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Geographic Information has an important role to play in linking and combining datasets through shared location, but the potential is still far from fully realized because the data is not well organized and the technology to aid this process has not been available. Developments in the Semantic Web and Linked Data, however, are making it possible to integrate data based on Geographic Information in a way that is more accessible to users. Drawing on the industry experience of a geographer and a computer scientist, Linked Data: A Geographic Perspective is a practical guide to implementing Geographic Information as Linked Data. Combine Geographic Information from Multiple Sources Using Linked Data After an introduction to the building blocks of Geographic Information, the Semantic Web, and Linked Data, the book explores how Geographic Information can become part of the Semantic Web as Linked Data. In easy-to-understand terms, the authors explain the complexities of modeling Geographic Information using Semantic Web technologies and publishing it as Linked Data. They review the software tools currently available for publishing and modeling Linked Data and provide a framework to help you evaluate new tools in a rapidly developing market. They also give an overview of the important languages and syntaxes you will need to master. Throughout, extensive examples demonstrate why and how you can use ontologies and Linked Data to manipulate and integrate real-world Geographic Information data from multiple sources. A Practical, Readable Guide for Geographers, Software Engineers, and Laypersons A coherent, readable introduction to a complex subject, this book supplies the durable knowledge and insight you need to think about Geographic Information through the lens of the Semantic Web. It provides a window to Linked Data for geographers, as well as a geographic perspective for software engineers who need to understand how to work with Geographic Information. Highlighting best practices, this book helps you organize and publish Geographic Information on the Semantic Web with more confidence.
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Keywords
- assumption
- Computer network resources
- COMPUTERSCIENCE
- Computing & information technology
- consortium
- Data mining
- Data Preparation and Mining
- Data processing
- Databases
- engineering & technology
- ENVIRO
- Environmental Science
- ENVIRONMENTALSCIENCE
- Geographical information systems & remote sensing
- Geography
- Geography, data processing
- geospatial
- GIS, Remote Sensing and Cartography
- Hypertext
- Information technology: general issues
- INFORMATIONSCIENCE
- Internet and Multimedia
- Internet: general works
- ITECH
- Language
- Ontology
- open
- SCI-TECH
- Semantic
- Semantic Web
- STM
- Web
- world
- World Wide Web
Links
DOI: 10.1201/b13877Editions