part provides a standard way to manage and retrieve observations and metadata from a variety of IoT sensor systems. The Tasking part provides a standard way for tasking IoT devices, such as sensors or actuators. The SensorThings API follows REST principles and uses JSON for encoding messages, as well as MQTT for publish/subscribe operations.

4.1.2.  OGC API — Features

The OGC API — Features Standard offers the capability to create, modify, and query spatial data on the Web. The Standard specifies requirements and recommendations for APIs that want to follow a standard way of sharing feature data. The specification is a multi-part standard. Part 1, labelled the Core, describes the mandatory capabilities that every implementing service has to support and is restricted to read-access to spatial data that is referenced to the World Geodetic System 1984 (WGS 84) Coordinate Reference System (CRS). Part 2 enables the use of different CRS, in addition to the WGS 84. Additional capabilities that address specific needs will be specified in additional parts. Envisaged future capabilities include, for example, support for creating and modifying data, more complex data models, and richer queries.

The OGC API — Features Standard is part of the OGC API family of standards. OGC API Standards define modular API building blocks to spatially enable Web APIs in a consistent way. The standards make use of the OpenAPI specification for defining the API building blocks.

4.1.3.  OGC Styles and Symbology

The OGC Symbology Conceptual Model: Core Part Standard (OGC 18-067r3), also known as OGC SymCore, specifies the conceptual basis to define symbology rules for the portrayal of geographical data. It is modular and extensible (one core model, many extensions), also encoding agnostic (one symbology model, many encodings). It contains a minimal set of abstract classes representing explicit extension points of the model.

OGC Styles and Symbology is a vision for a standard that implements the OGC Symbology Conceptual Model: Core Part Standard (OGC 18-067r3). The Web Mapping Code Sprint was a key moment to consolidate the roadmap to achieve this vision. The plan towards such a candidate SymCore 2.0 Standard consists of the definition of a conceptual and logical model, Cascading Style Sheets (CSS) and JavaScript Object Notation (JSON) encodings, as well as a mapping to SLD/SE (eventually with existing well known vendor options). The requirements described will be supported by illustrated and encoded cartographic use cases.

4.1.4.  OGC GeoXACML

The OGC GeoXACML Standard defines a geo-specific extension to the XACML Policy Language as defined by the OASIS standard “eXtensible Access Control Markup Language (XACML) that allows managing access to geographic information and services in an interoperable way across jurisdictions. Although XACML is meant to be used as a multi-purpose language, XACML does not have the capabilities to express geo-specific constraints on access rights. GeoXACML provides support for spatial data types and spatial authorization decision functions. Those data types and functions can be used to define additional spatial constraints for XACML based policies. GeoXACML defines extensions for the policy encoding schema only and thus does not affect the XACML context schema.

Implementations of OGC API Standards are designed to work over HTTP(S). Securing the deployed APIs is not of concern to the OGC API Standards. However, the requirement to describe the API’s endpoint via OpenAPI introduces standard options to enable authentication. Knowing the user that accesses an API is an important aspect for many use cases. Also, user identification is often used to control access to the data, served by the API. However, OGC API Standards do not currently provide guidance on how to apply access control but instead delegate the responsibility of describing the security scheme to the OpenAPI definition document. This leads to an interoperability issue if access is denied but there is no common (standardized) way to “tell the reason”. OGC’s GeoXACML 3.0 (currently still draft) Standard supports the interoperable exchange of access conditions as policies. GeoXACML 3.0 defines the geospatial extension to OASIS XACML 3.0 and thereby extends the ability to include Attribute Based Access Control (ABAC) also on geometries.

The challenge for the GeoXACML part of the code sprint was to develop a Policy Enforcement Point (PEP) that intercepts Web Feature Service (WFS) 2.0 requests and modifies the request according to an access decision returned by a GeoXACML 3.0 policy. The access control use case was the following: “WFS GetFeature requests shall exclude the NYC Central Park for feature type poly_landmarks”.

4.1.5.  OGC GeoAPI

OGC GeoAPI 3.0.2 is an OGC Standard providing a set of programming interfaces for geospatial applications. The GeoAPI interfaces closely follow the abstract models published by OGC and ISO specifications. The current release covers interfaces for metadata handling and for geodetic referencing (map projections). The GeoAPI interfaces provide a layer which separates client code, which call the API from library code, which implements the API. This follows a similar pattern to the well known JDBC or ODBC API which provides a standardized interface to databases. Clients can use the API without concern for the particular implementation which they will use.

4.2.1.  OGC GeoPose

OGC GeoPose is an OGC Draft Standard for exchanging the location and orientation of real or virtual geometric objects (Poses) within reference frames anchored to the earth’s surface (Geo) or within other astronomical coordinate systems. GeoPose specifies a single encoding in JSON format (IETF RFC 8259). The use cases addressed by GeoPose involve interactions between information systems or between an information system and a storage medium. The role of a GeoPose is to convey the orientation and position of a real or virtual object.

4.2.2.  OGC API — Records

OGC API — Records provides discovery and access to metadata records about resources such as features, coverages, tiles / maps, models, assets, services or widgets. The draft specification enables the discovery of geospatial resources by standardizing the way collections of descriptive information about the resources (metadata) are exposed. The draft specification also enables the discovery and sharing of related resources that may be referenced from geospatial resources or their metadata by standardizing the way all kinds of records are exposed and managed. The draft OGC API – Records specification is part of the OGC API family of standards.

4.2.3.  OGC GeoParquet

The OGC GeoParquet candidate Standard defines how geospatial data should be stored in Apache Parquet format including the representation of geometries and the required additional metadata. The Apache Parquet project provides an open source columnar file format that supports both data storage and retrieval.

4.3.1.  AsyncAPI

AsyncAPI is a specification by the Linux Foundation for describing and documenting message-driven APIs in a machine-readable and protocol-agnostic format. The specification defines a set of files required to describe a message-driven API. The files describing an API in accordance with the AsyncAPI Specification may be encoded in JSON or YAML.

4.3.2.  STAC API

The SpatioTemporal Asset Catalog (STAC) is a specification that offers a language for describing geospatial information, so it can be worked with, indexed, and discovered. The STAC API offers an interface that implements OGC API — Features. Although STAC has been developed outside of the OGC, in the long term it is envisaged that the STAC API specification will be developed into an OGC Community Standard that implements OGC API building blocks that are relevant for the STAC use cases.

4.4.1.  Apache Arrow

Apache Arrow is a software framework for developing applications that can process columnar data in data analytics solutions. The software framework offers a column-oriented memory format that can represent flat and hierarchical data for analytic operations on modern CPU and GPU hardware. Apache Arrow supports the Apache Parquet Format, which is the format on which the OGC GeoParquet candidate standard is being built to extend.

4.4.2.  Apache Baremaps

Apache Baremaps is an open source software toolkit and a set of infrastructure components for creating, operating, and publishing maps online. The toolkit provides a data pipeline that enables developers to build maps from a variety of data sources. The toolkit enables cartographers to customize the content and the style of a map as well as supporting services, such as location search and IP to location.

4.4.3.  Apache Sedona

Apache Sedona is a high-performance cluster computing system designed specifically for processing large-scale spatial data. The system leverages a number of open-source libraries to execute spatial operations such as Coordinate Reference System (CRS) transformation and file reading.

4.4.4.  Apache SIS

Apache Spatial Information System (SIS) is a free and open source software library for developing geospatial applications. The library is an implementation of OGC GeoAPI 3.0.1 interfaces and can be used for desktop or server applications. Services provided by Apache SIS include metadata, coordinate transformations, filtering, and grid coverages. The library is implemented using the Java programming language.

In this code sprint Apache SIS was used for testing the Geospatial Integrity of Geoscience Software (GIGS) test runners.

4.5.1.  OSGeo GeoNetwork

GeoNetwork is a catalog application for managing spatially referenced resources. It provides metadata editing and search functions as well as an interactive web map viewer.

4.5.2.  OSGeo GeoServer

GeoServer is a Java-based software server that allows users to view and edit geospatial data. Using open standards by the OGC, GeoServer allows for flexibility in map creation and data sharing.

4.5.3.  OSGeo OpenLayers

OpenLayers is a library for developing browser-based mapping applications. It works with vector and raster data from a variety of sources and is able to reproject data for rendering. The library has broad support for OGC protocols and formats, including Web Map Service (WMS), Web Map Tile Service (WMTS), Web Feature Service (WFS), Well Known Text (WKT), Well Known Binary (WKB), Geography Markup Language (GML), GeoTIFF/COG, and KML. In addition, OpenLayers has support for community specifications such as GeoJSON, XYZ tiles, TileJSON, and more. OpenLayers is written in JavaScript and is available under the BSD 2-Clause license.

The ol/source/OGCMapTile module provides a source for map tiles from an OGC API – Tiles implementation. The ol/source/OGCVectorTile module provides a source for tiled vector feature data from an OGC API — Tiles implementation.

4.5.4.  OSGeo OWSLib

OWSLib is a Python client for OGC Web Services and their related content models. The project is an OSGeo Community project and is released under a BSD 3-Clause License.

OWSLib supports numerous OGC standards, including increasing support for the OGC API suite of standards. The official documentation provides an overview of all supported standards.

4.5.5.  OSGeo pycsw

pycsw is an implementation of OGC API — Records and the OGC’s Catalogue Service for the Web (CSW) written in Python. Started in 2010 (more formally announced in 2011), pycsw allows for the publishing and discovery of geospatial metadata via numerous APIs (CSW 2/CSW 3, OpenSearch, OAI-PMH, SRU), providing a standards-based metadata and catalogue component of spatial data infrastructures. pycsw is Open Source, released under an MIT license, and runs on all major platforms (Windows, Linux, Mac OS X). pycsw is an official OSGeo Project as well as an OGC Reference Implementation.

pycsw supports numerous metadata content and API standards, including OGC API — Records — Part 1.0: Core and its associated specifications. The official documentation provides an overview of all supported standards.

4.5.6.  OSGeo pygeoapi

pygeoapi is a Python server implementation of the OGC API suite of Standards. The project emerged as part of the next generation OGC API efforts in 2018 and provides the capability for organizations to deploy a RESTful OGC API endpoint using OpenAPI, GeoJSON, and HTML. pygeoapi is open source and released under an MIT license. pygeoapi is an official OSGeo Project as well as an OGC Reference Implementation.

pygeoapi supports numerous OGC API Standards. The official documentation provides an overview of all supported standards.

4.5.7.  OSGeo QGIS

QGIS is a free and open-source cross-platform desktop GIS that supports viewing, editing, and analysis of geospatial data.

4.6.1.  OSGeo ZOO-Project

ZOO-Project is a Web Processing Service (WPS) implementation written in C. It is an open source platform which implements the WPS 1.0.0 and WPS 2.0.0 OGC Standards.

4.6.2.  TEAM Engine

The Test, Evaluation, And Measurement (TEAM) Engine is a testing facility that executes test suites developed using the TestNG framework or the OGC Compliance Test Language (CTL). It is typically used to verify specification compliance and is the official test harness of the OGC Compliance Testing Program (CITE).

4.6.3.  CesiumJS

CesiumJS is an open source JavaScript library that supports visualization of 3D globes and maps on web browsers. The library supports user interaction and streaming in of 3D Tiles (an OGC Community Standard) and a variety of other formats.

4.6.4.  OSGeo Leaflet

Leaflet is an open-source JavaScript library for mobile-friendly interactive maps. It works across all major desktop and mobile platforms, can be extended with a variety of plugins, and offers a well-documented API.

4.6.5.  Camptocamp ogc-client

Camptocamp’s ogc-client product is a Typescript library that implements several OGC Standards. The library supports the Web Map Service (WMS), Web Feature Service (WFS), and OGC API — Features standards. The library also supports the OGC API — Records candidate standard.

4.6.6.  HomeAssistant-SensorThings

Home Assistant is an award-winning free/libre/open-source home automation hub software written in Python. It can interface with over a thousand kinds of IoT devices and services, with a focus on domestic environments and data privacy.

HomeAssistant-SensorThings is a client for the OGC SensorThings API Part 1: Sensing in the form of a Home Assistant plugin (or “integration” in Home Assistant jargon). It implements discovery of available sensors in an endpoint, and periodic updates of the values of those sensors.

4.6.7.  Maplibre

MapLibre GL JS is an open-source library for publishing maps on websites or webview-based applications. The library uses GPU-accelerated rendering to offer client-side display of maps. The library supports client-side rendering of data, which makes it possible for an end-user to customize how a map is displayed.

4.6.8.  OSGeo MDME

MDME (Model Driven Metadata Editor) is a web-based application for populating YAML or JSON oriented metadata records. The application is built using Node/Vue.js. The application supports a variety of metadata models, for example MCF, OGC API — Records, and Data Package. The applications support extension of the internal metadata model.

4.6.9.  OL-Cesium

OL-Cesium is a library that integrates OpenLayers and Cesium. The OL-Cesium library supports map contexts, raster data sources, vector data sources, map selection (selected items), and animated transitions between map and globe views.

4.6.10.  OSGeo pygeometa

pygeometa provides a lightweight and Pythonic approach for users to easily create geospatial metadata in standards-based formats using simple configuration files called Metadata Control Files (MCF). The software has minimal dependencies (the installation is less than 50 kB), and provides a flexible extension mechanism leveraging the Jinja2 templating system. Leveraging the simple but powerful YAML format, pygeometa can generate metadata in numerous standards. Users can also create their own custom metadata formats which can be plugged into pygeometa for custom metadata format output. pygeometa is open source and released under an MIT license.

For developers, pygeometa provides a Pythonic API that allows developers to tightly couple metadata generation within their systems and integrate nicely into metadata production pipelines.

The project supports various metadata formats out of the box including ISO 19115, the WMO Core Metadata Profile, and the WIGOS Metadata Standard. The project also supports the OGC API — Records core record model as well as STAC (Item).

4.6.11.  Geomapfish

GeoMapFish is web application that enables developers to build extensible web-based GIS applications. It supports functionality such as webmapping, editing, responsive templates, and customization. The software supports a variety of OGC Standards as well as the MapFish protocol for communication between client-side and server-side applications. The software is built using OpenLayers, AngularJS, ngeo, Papyrus, and other toolkits.

4.6.12.  Smapshot

Smapshot is a crowdsourcing platform that enables volunteers to position historical images in 3D visualizations of geographic space, a process called ‘geolocalization’. More than a thousand volunteers have geolocalized up to 250,000 images. An OpenAPI-enabled service is available to integrate the data: https://smapshot.heig-vd.ch/development_documentation and the API and georeferencer are open source.

4.6.13.  go-ogc

go-ogc is a Go library for working with OGC API services. The library includes support for OGC API — Common, OGC API — Tiles, and OGC API — Features including support for the CQL2 JSON encoding. The library is available under the Apache 2.0 license.

4.6.14.  GPQ

GPQ is a utility for working with GeoParquet files. The command line interface can be used to validate a GeoParquet file, describe its metadata, and can convert data to and from GeoJSON. The utility is also available as a WebAssembly binary for use in a browser. GPQ is written in Go and is available under the Apache 2.0 license.

4.6.15.  ldproxy

ldproxy is an implementation of the OGC API family of standards, available under the MPL 2.0 open source license. ldproxy is developed by interactive instruments GmbH, written in Java, and is deployed using Docker containers. ldproxy implements all parts of OGC API — Features, OGC API — Tiles, OGC API — Styles, OGC API — 3D GeoVolumes, and OGC API — Routes. It is an OGC Reference Implementation for Parts 1 and 2 of OGC API — Features.

5.1.1.  CQL2

Discussions during the code sprint led to an issue with the CQL2-JSON encoding being identified and documented. The issue is summarized below.

In the JSON encoding for CQL2, there is a need to consider whether to still use function instead of op (or casei / accenti in that particular case) for those standard functions defined by the various requirements classes of the standard making the names consistent across the various functions. That is, the standard functions are likely to be routed to actual functions in the implementation, just like the user-defined custom functions.

The sprint participants also noted that the function definition also seems overcomplicated. They suggested that instead of:

{
   "function": {
      "name": "lowerCase",
      "args": [ "Test" ]
   }
}

an option would be to use:

{ "function": "lowerCase", "args": [ "Test" ] }

as with the op? (or "fn" in the case of using a short 2 letters property like op).

Further detail of this issue is documented on the OGC API — Features GitHub repository. Note that the SWG meeting of 2023-05-08 considered this issue and agreed on the following resolutions:

• change the JSON encoding of the custom functions to mimic the pattern for most standardized functions using an object with the op and args members;

• change casei and accenti to the same pattern with an op value;

• keep casei and accenti (if lower or upper are needed, they can be added as custom (or future standardized) functions); and

• rename “Basic Spatial Operators,” “Spatial Operators,” “Temporal Operators,” and “Array Operators” to use “Functions” instead of “Operators.”

5.1.2.  OGC API — Tiles

The sprint participants worked on fixing GDAL’s support of OGC API — Tiles — Part 1: Core. GDAL is an open source translator library for raster and vector geospatial data formats. The library presents a single raster abstract data model that enables the calling application to transform between a variety of data formats.

5.1.3.  OGC Styles and Symbology

During this code sprint the sprint participants worked on the JSON encoding of the OGC Styles & Symbology draft candidate Standard. The work included:

• presenting the standard in detail to the GeoStyler team who then provided the editors of the standard with valuable feedback;

• a new example styling for polygonal features;

• a new JSON Schema for the encoding; and

• addition of some descriptive text for the section.

A number of GitHub Issues were created as a result of this work. This included a GitHub Issue to fix the direction of the composition arrow in Unified Modeling Language (UML) class diagrams in the draft candidate Standard. This also included an issue for updating of the naming of the enumerations of the RelationalOperator between the table and the UML class diagram to improve consistency. Another issue created was for addition of capabilities required for completeness. Pull requests were also created for fixing editorial issues and formatting the CartoSym JSON schema.

5.1.4.  OGC Features and Geometries JSON (JSON-FG)

In the OGC API — Records discussions an issue was raised about the fact that some GeoJSON clients can only access information from the standard GeoJSON feature members (“id”, “geometry”, and “properties”).

Like OGC API — Features, OGC API — Records and STAC, JSON-FG also adds additional JSON members to a GeoJSON feature. While this is a valid extension of GeoJSON, the fact that such extensions may not be accessible in widely used tools and libraries is a concern. As a result of the discussions an issue was opened in the JSON-FG GitHub repository after a discussion in the JSON-FG Standards Working Group.

5.1.5.  OGC GeoXACML

5.1.5.3.  Achievement

During the Code Sprint a demonstration was implemented that follows the XACML flow diagram shown in Figure 2.

Figure 2 — XACML Flow Diagram

A GeoServer 2.23 WAR-file deployment was used create the WFS 2.0 service endpoint.

The injection of the PEP was done by updating the “geoserver.war” file manually:

• zip -u geserver.war WEB-INF/web.xml

• zip -u geoserver.war WEB-INF/lib/GeoXACMLFilter.jar

The web.xml file contains the deployment for the WFS Filter for GeoXACML 3.0.:

<filter>
<filter-name>GeoXACMLFilter</filter-name>
<filter-class>de.securedimensions.geoxacml3.ows.GeoServerFilter</filter-class>
<init-param>
<param-name>pdpURL</param-name>
<param-value>https://ogc.demo.secure-dimensions.de/authzforce-ce</param-value>
</init-param>
<init-param>
<param-name>pdpDomain</param-name>
<param-value>A0bdIbmGEeWhFwcKrC9gSQ</param-value>
</init-param>
</filter>
<filter-mapping>
<filter-name>Set Character Encoding</filter-name>
<url-pattern>/*</url-pattern>
</filter-mapping>
<!-- Uncomment following filter to enable CORS
<filter-mapping>
<filter-name>cross-origin</filter-name>
<url-pattern>/*</url-pattern>
</filter-mapping>
-->
<filter-mapping>
<filter-name>GeoXACMLFilter</filter-name>
<url-pattern>/wfs</url-pattern>
</filter-mapping>

Geoserver web.xml initializing the WFS Filter for GeoXACML 3.0 on path /wfs

During the code sprint one bug concerning the processing of XML attributes was fixed.

5.1.5.4.  Demonstration

The focus during the code sprint was to demonstrate the ability to rewrite WFS requests to reflect geospatial access control decisions. In order to achieve that, a simple GeoXACML 3.0 policy was crafted using ALFA for Visual Studio Code (ALFA plugin):

namespace ogc_codesprint {
    import GeoXACML.*
    import Attributes.*

    obligation Filter = "urn:secd:wfs:filter"

    policyset Manhattan = "root" {
        target clause service == "WFS"
        apply permitOverrides
        policy POLY_LANDMARKS = "poly_landmarks" {
            target clause feature_type == "tiger:poly_landmarks"
            apply firstApplicable
            rule CENTRAL_PARK {
                target clause request == "GetFeature"
                permit
                condition(geometryOneAndOnly(bbox) >< "POLYGON((40.767774 -73.981464, 40.768268 -73.981396, 40.768483 -73.981634, 40.769272 -73.981131, 40.76983 -73.980652, 40.770488 -73.980215, 40.771096 -73.9798, 40.771753 -73.979298, 40.77241 -73.978862, 40.773018 -73.978447, 40.773708 -73.977923, 40.7743 -73.977465, 40.774859 -73.977072, 40.775565 -73.97657, 40.776288 -73.97609, 40.776947 -73.975588, 40.777554 -73.97513, 40.778244 -73.974671, 40.778852 -73.974234, 40.779427 -73.973776, 40.782105 -73.971899, 40.782795 -73.971375, 40.78342 -73.970917, 40.783995 -73.970437, 40.784685 -73.969956, 40.785293 -73.969498, 40.785983 -73.969018, 40.786624 -73.968537, 40.787264 -73.968036, 40.787922 -73.96762, 40.78848 -73.967119, 40.789105 -73.966704, 40.789713 -73.966245, 40.790353 -73.965787, 40.79106 -73.965241, 40.791684 -73.964804, 40.792358 -73.964281, 40.794247 -73.962905, 40.794905 -73.962403, 40.795545 -73.961966, 40.796153 -73.961529, 40.796761 -73.961049, 40.797418 -73.960612, 40.798125 -73.960109, 40.798782 -73.959607, 40.799374 -73.959149, 40.800047 -73.95869, 40.800425 -73.958428, 40.800507 -73.958124, 40.800588 -73.957885, 40.799509 -73.955312, 40.798298 -73.95248, 40.797003 -73.94954, 40.79669 -73.94952, 40.796329 -73.949761, 40.795705 -73.950241, 40.795031 -73.950744, 40.794374 -73.951159, 40.793684 -73.95177, 40.79306 -73.952142, 40.792419 -73.9526, 40.791729 -73.953103, 40.791154 -73.953496, 40.790414 -73.954042, 40.789199 -73.954937, 40.788624 -73.955352, 40.78795 -73.955854, 40.78726 -73.956335, 40.786669 -73.956815, 40.786028 -73.957339, 40.78542 -73.957732, 40.784796 -73.958212, 40.784188 -73.958627, 40.783514 -73.959086, 40.782873 -73.959588, 40.782233 -73.96009, 40.781625 -73.960548, 40.780852 -73.961029, 40.780294 -73.961466, 40.779587 -73.961946, 40.779012 -73.962383, 40.778388 -73.962863, 40.777747 -73.963343, 40.777106 -73.963845, 40.776334 -73.964391, 40.775726 -73.964871, 40.77502 -73.965438, 40.774494 -73.965939, 40.773771 -73.966398, 40.773196 -73.966856, 40.772523 -73.967315, 40.7718 -73.967817, 40.771225 -73.968253, 40.770585 -73.96869, 40.769992 -73.969148, 40.769368 -73.969607, 40.76871 -73.970065, 40.768135 -73.970501, 40.767511 -73.970981, 40.766837 -73.971397, 40.766213 -73.971898, 40.765605 -73.972313, 40.764981 -73.972793, 40.764389 -73.973251, 40.764621 -73.973791, 40.765651 -73.976428, 40.766812 -73.97926, 40.767575 -73.981008, 40.767774 -73.981464))":geometry)
                on permit {
                    obligation Filter {
                        Attributes.Filter.operation = "Disjoint"
                        Attributes.Filter.geometry = "POLYGON((40.767774 -73.981464, 40.768268 -73.981396, 40.768483 -73.981634, 40.769272 -73.981131, 40.76983 -73.980652, 40.770488 -73.980215, 40.771096 -73.9798, 40.771753 -73.979298, 40.77241 -73.978862, 40.773018 -73.978447, 40.773708 -73.977923, 40.7743 -73.977465, 40.774859 -73.977072, 40.775565 -73.97657, 40.776288 -73.97609, 40.776947 -73.975588, 40.777554 -73.97513, 40.778244 -73.974671, 40.778852 -73.974234, 40.779427 -73.973776, 40.782105 -73.971899, 40.782795 -73.971375, 40.78342 -73.970917, 40.783995 -73.970437, 40.784685 -73.969956, 40.785293 -73.969498, 40.785983 -73.969018, 40.786624 -73.968537, 40.787264 -73.968036, 40.787922 -73.96762, 40.78848 -73.967119, 40.789105 -73.966704, 40.789713 -73.966245, 40.790353 -73.965787, 40.79106 -73.965241, 40.791684 -73.964804, 40.792358 -73.964281, 40.794247 -73.962905, 40.794905 -73.962403, 40.795545 -73.961966, 40.796153 -73.961529, 40.796761 -73.961049, 40.797418 -73.960612, 40.798125 -73.960109, 40.798782 -73.959607, 40.799374 -73.959149, 40.800047 -73.95869, 40.800425 -73.958428, 40.800507 -73.958124, 40.800588 -73.957885, 40.799509 -73.955312, 40.798298 -73.95248, 40.797003 -73.94954, 40.79669 -73.94952, 40.796329 -73.949761, 40.795705 -73.950241, 40.795031 -73.950744, 40.794374 -73.951159, 40.793684 -73.95177, 40.79306 -73.952142, 40.792419 -73.9526, 40.791729 -73.953103, 40.791154 -73.953496, 40.790414 -73.954042, 40.789199 -73.954937, 40.788624 -73.955352, 40.78795 -73.955854, 40.78726 -73.956335, 40.786669 -73.956815, 40.786028 -73.957339, 40.78542 -73.957732, 40.784796 -73.958212, 40.784188 -73.958627, 40.783514 -73.959086, 40.782873 -73.959588, 40.782233 -73.96009, 40.781625 -73.960548, 40.780852 -73.961029, 40.780294 -73.961466, 40.779587 -73.961946, 40.779012 -73.962383, 40.778388 -73.962863, 40.777747 -73.963343, 40.777106 -73.963845, 40.776334 -73.964391, 40.775726 -73.964871, 40.77502 -73.965438, 40.774494 -73.965939, 40.773771 -73.966398, 40.773196 -73.966856, 40.772523 -73.967315, 40.7718 -73.967817, 40.771225 -73.968253, 40.770585 -73.96869, 40.769992 -73.969148, 40.769368 -73.969607, 40.76871 -73.970065, 40.768135 -73.970501, 40.767511 -73.970981, 40.766837 -73.971397, 40.766213 -73.971898, 40.765605 -73.972313, 40.764981 -73.972793, 40.764389 -73.973251, 40.764621 -73.973791, 40.765651 -73.976428, 40.766812 -73.97926, 40.767575 -73.981008, 40.767774 -73.981464))":geometry
                    }
                }
            }
            rule ALL_PERMIT {
                permit
            }
        }

    }
}

GeoXACML 3.0 PolicySet described in ALFA

The GeoXACML 3.0 policy is structured in a simple way:

• PolicySet (Manhattan) matches “service == WFS”

• Policy (POLY_LANDMARKS) matches “typesNames == tiger:poly_landmarks”

• Rule (CENTRAL_PARK) matches “request == GetFeature”

• The Rule Condition contains is geospatial “BBOX Intersects Polygon(…)”

Any request that matches the condition results in the decision “Permit” with the Obligation “urn:secd:filter”. As specified in the XACML 3.0 specification, a PEP must enforce the decision including all obligations. The processing of this filter obligation provides the missing information to construct the WFS Filter (disjoint Central Park).

The result of this processing can be visualized with QGIS (WFS Layer):

Figure 3 — Left: Feature type “poly_landmarks” without PEP → Central Park feature(s) are included; Right: Feature type “poly_landmarks” with PEP → Central Park feature(s) are excluded!

The implementation of the Filter obtains the information from the HTTP request:

SubjectCategory subjectCat = new SubjectCategory();
ResourceCategory resourceCat = new ResourceCategory();
ActionCategory actionCategory = new ActionCategory();
EnvironmentCategory environmentCategory = new EnvironmentCategory();

AttributeValueType serviceType = new AttributeValueType(Arrays.asList(httpRequest.getParameter("SERVICE")), XACMLDatatypeId.STRING.value(), null);
Attribute service = new Attribute(Arrays.asList(serviceType),"urn:ogc:ows:service", "", false);
resourceCat.addAttribute(service);

Sample code for obtaining information from the HTTP request

Using the XACML-SDK for Java from Authzforce, the response from the PDP can be obtained in a few lines of code:

Request xacmlRequest = Utils.createXacmlRequest(Arrays.asList(subjectCat), Arrays.asList(resourceCat), Arrays.asList(actionCategory), Arrays.asList(environmentCategory));

ResponsesFactory xacmlResponse = pdp.getAuthZ(subjectCat, resourceCat, actionCategory, environmentCategory);
for (Response r : xacmlResponse.getResponses()) {
    LOGGER.info("XACML Response: " + r.toString());
    DecisionType decision = r.getDecision();
    LOGGER.info("XACML Decision: " + decision.toString());
    LOGGER.info("decision: " + decision.value());
    for (Obligation obligation : r.getObligations().getObligations()) {
        if (obligation.getObligationId().equalsIgnoreCase("urn:secd:wfs:filter")) {
            for (AttributeAssignment aa : obligation.getAttributeAssignments()) {
                if (aa.getAttributeId().equalsIgnoreCase("urn:secd:filter:geometry")) {
                    filterGeometry = aa.getContent().get(0).toString();
                }
                if (aa.getAttributeId().equalsIgnoreCase("urn:secd:filter:operation")) {
                    filterOperation = aa.getContent().get(0).toString();
                }
            }

        }
    }
}

Sample code for obtaining the response from the PDP

<?xml version='1.0' encoding='UTF-8'?><ns4:Response xmlns:ns6="http://authzforce.github.io/pap-dao-flat-file/xmlns/properties/3.6" xmlns:ns5="http://authzforce.github.io/core/xmlns/pdp/8" xmlns:ns4="urn:oasis:names:tc:xacml:3.0:core:schema:wd-17" xmlns:ns3="http://www.w3.org/2005/Atom" xmlns:ns2="http://authzforce.github.io/rest-api-model/xmlns/authz/5"><ns4:Result><ns4:Decision>Permit</ns4:Decision><ns4:Obligations><ns4:Obligation ObligationId="urn:secd:wfs:filter"><ns4:AttributeAssignment AttributeId="urn:secd:filter:operation" Category="urn:oasis:names:tc:xacml:3.0:attribute-category:resource" DataType="http://www.w3.org/2001/XMLSchema#string">Disjoint</ns4:AttributeAssignment><ns4:AttributeAssignment AttributeId="urn:secd:filter:geometry" Category="urn:oasis:names:tc:xacml:3.0:attribute-category:resource" DataType="urn:ogc:def:geoxacml:3.0:data-type:geometry">POLYGON ((40.767774 -73.981464, 40.768268 -73.981396, 40.768483 -73.981634, 40.769272 -73.981131, 40.76983 -73.980652, 40.770488 -73.980215, 40.771096 -73.9798, 40.771753 -73.979298, 40.77241 -73.978862, 40.773018 -73.978447, 40.773708 -73.977923, 40.7743 -73.977465, 40.774859 -73.977072, 40.775565 -73.97657, 40.776288 -73.97609, 40.776947 -73.975588, 40.777554 -73.97513, 40.778244 -73.974671, 40.778852 -73.974234, 40.779427 -73.973776, 40.782105 -73.971899, 40.782795 -73.971375, 40.78342 -73.970917, 40.783995 -73.970437, 40.784685 -73.969956, 40.785293 -73.969498, 40.785983 -73.969018, 40.786624 -73.968537, 40.787264 -73.968036, 40.787922 -73.96762, 40.78848 -73.967119, 40.789105 -73.966704, 40.789713 -73.966245, 40.790353 -73.965787, 40.79106 -73.965241, 40.791684 -73.964804, 40.792358 -73.964281, 40.794247 -73.962905, 40.794905 -73.962403, 40.795545 -73.961966, 40.796153 -73.961529, 40.796761 -73.961049, 40.797418 -73.960612, 40.798125 -73.960109, 40.798782 -73.959607, 40.799374 -73.959149, 40.800047 -73.95869, 40.800425 -73.958428, 40.800507 -73.958124, 40.800588 -73.957885, 40.799509 -73.955312, 40.798298 -73.95248, 40.797003 -73.94954, 40.79669 -73.94952, 40.796329 -73.949761, 40.795705 -73.950241, 40.795031 -73.950744, 40.794374 -73.951159, 40.793684 -73.95177, 40.79306 -73.952142, 40.792419 -73.9526, 40.791729 -73.953103, 40.791154 -73.953496, 40.790414 -73.954042, 40.789199 -73.954937, 40.788624 -73.955352, 40.78795 -73.955854, 40.78726 -73.956335, 40.786669 -73.956815, 40.786028 -73.957339, 40.78542 -73.957732, 40.784796 -73.958212, 40.784188 -73.958627, 40.783514 -73.959086, 40.782873 -73.959588, 40.782233 -73.96009, 40.781625 -73.960548, 40.780852 -73.961029, 40.780294 -73.961466, 40.779587 -73.961946, 40.779012 -73.962383, 40.778388 -73.962863, 40.777747 -73.963343, 40.777106 -73.963845, 40.776334 -73.964391, 40.775726 -73.964871, 40.77502 -73.965438, 40.774494 -73.965939, 40.773771 -73.966398, 40.773196 -73.966856, 40.772523 -73.967315, 40.7718 -73.967817, 40.771225 -73.968253, 40.770585 -73.96869, 40.769992 -73.969148, 40.769368 -73.969607, 40.76871 -73.970065, 40.768135 -73.970501, 40.767511 -73.970981, 40.766837 -73.971397, 40.766213 -73.971898, 40.765605 -73.972313, 40.764981 -73.972793, 40.764389 -73.973251, 40.764621 -73.973791, 40.765651 -73.976428, 40.766812 -73.97926, 40.767575 -73.981008, 40.767774 -73.981464))</ns4:AttributeAssignment></ns4:Obligation></ns4:Obligations>

typeNames[0] = {http://www.census.gov}poly_landmarks
srsName = urn:ogc:def:crs:EPSG::4326
filter = [[ the_geom within POLYGON ((40.46203574999999 -74.35610985937501, 40.46203574999999 -74.103704953125, 40.674587249999995 -74.103704953125, 40.674587249999995 -74.35610985937501, 40.46203574999999 -74.35610985937501)) ] AND [ the_geom disjoint POLYGON ((40.767774 -73.981464, 40.768268 -73.981396, 40.768483 -73.981634, 40.769272 -73.981131, 40.76983 -73.980652, 40.770488 -73.980215, 40.771096 -73.9798, 40.771753 -73.979298, 40.77241 -73.978862, 40.773018 -73.978447, 40.773708 -73.977923, 40.7743 -73.977465, 40.774859 -73.977072, 40.775565 -73.97657, 40.776288 -73.97609, 40.776947 -73.975588, 40.777554 -73.97513, 40.778244 -73.974671, 40.778852 -73.974234, 40.779427 -73.973776, 40.782105 -73.971899, 40.782795 -73.971375, 40.78342 -73.970917, 40.783995 -73.970437, 40.784685 -73.969956, 40.785293 -73.969498, 40.785983 -73.969018, 40.786624 -73.968537, 40.787264 -73.968036, 40.787922 -73.96762, 40.78848 -73.967119, 40.789105 -73.966704, 40.789713 -73.966245, 40.790353 -73.965787, 40.79106 -73.965241, 40.791684 -73.964804, 40.792358 -73.964281, 40.794247 -73.962905, 40.794905 -73.962403, 40.795545 -73.961966, 40.796153 -73.961529, 40.796761 -73.961049, 40.797418 -73.960612, 40.798125 -73.960109, 40.798782 -73.959607, 40.799374 -73.959149, 40.800047 -73.95869, 40.800425 -73.958428, 40.800507 -73.958124, 40.800588 -73.957885, 40.799509 -73.955312, 40.798298 -73.95248, 40.797003 -73.94954, 40.79669 -73.94952, 40.796329 -73.949761, 40.795705 -73.950241, 40.795031 -73.950744, 40.794374 -73.951159, 40.793684 -73.95177, 40.79306 -73.952142, 40.792419 -73.9526, 40.791729 -73.953103, 40.791154 -73.953496, 40.790414 -73.954042, 40.789199 -73.954937, 40.788624 -73.955352, 40.78795 -73.955854, 40.78726 -73.956335, 40.786669 -73.956815, 40.786028 -73.957339, 40.78542 -73.957732, 40.784796 -73.958212, 40.784188 -73.958627, 40.783514 -73.959086, 40.782873 -73.959588, 40.782233 -73.96009, 40.781625 -73.960548, 40.780852 -73.961029, 40.780294 -73.961466, 40.779587 -73.961946, 40.779012 -73.962383, 40.778388 -73.962863, 40.777747 -73.963343, 40.777106 -73.963845, 40.776334 -73.964391, 40.775726 -73.964871, 40.77502 -73.965438, 40.774494 -73.965939, 40.773771 -73.966398, 40.773196 -73.966856, 40.772523 -73.967315, 40.7718 -73.967817, 40.771225 -73.968253, 40.770585 -73.96869, 40.769992 -73.969148, 40.769368 -73.969607, 40.76871 -73.970065, 40.768135 -73.970501, 40.767511 -73.970981, 40.766837 -73.971397, 40.766213 -73.971898, 40.765605 -73.972313, 40.764981 -73.972793, 40.764389 -73.973251, 40.764621 -73.973791, 40.765651 -73.976428, 40.766812 -73.97926, 40.767575 -73.981008, 40.767774 -73.981464)) ]]

5.1.6.  OGC GeoAPI

The work done during this code sprint was not on GeoAPI itself, but on a usage of it. GeoAPI is the interface between the Java runner of GIGS tests (Geospatial Integrity of Geoscience Software) and PROJ-JNI. Both projects have been updated for enabling the execution of a greater range of GIGS tests on PROJ. The changes consisted in upgrading the way that client codes discover GeoAPI implementations. That discovery is done through the Java Service Providers mechanism. However, that mechanism changed significantly between Java 8 and Java 9. The new mechanism in Java 9, in addition to being more secure, also provides more flexibility in the way to discover services. This flexibility has been exploited during this code sprint for filling some holes in the GIGS test coverage.

The Apache SIS project, which is another GeoAPI implementation, has not yet been updated to Java 9+ modularization. That update will take more time because SIS is made of many modules, while PROJ-JNI is a single module. But this testbed experimented how the work can been done. An outcome of this testbed is that a small change will be needed in GeoAPI for working with the more security-constrained way that Java 9+ discovers services and resources.

5.1.7.  OGC API — Records

Edits to the candidate standard in preparation for the code sprint included:

• update of core/openapi/schemas/language.yaml;

• setting of the default language direction to ltr;

• Removal of obsolete files; and

• Removal of all requirements/recommendations copied from OGC API — Features — Part 1.

A sample of the edits made to the candidate standard during the code sprint is as follows.

• Addition of a providers’ array to align with STAC.

• Other changes to various schemas and recommendations towards closer STAC harmonization.

• Addition of a time member to the Record example and updates to the Contact information.

• Addition of requirements for the logo member.

• Change of the deliveryPoint member to an array of string to allow multiple address.

• Updates to the theme model.

• Fixing of the nullability of the time property and add resolution.

The OGC API — Records team held two breakouts during the code sprint focusing on advancing the specification for review by the OGC Architecture Board (OAB). The discussions during the breakout sessions included:

• Extension for faceted searching

• Record model: contacts and roles

• STAC harmonization.

5.1.8.  OGC API — Features

Before the code sprint a new proposal for handling feature schemas had been prepared for discussion in the OGC Features API Standards Working Group and at the code sprint.

In current drafts, a JSON schema for the GeoJSON encoding of the features is returned by the API as the feature schema. That approach has several disadvantages as follows.

• Not all APIs can support GeoJSON (e.g., for 3D buildings).

• There was a need to have different schemas for different operations. For example, the server may return features with a (slightly) different schema than it expects when a new feature is created or updated.

• Validation of content is one use case for a schema, but for other use cases an encoding-agnostic logical schema is more beneficial and easier to use. For the queryables and sortables resources such a schema is already used.

• Another example is that of feature relationships that should be expressed as such in the schema but that can be encoded in various ways in the data depending on the format or the use case.

The proposal addresses these issues by:

• providing an encoding-agnostic logical schema of the features in a collection (expressed in JSON Schema, using the same requirements and recommendations as in Part 3 for the Queryables resource);

• adding an additional keyword to identify special roles that a property may have (e.g., identify the feature id, the primary geometry, etc);

• using the JSON Schema keywords readOnly and writeOnly to identify properties that are only relevant for GET (read-only) or POST/PUT/PATCH (write-only) requests;

• adding support for properties that are a reference to another feature in the same API or another API; and

• specifying a new query parameter profile to support requesting different representations of such feature references in the data.

The proposal was discussed by sprint participants in a breakout session. The GitHub issue was updated with the results of the discussion. There was agreement to start work on a pull request for OGC API — Features, to test the approach in implementations, and to present the approach to other OGC API working groups at the June 2023 OGC Member Meeting.

Participants from interactive instruments started to work on an implementation in ldproxy during the code sprint. The implementation was completed in the weeks after the code sprint.

The approach was presented and discussed in the OGC API track during the June 2023 OGC Member Meeting. The approach was supported by other OGC API working groups. As a result the Standards Working Group decided to use the approach as the starting point for a new part (Part 5: Schemas).

Other OGC API — Features topics that were discussed with participants from open source projects included the following.

• Discussion with Smapshot developers about the relationship between GeoPose and features and how to provide GeoPose via building blocks from OGC API — Features.

• Support for faceted search, i.e., return not only a page of selected features, but also statistical information about important values of selected properties and the number of features that have that value. This information can be used to interactively “drill down” to find features of interest. A proposal currently exists in OGC API — Records.

• For clients that interact with a Features API, it would be beneficial if APIs would provide not only a textual GeoJSON encoding, but also a more efficient binary encoding. Currently no conformance class exists for such a feature encoding in OGC API — Features. This is a topic that should be discussed in the Standards Working Group.

5.1.9.  OGC API — Environmental Data Retrieval

In the OGC MetOcean Domain Working Group (DWG) there is interest in establishing an OGC API approach for Publish/Subscribe (Pub/Sub) operations. This is because alerts have to be sent out instantly when severe weather events occur. Members of the MetOcean DWG have been developing a Discussion Paper on Pub/Sub operations which was presented at the OGC Member Meeting in Frascati, Italy in February 2023. It is envisaged that the Discussion Paper will lead to the specification of a conformance class in the OGC API — Environmental Data Retrieval (EDR) standard that can also be used by other OGC API Standards as well.

The Discussion Paper describes a number approaches of how to support event-driven functionality in OGC API Standards. The Discussion Paper specifies a prototype API. The next step is turning that prototype into a conformance class. The basic premises behind the specification is to be generic. The specification recommends use of AsyncAPI to advertize an event-driven capability. The specification also recommends use of a well-known encoding, for example, JSON. Finally, the specification recommends use of the endpoint of the building blocks used for OGC API when advertizing the event-driven capability.

An initial attempt at generic conformance classes is being developed in a draft pull request to OGC API — EDR.

The generic nature of the draft at the time of the code sprint is a challenge for subscribers as the content of the messages is undefined. As a result, different publishers will design messages in different ways and provider-specific subscription clients have to be developed. This resulted in a proposal for adding a new conformance class for a generic message payload, which was added to the OGC API — EDR pull request after the code sprint.

During the code sprint pygeoapi was updated with an implementation of the draft Pub/Sub extension.

Work on a new ldproxy Pub/Sub module for feature resources was started based on the draft Pub/Sub extension. Two open-source Java libraries for MQTT were analyzed (Eclipse Paho and HiveMQ). HiveMQ was selected for the development, mainly because of its support for reactive programming. Only the initial framework was set up during the code sprint. The work will be continued in OGC Testbed-19.

5.2.1.  AsyncAPI

The maintainers of pygeoapi worked on support for AsyncAPI. A discussion of the pygeoapi results is presented in Clause 6.5. The landing page of the pygeoapi instance was modified to enable it to advertise links to both the OpenAPI definition document and the AsyncAPI definition document. Figure 4 shows a screenshot of the landing page of a pygeoapi instance that advertises both an OpenAPI and an AsyncAPI definition document.