Enhancing the Efficiency of ICT by Spatial Data Interoperability

Enhancing the Efficiency of ICT by Spatial Data Interoperability

Otakar Cerba (University of West Bohemia, Czech Republic), Karel Charvat (Czech Center for Science and Society, Czech Republic), Jan Jezek (University of West Bohemia, Czech Republic) and Stepan Kafka (HELP SERVICE – REMOTE SENSING spol. s.r.o., Czech Republic)
DOI: 10.4018/978-1-60960-472-1.ch504
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Abstract

In the present world of information and communication technologies (ICT) “Green ICT” represents a topic of immense interest. The meaning, sense and scope of Green ICT are quite varied and very wide. Hardware technologies, for example (virtualization of hardware) and corresponding methods are considered initiatives towards environment protection and sustainable growth. At the same time, however, improved development and implementation of existing tools influencing environment by implication (for example due to reducing travel costs or energy savings) are very important in terms of Green ICT. ICT solutions could also work as a device or medium of implementation of new environmentally friendly methods, for instance in agriculture or industry. Spatial data or data with a direct or indirect reference to a specific location or geographic area (INSPIRE Registry, 2009), like digital maps, data in navigation tools, are a significant means of correlating otherwise disparate sources of information. This chapter tries to show the relationship of spatial data and how it can benefit Green ICT. This relationship is vital, as spatial data plays a very important role in system and application (e.g. Geographic Information Systems) with the potential for making direct impact on environmental protection. Spatial data continues to be an integral part of common equipment like mobile phones, car navigation systems and computers. The numbers of these gadgets are constantly growing and so is the corresponding volume of spatial data sets. Within the context of this rapid growth, the costs of data capture, management, updating, processing and distribution are increasing. For example the operation of servers containing the same spatial data sets is energy-consuming and results in burdening the influence on environment. Spatial data sharing, re-use and possibilities of interconnection of existing spatial data sources pose a solution. Therefore, the spatial data interoperability assurance (e.g. by private spatial data providers, state administration etc.) is required. The spatial data interoperability enables more efficient management and use of spatial data sets and achieving of desired savings.The principles of spatial data interoperability are described in the first part of this document. Emphasis is put on spatial data heterogeneities as the main problem of spatial data interoperability. Moreover, technologies focused on elimination of spatial data heterogeneities are discussed here. Subsequent paragraphs introduce selected instruments (metadata, schema languages, ontologies) which are based on data description and support data interoperability. The last section of this document is composed of examples of several international projects focused on spatial data description and processing of well-described spatial data through web services.
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Abstract

In the present world of information and communication technologies (ICT) “Green ICT” represents a topic of immense interest. The meaning, sense and scope of Green ICT are quite varied and very wide. Hardware technologies, for example (virtualization of hardware) and corresponding methods are considered initiatives towards environment protection and sustainable growth. At the same time, however, improved development and implementation of existing tools influencing environment by implication (for example due to reducing travel costs or energy savings) are very important in terms of Green ICT. ICT solutions could also work as a device or medium of implementation of new environmentally friendly methods, for instance in agriculture or industry. Spatial data or data with a direct or indirect reference to a specific location or geographic area (INSPIRE Registry, 2009), like digital maps, data in navigation tools, are a significant means of correlating otherwise disparate sources of information. This chapter tries to show the relationship of spatial data and how it can benefit Green ICT. This relationship is vital, as spatial data plays a very important role in system and application (e.g. Geographic Information Systems) with the potential for making direct impact on environmental protection. Spatial data continues to be an integral part of common equipment like mobile phones, car navigation systems and computers. The numbers of these gadgets are constantly growing and so is the corresponding volume of spatial data sets. Within the context of this rapid growth, the costs of data capture, management, updating, processing and distribution are increasing. For example the operation of servers containing the same spatial data sets is energy-consuming and results in burdening the influence on environment. Spatial data sharing, re-use and possibilities of interconnection of existing spatial data sources pose a solution. Therefore, the spatial data interoperability assurance (e.g. by private spatial data providers, state administration etc.) is required. The spatial data interoperability enables more efficient management and use of spatial data sets and achieving of desired savings.The principles of spatial data interoperability are described in the first part of this document. Emphasis is put on spatial data heterogeneities as the main problem of spatial data interoperability. Moreover, technologies focused on elimination of spatial data heterogeneities are discussed here. Subsequent paragraphs introduce selected instruments (metadata, schema languages, ontologies) which are based on data description and support data interoperability. The last section of this document is composed of examples of several international projects focused on spatial data description and processing of well-described spatial data through web services.

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