In today’s information world, users have access to a vast amount of geospatial information. When information from multiple sources can be combined together, its usefulness increases dramatically. However, there is no well-defined fusion framework available that addresses semantic differences in heterogeneous geospatial sources. The Semantic Web Link Builder and Triple Generator ER describes a generalized approach towards performing data fusion from multiple heterogeneous geospatial sources.

The specific use case addressed in the Testbed 15 Machine Learning Thread research activity was semantic enrichment of hydrographic features provided by Natural Resources Canada (NRCan). The discussion in the ER attempts to define and formalize the integration pipeline necessary to perform a fusion process for producing semantically coherent fused entities. This was done by using a number of ontologies for supporting correlation and semantic mediation defined using the new W3C Shape Constraint Language (SHACL), as well as a correlation engine that was implemented to be accessible through an Application Programming Interface (API) based on the Representational State Transfer (REST) paradigm.

Based on the findings in Testbed 15, future OGC innovation work will need to implement the suggested semantic mediation and fusion engine.

The intersection of Machine Learning (ML) and Deep Learning (DL) and geospatial technology is creating opportunities that have not been possible before. Use of these technologies is enhancing our ability to increase crop yield through precision agriculture, to fight crime by deploying predictive policing models, or to enhanced image classification and feature detection. In the Testbed 15 ML activity, participants explored the ability of ML to interact with and use OGC web standards in the context of natural resources applications. A key research objective was to demonstrate the use of OGC standards in the ML domain through the development of scenarios. The scenarios used in the ML thread were:

Each scenario utilized a set of supporting geospatial data coupled with cataloging and processing services to support the research objectives. A ML model is at the core of each scenario. In each scenario the goal was to have the model make key decisions that a human in the system would typically make under normal circumstances. Each scenario and corresponding prototype implementations were supported by at least one client to demonstrate the execution and parsing of outputs for visualization.

In summary, the ML thread included five scenarios utilizing seven ML models in a solution architecture that included implementations of the OGC Web Processing Service (WPS), OGC Web Feature Service (WFS) and OGC Catalogue Service for the Web (CSW) standards. This ER includes a thorough investigation and documentation of the experiences of the ML participants resulting in a set of recommendations for future work.

With the rise in cloud computing, sensitive data can transit through or be stored in systems that are outside the traditional security perimeter. Data is free to flow anywhere and everywhere it might be needed by an increasingly mobile workforce. Therefore, cybersecurity strategies need to shift from trying to maintain a secure perimeter around systems and applications to secure data against unauthorized access. A data-centric security strategy is required.

The Data Centric Security ER discusses the current state of security in protecting data in a geospatial environment. The ER examines the use of encrypted container formats such as NATO STANAG 4778 “Information on standard Metadata Binding” with metadata as defined in NATO STANAG 4774 “Confidentiality Metadata Label Syntax” in combination with geospatial data using the encoding for an OGC Web Feature Service (WFS) FeatureCollection structure. The ER also recommends the creation of new media types to support output container formats such as STANAG 4778. The ER then discusses various implementation scenarios in which a STANAG 4778 (eXtensible Markup Language (XML) container maintains encrypted data from author to service to viewer. These implementations use the new OGC API – Features standard with features encrypted using keys supplied by feature authors and users.

The participants demonstrated that data centric security is possible within the OGC API service framework. The ER documents the three DCS scenarios used to investigate the data centric security:

The ER concludes with issues encountered and recommendations for future work. Based on these recommendations, Testbed 16 participants will develop a Data Centric Security implementation in the OGC API family of standards, including a Data Centric Security JSON implementation.

The Delta Updates ER documents the design of a service architecture that allows the delivery of prioritized updates of geospatial features to a client, that may be in a DDIL (Denied, Degraded, Intermitted or Limited Bandwidth) environment. Dissemination of GEOINT data in a DDIL Bandwidth environment is a challenging problem. By not serving the entire dataset, but only the changes (delta updates) combined with priority was identified as a valid approach to this problem. Two different technical scenarios were investigated and tested:

As such, the ER documents how prioritized delta updates can be served using a transactional extension to the OGC API – Features Core and the draft WPS standard/OGC API – Processes specification in front of Web Feature Service instances. Both approaches use the same algorithm to keep track of the changes to the dataset.

The ER concludes with a key recommendation that the OGC investigate a common approach for delta updates across existing and in development OGC APIs.

Platforms supporting numerous applications have emerged that provide access to Earth Observation data and processing capacities. These platforms host very large datasets, which makes a paradigm shift from data download and local processing towards application upload and processing close to the physical location of the data more and more important. To best interpret peta- and exascale scientific data, capabilities of these platforms need to be combined.

The work in this activity builds on previous OGC testbed activities. OGC Testbed-13 and Testbed-14 ERs propose solutions for packaging, deployment and execution of applications in cloud environments that expose standardized interfaces such as the OGC Web Processing Service (WPS). As long as a dedicated standardized interface such as an OGC WPS instance, a container execution environment (e.g. Docker), and data access are provided, the proposed approach is agnostic to the target cloud platform.

The ER presents the data model and interface for a catalogue service enabling discovery of EO applications and related processing services for subsequent deployment and/or invocation in a distributed environment. The ER also provides the architectural and implementation details of the software components that were developed as part of the activity and which interact through the described data model. These software components include catalogue clients, catalogue servers and WPS transactional (WPS-T) servers.

Web Mapping client-side styling requires a way to locate a suitable style on the server, determine the style’s applicability to the current displayed layers, and retrieve the style. A style is a sequence of rules of symbolizing instructions to be applied by a rendering engine on one or more features and/or coverages. Further, style catalogs and style reuse require a way to describe styles (what kind of symbolization is used, what layers are involved, what attributes are needed). At the same time both client and server applications are increasingly supporting a wider variety of open styling encodings. To meet these and other style interoperability requirements, a style encoding and metadata conceptual model is required. The model provides information for understanding a style’s intended usage, availability, and compatibility with existing layers. The model also supports style search. The ER describes the Styles conceptual model developed in Testbed 15.

In Testbed 15, the Styled Layer Descriptor (SLD) 1.0, Symbology Encoding (SE) 1.1, Cascading Style Sheets (CSS), and https://docs.mapbox.com/mapbox-gl-js/style-spec/ [Mapbox GL] styles were reviewed. The testbed activity also built upon previous OGC work, in particular:

This ER documents a draft specification for a Web API that enables map servers and clients as well as visual style editors to manage and fetch styles. Web APIs are software interfaces that use an architectural style that is founded on the technologies of the Web. Styles consist of symbolizing instructions that are applied by a rendering engine on features and/or coverages.

The draft Styles API supports several types of consumers, mainly:

Feature data is either accessed directly or organized into spatial partitions such as a tiled data store (aka “vector tiles”). The Styles API is consistent with the emerging OGC API family of standards. The Styles API implements the conceptual model for style encodings and style metadata as documented in chapter 6 of the Encoding and Metadata Conceptual Model for Styles ER. The model defines three main concepts:

Since 2017, the OGC has had a focused effort developing API standards based on the concepts defined in a Resource Oriented Architecture (ROA). The OGC APIs are described using the OpenAPI 3.0 specification. The ER defines a proof-of-concept for a Maps and Tiles API specification. The draft Maps and Tiles specification builds on the OGC API – Features – Part 1: Core standard.

The draft Tiles specification describes a service that retrieves data representations as tiles. In the draft specification, the assumption is that tiles are organized into Tile Matrix Sets (TMS) consisting of regular tile matrices available at different scales or resolutions.

The draft Maps specification describes an API that presents data as maps by applying a style. These maps can be retrieved in a tiled structure or as maps of any size generated on-the-fly. Some of the functionality in the draft Maps specification is based on the OGC Web Map Tile Service (WMTS) 1.0 standard. This is related to the use of styles by using the draft Styles API specification that was developed in the Testbed-15 Open Portrayal Framework thread.

Standards that enable interoperable portrayal are critical in many domains, where distributed environments lead to a variety of styles, rendering engines, and spatial data types. In this context, the goal of the Testbed 15 OPF work was to enable the rendering of geospatial data in a uniform way, according to specific user requirements without undue burden on the user. The ER includes an overview of the requirements, detailed presentation of the demonstration scenario, a high-level architecture, and prototype solutions that were developed.

The main topics addressed in the OPF Thread are style changing and sharing, converting style encodings, client- / server-side rendering of vector- and raster data and data provision in denied, disrupted, intermittent, and limited bandwidth (DDIL) infrastructure situations. This ER, along with companion ERs, documents a set of emerging specifications that support interoperable portrayal of heterogeneous geospatial data. This includes an enhanced GeoPackage model which was developed to facilitate advanced styling in offline situations. The main results are discussed in GeoPackage chapter.

A detailed demonstration and requirements scenario was defined and documented. The scenario discussion explains the requirements for the various developments conducted in Testbed-15. Among these are a series of new OGC Web APIs.

In this ER, the API discussion is from a more abstract viewpoint, with some of the major discussion items and design decisions being highlighted in the Emerging OGC Web APIs chapter. The detailed documentation of the APIs can be found in the respective Engineering Reports that are listed in the OPF Thread Summary.

The ER concludes with the documentation of a number of general discussions and design decisions that were made by the OPF participants. A detailed description of implementation aspects and presentation of the results was provided by the participants and is presented in Annex A: OPF Implementations.

There is a critical need to be able to easily and efficiently update – on a priority basis – content in a tiled imagery datastore. The OGC API – Images and ChangeSet draft specification addresses the use case of an OGC API Tile Server that serves image tiles and a client that portrays the result as a set of images. The source images can be updated and therefore the tile server also needs to be able to deliver only the tiles that have changed.

The ER addresses two independent but related APIs:

The OGC API – Images is designed to simplify the creation and maintenance of sets of images that can then be exposed and retrieved by other OGC API’s, such as OGC API – Coverages. The use of the ChangeSet filter helps keep clients synchronized with changes to the source content on servers while also minimizing the bandwidth necessary for the synchronization.

Note: That the Delta Updates ER recommends that the OGC investigate a common approach for delta updates across existing and in development OGC APIs.

The Portrayal Summary ER provides an executive summary of the Testbed 15 Open Portrayal Framework (OPF) Thread. The OGC Open Portrayal Framework is a set of emerging models and API specifications that support interoperable portrayal of heterogeneous geospatial data. The OPF facilitates the rendering of geospatial data in a uniform way, according to specific user requirements. The primary topics addressed in the OPF thread covered supporting style sharing and updates, client- and server-side rendering of both vector- and raster data, and converting styles from one encoding to another. This work was based on the concepts, relationships and terms defined in a draft conceptual style model. In addition, the requirement to render data according to style definitions in a scenario with denied, disrupted, intermittent, and limited bandwidth (DDIL) infrastructure was addressed.

To progress the development, testing, and demonstration of the prototype models and APIs, a detailed scenario was defined that allowed the participants to assess the ability of the OPF to support simulated users in a humanitarian relief situation. The OPF scenario was comprised of four major aspects:

Based on the OPF scenario the ER describes how the work completed in the OPF thread set a milestone towards realizing a fully interoperable multi-source/multi-data type geospatial data rendering environments. The ER highlights the achievements of the testbed participants by discussing and demonstrating how the OPF scenario requirements were addressed.

There is rapid growth in the area of Federated Clouds. Federated Clouds represent the union of software, infrastructure and platform services from disparate networks that can be accessed by a client via the internet. Within this environment, the need for innovative security models for user access to cloud resources is paramount. Traditional security models are not adequate.

The Federated Clouds Security ER documents the analysis of two types of federation: The centralized entity and distributed architecture approaches. Both approaches were analyzed through the lens of security. The ER documents how federated membership, resource and access policy management can be provided within a security environment, while also providing portability and interoperability to all stakeholders. The work presented in the ER also took into account how governance can be affected by design choices. I addition the ER provides an introduction to the concepts of Federation and Federated Clouds and then introduces the concept of a Federation Manager (FM) and tries to establish a clear list of functionality aspects necessary to manage and use a Federation. The ER concludes with a complete analysis of the Federation Managers deployed during this Testbed-15 activity, and how to tackle each of the functionality challenges.

The results of the integration experiments indicated that both architectures lead to different technical consequences which were investigated and described in the ER. As such, the ER forms a suitable basis for further investigation on interoperability and security between and across federations.

The Federated Clouds Analytics ER documents the results and experiences gained during the Federated Cloud Analytics task. The work documented addresses a broader question of how to leverage Cloud architectures managing automated processing on a cluster of machines combined with using OGC standards. The research focused on the SCALE Data Center Environment. Also as part of this activity, the SEED job interface specification was used to package job input/output parameters metadata with Docker images that contain discrete processing algorithms. This enables developers to prepare the software in a self-contained package containing all execution dependencies, deploy and execute it in a hosted environment with access to data. Within this context, the ER documents how the OGC Web Processing Service (WPS) 2.0 Standard can be used as a standard API for Cloud analytics for workflow automation.

More specifically, the ER provides an analysis of:

This ER presents a thorough analysis of the work produced in the Earth Observation Clouds (EOC) threads in OGC Testbeds 13 and 14 in relation to the US National Geospatial Intelligence (NGA) GeoInt Scale and SEED environments. Scale provides management of automated processing on a cluster of machines. The SEED specification aids the discovery and consumption of a discrete unit of work contained within a Docker image.

The ER outlines how the OGC Testbed-13 and OGC Testbed-14 research results of “bringing applications/users to the data” relate to Scale and SEED. Both approaches have in common that they encapsulate workloads in Docker containers, making them as independent as possible of the execution environment. More importantly, such Docker containers can be moved to nodes in the data center closest to the data or to other data centers altogether. While comparing the two approaches, the ER identifies and describes opportunities for harmonization or standardization. However, this also provides reasons why some features must remain separate. These hard problems require additional work but represent opportunities which should be examined in future initiatives.

For developers, the ER constitutes a technical reference supporting the comparison of the two approaches, thereby enabling developers to make informed choices, understand trade-offs, identify relevant standards and clarify misunderstandings.

Assurance of the quality and repeatability of data results is essential in many fields, such as eScience, and healthcare, and requires cloud auditing and the maintenance of provenance information for the whole workflow execution. The use of heterogeneous components in cloud computing environment introduces the risks of accidental data corruption, processing errors, vulnerabilities such as security violation, data tampering or malicious forgery of provenance. Cloud systems are structured in a fundamentally different way from other distributed systems, such as grids, and therefore present new challenges for the collection of provenance data.

The scope of the study documented in this ER is a review of the state-of-the-art of Provenance and Blockchain technologies, identifing the challenges and requirements about using cloud computing provenance on a blockchain. Based on these analyses, an architecture is proposed to share provenance information from federated cloud workflows that ensure the provenance information has not be tampered with so that user can trust the results produced by the workflow.

The study determined that W3C Self Sovereign Identifiers (SSIs) and verifiable credentials are fundamental assets for interaction over the Internet and are the cornerstone of establishing the Web Of Trust needed to ensure provenance of information. SSI brings back full control of the identity to the owner and the use of Distributed Ledger Technology (DLT) and Blockchain to support Distributed Public Key Infrastructure (DPKI) provides a solid alternative that addresses the usability and security issues of the centralized PKI approach.

MapML is a text format for encoding map information for the World Wide Web. The value of MapML is enabling Web-based user agent software (browsers and others) to display and edit maps and map data without unnecessary customization.

The Quebec Model MapML ER describes the Map Markup Language (MapML) enabled client implementation for the Quebec Lake-River Differentiation Model in the Machine Learning (ML) task. This ER details the MapML parsing capabilities that were developed to illustrate the outputs of a ML model to delineate lake and river features from an undifferentiated waterbody vector dataset in Québec, Canada. Client data was accessed through an OGC Web Processing Service (WPS) interface in coordination with an OGC API – Features implementation.

The ER concludes that MapML is suitable for representing not only a selection of features from a data source, but may also be useful as a metadata document describing a collection of information. MapML could provide links into the collection using map semantics (bounding boxes, tiles, images, features etc.).