Catálogo de publicaciones - libros

The Advanced Fire Information System (AFIS) is a joint initiative between CSIR and Eskom, the South African electricity utility. AFIS infers fire occurrences from processed, remotely sensed data and triggers alarms to Eskom operators based on the proximity of fire events to Eskom's infrastructure. We intend on migrating AFIS from a narrowly focussed “black-box” application to one servicing users in multiple fire-related scenarios, enabling rapid development and deployment of new applications through concept-based queries of data and knowledge repositories. Future AFIS versions would supply highly tuned, meaningful and customized fire alerts to users based on an open framework of Geo-spatial Web services, ontologies and software agents. Other Geospatial Web applications may have to follow a similar path via Web services and standards-based architectures, thereby providing the foundation for the Geospatial Web.

Geographic information is a valuable resource for applications and analysis where location of objects and events can enhance policy, land use and decision-making activities. Interoperability has been an ongoing activity of the geodata user community for decades, focusing on formats and standards. The recent popularity and adoption of the Internet and Web Services have provided a new means of interoperability for geodata, differing from previous approaches to information exchange. This chapter provides an overview of Geospatial Web Services as better methods to achieve efficient data exchange. The emerging Web 2.0 phenomenon is also discussed in the context of this approach.

The ability to represent geospatial semantics is of great importance when building geospatial applications for the Web. The Semantic Web Service (SWS) technology provides solutions for intelligent service annotation, discovery, composition and invocation in distributed environments. Deploying this technology into geospatial Web applications has the potential to enhance discovery, retrieval and integration of geographic information, as well as its reuse in various contexts. This chapter gives an overview of the SWING research framework, which is aimed at investigating the applicability of semantic technologies in the area of geo-spatial services. The goal is to provide a semantic framework that facilitates the employment of geospatial services to solve a specific task in geo-spatial decision making. In this chapter, we emphasize the motivation and the challenges for such a framework, point out the main components and highlight its potential impact.

What prevents the Geospatial Web from taking off is not a missing architecture and protocol stack but, beside other aspects, the question of how Web services can be semi-automatically discovered and whether and to what degree they satisfy user requirements. Two approaches turned out to be useful for semantic-enabled geospatial information retrieval: subsumption reasoning and similarity measurement. However, while the former one can be applied to query service ontologies described in OWL-S or WSMO/WSML, most existing similarity theories are not able to cope with logic-based service descriptions. This chapter presents initial results in developing a directed and context-aware similarity measure that compares WSML concept descriptions for overlap and therefore supports retrieval within the upcoming Geospatial Web.

Geographic space still lacks the semantics allowing a unified view of spatial data. Indeed, as a unique but all encompassing domain, it presents specificities that geospatial applications are still unable to handle. Moreover, to be useful, new spatial applications need to match human cognitive abilities of spatial representation and reasoning. In this context, eMerges, an approach to geospatial data integration based on Semantic Web Services (SWS), allows the unified representation and manipulation of heterogeneous spatial data sources. eMerges provides this integration by mediating legacy spatial data sources to high-level spatial ontologies through SWS and by presenting for each object context dependent affordances. This generic approach is applied here in the context of an emergency management use case developed in collaboration with emergency planners of public agencies.