Michael Gould

Service-oriented applications for environmental models: Reusable geospatial services

Environmental modelling often requires a long iterative process of sourcing, reformatting, analyzing, and introducing various types of data into the model. Much of the data to be analyzed are geospatial data-digital terrain models (DTM), river basin boundaries, snow cover from satellite imagery, etc.-and so the modelling workflow typically involves the use of multiple desktop GIS and remote sensing software packages, with limited compatibility among them. Recent advances in service-oriented architectures (SOA) are allowing users to migrate from dedicated desktop solutions to on-line, loosely coupled, and standards-based services which accept source data, process them, and pass results as basic parameters to other intermediate services and/or then to the main model, which also may be made available on-line. This contribution presents a service-oriented application that addresses the issues of data accessibility and service interoperability for environmental models. Key model capabilities are implemented as geospatial services, which are combined to form complex services, and may be reused in other similar contexts. This work was carried out under the auspices of the AWARE project funded by the European programme Global Monitoring for Environment and Security (GMES). We show results of the service-oriented application applied to alpine runoff models, including the use of geospatial services facilitating discovery, access, processing and visualization of geospatial data in a distributed manner.

Integrating Semantic and Syntactic Descriptions to Chain Geographic Services

Integrating multiple geographic services from different information communities and spatiolinguistic regions is challenging because of its inherent complexity and heterogeneity. A geographic information systems workflow approach can use semantic and syntactic service descriptions to form service chains that can integrate service discovery, composition, and reuse. Service chaining links remote geographic services to help expert users form complex geoprocessing services and perform timely analysis of geodata. This method facilitates the use of XML-based service description languages to build a geoservice-reuse architecture based on common ontologies and shared service descriptions

Managing user-generated information in geospatial cyberinfrastructures

Information systems built using standards-based distributed services have become the default computing paradigm adopted by the geospatial community for building information infrastructures also known as Spatial Data Infrastructures (SDIs). Government mandates such as the INSPIRE European Directive recommend standards for sharing resources (e.g., data and processes) with the goal of improving environmental (and related) decision making. Although SDIs present benefits to data providers in terms of data sharing and management, most geospatial infrastructures have been built following a top-down approach in which official providers (most commonly mapping agencies) are permitted to deploy and maintain resources. Because the mechanisms to deploy resources in these infrastructures are technologically complex, there has been limited participation from users, resulting in a scarcity of deployed resources. To address these limitations, we present a distributed architecture based on INSPIRE principles and extended with a Service Framework component. This component improves ad hoc integration and deployment of geospatial data resources within geospatial information infrastructures. The Service Framework addresses the need to improve the availability of geospatial data resources by providing mechanisms to assist users in wrapping resources to generate INSPIRE-based services.

Enhancing Geo‐Service Chaining through Deep Service Descriptions

We demonstrate the integrated use of semantic and syntactic service descriptions, called deep service descriptions, for service chaining by combining two prototypes: one that deals with geoservice discovery abstract composition (called ‘GeoMatchMaker’), with one that supports concrete composition and execution of geoservices services (called ‘Integrated Component Designer’). Most other service chaining approaches confine themselves to handling either syntactic or semantic service descriptions. The proprietary formats of these descriptions hamper an effective integration of discovery, composition and execution of multiple services. In essence, service chaining should help a user by

Managing Earth observation data with distributed geoprocessing services

Geospatial web services within a Spatial Data Infrastructure framework enable discovery of, and access to, geospatial information and services as well as data visualization. Earth Observation data-based applications pose a challenge for these infrastructures due to their consumption of huge volumes of data. Spatial Data Infrastructures promote the processing of data in situ rather than downloading them for local processing, and therefore novel methods are needed for scientists to process EO data in a distributed way. We describe an approach to facilitate EO data exploitation via distributed geoprocessing services, and we use as a concrete use case a scenario for predicting runoff in Alpine river basins. We show a methodology for wrapping geoprocesses in standardized containers, and an API platform for accessing and combining collections of these service containers.

Improving reuse of web service compositions

We describe a methodology for assembling composite services based on three basic processes which are independent of the concrete implementation: Service Abstraction Process, Service Composition Process, and Translation Process. These processes share the concept of integrated component composed of two key aspects: a specific set of the Aalsts workflow patterns together with a component-style composition of complex services. We propose a novel approach that implements the steps of such methodology, providing an efficient manner for developing service compositions and enhancing the expressiveness of target composition languages like BPEL4WS. Here we focus on the description of the Service Abstraction Process, a critical step in order to enhance the service composition by facilitating the reuse of existing services.

Service Composition for SDIs: Integrated Components Creation

We describe a methodology for creating composite Web services, a key ingredient in spatial data infrastructure (SDI) applications, which we demonstrate on an emergency management use case. The methodology uses three basic processes independent of the concrete implementation: service abstraction process, service composition process, and translation process. These processes share the concept of integrated component composed of two key aspects: a component-style composition of complex services together with a specific set of workflow patterns. We propose a novel model that implements the steps of such methodology, providing an efficient manner for developing service compositions and enhancing the expressiveness of target composition languages like BPEL4WS. We focus on the description of the service abstraction process and the relationships among its grounded elements - services, components, and workflow patterns -, which form the basis of an integrated component, for enhancing the service composition by facilitating the reuse of existing services

Enhancing integrated indoor/outdoor mobility in a smart campus

A Smart City relies on six key factors: Smart Governance, Smart People, Smart Economy, Smart Environment, Smart Living and Smart Mobility. This paper focuses on Smart Mobility by improving one of its key components: positioning. We developed and deployed a novel indoor positioning system (IPS) that is combined with an outdoor positioning system to support seamless indoor and outdoor navigation and wayfinding. The positioning system is implemented as a service in our broader cartography-based smart university platform, called SmartUJI, which centralizes access to a diverse collection of campus information and provides basic and complex services for the Universitat Jaume I (Spain), which serves as surrogate of a small city. Using our IPS and based on the SmartUJI services, we developed, deployed and evaluated two end-user mobile applications: the SmartUJI APP that allows users to obtain map-based information about the different facilities of the campus, and the SmartUJI AR that allows users to interact with the campus through an augmented reality interface. Students, university staff and visitors who tested the applications reported their usefulness in locating university facilities and generally improving spatial orientation.

Semi-automatic metadata extraction from imagery and cartographic data

Metadata are necessary to allow discovery and description of data and service resources within a Spatial Data Infrastructure, however current manual metadata editing workflows are tedious and under-utilized. We discuss on-going developments for semi-automatic metadata extraction from well- known imagery and cartographic data sources, being implemented within an open source software project in Spain. Internal metadata are collected automatically and the user can then choose to add external metadata, and to publish the final metadata record to catalogues. The next step will be to extract implicit metadata using Google-like methods.

Multidimensional binary indexing for neighbourhood calculations in spatial partition trees

We present a binary array encoding (location arrays) of the nodes in a spatial partition tree representing spaces of dimension k. This framework facilitates tree traversal for optimizing access speed, and also supports simplified calculation of the neighbourhood of a subinterval of a particular partition. After defining the encoding we present a neighbour determination algorithm which extends work carried out by Samet, Goodchild and others on quadtrees, of particular interest when managing large data volumes during real-time terrain flyovers. The primary extension is that the encoding and the neighbour determination algorithm extend to arbitrary dimensions beyond the 2-d quadtree case.