Geospatial Data Science ? A Hands?on Approach for Building Geospatial Applications using Linked Data Technologies

Manolis Koubarakis

ISBN 13: 9798400707407

Published by John Wiley & Sons, John Wiley & Sons, 2023

About this Item

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Seller Inventory # 9798400707407

Bibliographic Details

• Title: Geospatial Data Science ? A Hands?on Approach for Building Geospatial Applications using Linked Data Technologies
• Publisher: John Wiley & Sons, John Wiley & Sons
• Publication Date: 2023
• Language: English
• ISBN 13: 9798400707407
• Binding: Buch
• Condition: Neu
• Dimensions: 235W x 191H x 23D millimeters 235 millimeters width by 191 millimeters height by 23 millimeters depth
• Weight: 756 grams

About this title

Synopsis

This introductory textbook teaches the simple development of geospatial applications based on the principles and software tools of geospatial data science. It introduces a new generation of geospatial technologies that have emerged from the development of the Semantic Web and the linked data paradigm, and shows how data scientists can use them to build environmental applications easily.

Geospatial data science is the science of collecting, organizing, analyzing, and visualizing geospatial data. Since around 2010, there has been extensive work in the area of geospatial data science using semantic technologies and linked data, from researchers in the areas of the Semantic Web, Geospatial Databases and Geoinformatics. The main results of this research have been the publication of the OGC standard GeoSPARQL and the implementation of a number of linked data tools supporting this standard. Up to now, there has been no textbook that enables someone to teach this material to undergraduate or graduate students.

The material of the book is developed in a tutorial style and it is appropriate for an introductory course on the subject. This can be an advanced undergraduate course or a graduate course offered by Computer Science or GIS faculty. It is a hands-on approach and every chapter contains exercises that help students master the material.

The book is accompanied by a Web site: https://ai.di.uoa.gr/geospatial-data-science-book/index.html where solutions to some of the exercises are given together with supplementary material such as datasets and code. Most of the material in the book has been tried in the “Knowledge Technologies” course taught by the first author in the Department of Informatics and Telecommunications of the National and Kapodistrian University of Athens since 2012.