Theme section “Towards Intelligent Geoprocessing on the Web”

IEEE Transactions on Automation Science and Engineering, 2010

The need for computational resources capable of processing geospatial data has accelerated the uptake of geospatial web services. Several academic and commercial organizations now offer geospatial web services for data provision, coordinate transformation, geocoding and several other tasks. These web services adopt specifications developed by the Open Geospatial Consortium (OGC)-the leading standardization body for Geographic Information Systems. In parallel with efforts of the OGC, the Grid computing community has published specifications for developing Grid applications. The Open Grid Forum (OGF) is the main body that promotes interoperability between Grid computing systems. This study examines the integration of Grid services and geospatial web services into workflows for Geoscientific processing. An architecture is proposed that bridges web services based on the abstract geospatial architecture (ISO19119) and the Open Grid Services Architecture (OGSA). The paper presents a workflow management system, called SAW-GEO, that supports orchestration of Grid-enabled geospatial web services. An implementation of SAW-GEO is presented, based on both the Simple Conceptual Unified Flow Language (SCUFL) and the Business Process Execution Language for Web Services (WS-BPEL or BPEL for short). Note to Practitioners-Geoscientific workflows are used in several disciplines including for example geology, geophysics hydrology, and petroleum science. Some of the analysis carried out by geoscientists can now be offered on the World Wide Web using standardized web services. Our study examines the potential of workflow enactors to support the creation of geoscientific workflows involving web services based on standards of the Open Geospatial Consortium. An implementation of a prototype is presented and applied to the analysis of groundwater vulnerability using borehole data. A sample workflow is implemented using two different workflow enactors and their distinct languages to demonstrate that the proposed approach is independent of the workflow enactor adopted. The proposed approach could be used to support collaborative workflows that involve analytical services provided by multiple organizations

Concurrency and …, 2008

We discuss the development and application of Web-service-based geographical information system (GIS) Grids. Following the WS-I+ approach of building Grids on Web service standards, we have developed data Grid components for archival and real-time data, map generating services that can be used to build user interfaces, information services for storing both stateless and stateful metadata, and service orchestration and management tools. Our goal is to support dynamically assembled Grid service collections that combine both GIS services with more traditional Grid capabilities such as file transfer and remote code execution. We are applying these tools to problems in earthquake modeling and forecasting, but we are attempting to build general purpose tools by using and extending appropriate standards.

Annals of Gis / Geographic Information Sciences, 2005

This paper presents a new framework for Grid-enabled GIService web portals to facilitate the building of high-level intelligent Internet GIServices. The five-tier architecture suggested here can support advanced semantic search and query functions for distributed GIServices by combining Grid computing, Semantic Web, and software agent technologies. The design of the web portal user interface with software agents can help end users combine and integrate computing power with geospatial data and services. Geospatial ontologies are incorporated into the framework by using geographic web ontology language (G-OWL). Intelligent software agent (GeoAgent) techniques are used to automate the procedures for searching, retrieving and processing geospatial data. The proposed Internet GIService architecture will provide a blue print for the establishment of Grid-enabled Internet GIServices and will help the GIS community to identify potential technical challenges to implement intelligent Internet GIServices.

Nowadays, GIS applications can be found on everyone's PC, PDA, Tablet PC, and Smartphone. Desktop GIS systems are gradually being substituted by web services and tailored application solutions. In fact, due to the capabilities of Internet networking, the use of web-based GIS has rapidly expanded. The first web-based GIS were quite simple, while the user had to collect cartographic data to be used as the geographical background of the system. Today, the web-based GIS systems have reached the level of a fully functional platform, where a user can directly upload, edit and save complex projects. Another characteristic of this new trend is its full integration with data determined by Global Positioning System and Remote Sensing imagery. Moreover, several virtual globe interfaces and geographic visualization applications started to provide the basic cartographic and satellite image background for users. Then, many enterprises offered web-based GIS applications with a variety of tools...

International Journal of Geographical Information Science, 2009

Earth science research and applications usually use Distributed Geospatial Information Processing (DGIP) services and powerful computing capabilities to extract information and knowledge from large volumes of distributed geospatial data. Conceptually, such processing can be abstracted into a logical model that utilizes geospatial domain knowledge to produce new geospatial products. Using this idea, the geo-tree concept and the proposed geospatial Abstract Information Model (AIM) have been used to develop a Grid workflow engine complying with geospatial standards and the Business Process Execution Language. Upon a user's request, the engine generates virtual geospatial data/information/knowledge products from existing DGIP data and services. This article details how to (1) define and describe the AIM in XML format, (2) describe the process logically with an AIM, including the geospatial semantic logic, (3) conceptually describe the process of producing a particular geospatial product step by step from raw geospatial data, (4) instantiate AIM as a concrete Grid-service workflow by selecting the optimal service instances and data sets, and (5) design a Grid workflow engine to execute the concrete workflows to produce geospatial products. To verify the advantages and applicability of this Grid-enabled virtual geospatial product system, its performance is evaluated, and a sample application is provided.

2010

Handbook of Research on Geoinformatics, 2009

With the rapid accumulation of geospatial data and the advancement of geoscience, there is a critical requirement for an infrastructure that can integrate large-scale, heterogeneous, and distributed storage systems for the sharing of geospatial data within multiple user communities. This article probes into the feasibility to share distributed geospatial data through Grid computing technology by introducing several major issues (including system heterogeneity, uniform mechanism to publish and discover geospatial data, performance, and security) to be faced by geospatial data sharing and how Grid technology can help to solve these issues. Some recent research efforts, such as ESG and the Data Grid system in GMU CSISS, have proven that Grid technology provides a large-scale infrastructure which can seamlessly integrate dispersed geospatial data together and provide uniform and efficient ways to access the data.

Computers & Geosciences, 2014

Data semantics play an extremely significant role in spatial data infrastructures by providing semantic specifications to geospatial data and enabling in this way data sharing and interoperability. By applying, on the fly, composite geospatial processes on the above data it is possible to produce valuable geoinformation over the web directly available and applicable to a wide range of geo-activities of significant importance for the research and industry community. Cloud computing may enable geospatial processing since it refers to, among other things, efficient computing resources providing on demand processing services. In this context, we attempt to provide a design and architectural framework for web applications based on open geospatial standards. Our approach includes, in addition to geospatial processing, data acquisition services that are essential especially when dealing with satellite images and applications in the area of remote sensing and similar fields. As a result, by putting in a common framework all data and geoprocesses available in the Cloud, it is possible to combine the appropriate services in order to produce a solution for a specific need.

2005-03-11]. http:// …, 2005

acquiring, processing and sharing geo-data among interested parties. In order to serve geographical information to users in such environment, Service Oriented Architecture (SOA) principles have gained great importance. In SOA-based systems, Information Services support the discovery and handling of these geospatial services.