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Reasoning Geo-Spatial Neutral Similarity from Seismic Data Using Mixture and State Clustering Models Read chapter Read first chapter

2016 | OriginalPaper | Chapter

Using Linked Open Data in Geographical Information Systems

Authors : Patricia Carolina Neves Azevedo, Vitor Afonso Pinto, Guilherme Sousa Bastos, Fernando Silva Parreiras

Published in: Geographical Information Systems Theory, Applications and Management

Publisher: Springer International Publishing

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Abstract

Linked Open Data is becoming increasingly important for Geographical Information Systems because most of the sources available on the Web are free of charge. In this work, we present an approach for integrating heterogeneous data located in various public organizations. We address the concepts and technologies which allow for visualizing flood information available from linked open data sources using geographical information systems. The proposed approach adds to the decision-making process, specially in the context of minimizing damage caused by floods. This work also contributes to reducing costs to obtain information beyond organization boundaries by using Semantic Web technologies.

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previous chapter Using Conditional Probability and a Nonlinear Kriging Technique to Predict Potato Early Die Caused by Verticllium Dahliae
Footnotes
1
As systems databases make use of SQL to query records in databases, SPARQL is a query language for retrieving information in RDF graphs [15].
 
2
Resource Description Framework (RDF) is a language for representing information on the Web and designed for situations where information needs to be processed by applications, rather than simply being shown to people [14].
 
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Metadata
Title
Using Linked Open Data in Geographical Information Systems
Authors
Patricia Carolina Neves Azevedo
Vitor Afonso Pinto
Guilherme Sousa Bastos
Fernando Silva Parreiras
Copyright Year
2016
Book
Geographical Information Systems Theory, Applications and Management

Print ISBN: 978-3-319-29588-6

Electronic ISBN: 978-3-319-29589-3

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-29589-3_10

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