Spatial Data Infrastructures

Spatial Data Infrastructures

Clodoveu Augusto Davis Jr. (Pontifical Catholic University of Minas Gerais, Brazil)
DOI: 10.4018/978-1-60566-026-4.ch565
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Spatial Data Infrastructures (SDI), also known as Spatial Information Infrastructures (SII), are a set of policies, technologies and standards that interconnect a community of spatial information users and related support activities for production and management of geographic information (Phillips, Williamson, & Ezigbalike, 1999). SDI reduces redundant effort and lowers production costs for new and existent datasets through interoperable information sharing, providing neutral means to access geographic data. Multiple information providers, commercial or public, may cover various interests and compete among themselves for clients. SDIs present several challenges, at various levels of interaction. First, there is a societal and organizational level. Partners in a community should have convergent interests, agree on common rules, and be able to use information produced by others. Such agreements are not easy to achieve, and usually require long-term commitments. Within public organizations, it is usual to think in transnational terms, between national mapping agencies, but intranational relationships are also important. Second, there are standardization issues. Guiding the technology standardization and defining the key elements for SDI, the Open Geospatial Consortium (OGC) has proposed a number of standards, through a framework called OGC Reference Model (Percivall, 2003). Third, there are concerns on specific aspects of geographic information, such as scale (levels of detail, accuracy, uncertainty) and the need to integrate data from various sources. Geographic information from each source needs to be consolidated in order to be valuable to high-level decisionmakers. In this case, SDI can be seen as a set of building blocks, in which hierarchies are built through the exchange and consolidation of information from corporate and local levels, to regional and global levels. In this hierarchy, lower levels (Davis & Alves, 2005) provide detailed information that helps to consolidate the upper, more general, levels (Rajabifard & Williamson, 2001). The integration problem also requires attention to semantics, because data produced by different organizations, for different needs, are not necessarily compatible, even if they refer to the same location or to the same real-world subject. In this particular issue, the development and use of ontologies may be required. Finally, there is a technological level. The exchange of information can occur in several ways, but the most interesting one is the use of Web services, using a service-based architecture approach, thus achieving loosely-­coupled and distributed geographic information systems (Bernard & Craglia, 2005; Davis & Alves, 2005). There are pending issues related to the compatibility between Web service standards defined by the OGC and by the World Wide Web Consortium (W3C), but there are already initiatives to bridge them (Bacharach, 2007; Kim, Kim, Lee, & Joo, 2005). There is also the need to define and propose higherlevel services, so SDI can go beyond the simple discovery and download of geographic data, and provide solutions to location-related problems using multiple and distributed sources of information.
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Creating geographic datasets is a complex and expensive undertaking. In the past, redundant efforts in dataset creation were commonplace: organizations with an interest in the same areas, therefore potential partners for sharing basic data, would not cooperate due to their diverse technological strategies, budgeting, and timing. Of course, such redundancy was undesirable, motivating the creation of cooperation efforts for data sharing.

Key Terms in this Chapter

GML: The Geography Markup Language is a XML grammar defined by the Open Geospatial Consortium (OGC) to adequately express and transfer, in a neutral way, the encoding of geographic features. Its purpose is to foster the integration of geographic data sources.

Service-Oriented Architectures (SOA): Information system architectures in which services encapsulate the exchange of data among modules, which can reside in different points throughout a computer network.

Geographic Information System (GIS): Information systems used to store, analyze, and manipulate geographic data, that is, data that represent objects or phenomena for which the geographic location is an important characteristic.

Web Services: Software applications from which interfaces and bindings are expressed in XML and that can be discovered using XML messages. In the W3C definition, Web services are “a software system designed to support interoperable machine-to-machine interaction over a network.”

Geoportal: A Web site that presents an entry point to geographic content on the Web, used to discover and access geographic information and associated services on the Web.

Spatial Data Clearinghouse: Internet-based components that intend to facilitate access to spatial data, by establishing a centralized site from which data from several sources can be found, and by providing complementary services, including searching, viewing, transferring, and ordering spatial data.

XML: The eXtensible Markup Language is a markup language developed to facilitate the sharing of structured data across different information systems.

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