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Mobility data science = from data to...

Sakr, Mahmoud.

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Mobility data science = from data to insights /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Mobility data science/ by Mahmoud Sakr, Alejandro Vaisman, Esteban Zimányi.
Reminder of title:	from data to insights /
Author:	Sakr, Mahmoud.
other author:	Vaisman, Alejandro.
Published:	Cham :Springer Nature Switzerland : : 2025.,
Description:	xxii, 592 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	Preface -- Part I Fundamental Concepts 1 Mobility Data Science 2 Spatial, Temporal, and Mobility Databases 3 Mobility Data Representation 4 Mobility Data Visualization 5 Querying Mobility Databases -- Part II Advanced Topics 6 Query Processing and Indexing 7 Mobility Data Warehouses 8 Distributed Mobility Databases -- Part III Mobility Analytics 9 Mobility Data Cleaning 10 Mobility Data Analysis 11 Urban Mobility Use Case 12 Concluding Remarks.
Contained By:	Springer Nature eBook
Subject:	Data mining. -
Online resource:	https://doi.org/10.1007/978-3-031-82636-8
ISBN:	9783031826368

Mobility data science = from data to insights /
Sakr, Mahmoud.

Mobility data sciencefrom data to insights /[electronic resource] :by Mahmoud Sakr, Alejandro Vaisman, Esteban Zimányi. - Cham :Springer Nature Switzerland :2025. - xxii, 592 p. :ill. (some col.), digital ;24 cm. - Data-centric systems and applications,2197-974X. - Data-centric systems and applications..

Preface -- Part I Fundamental Concepts 1 Mobility Data Science 2 Spatial, Temporal, and Mobility Databases 3 Mobility Data Representation 4 Mobility Data Visualization 5 Querying Mobility Databases -- Part II Advanced Topics 6 Query Processing and Indexing 7 Mobility Data Warehouses 8 Distributed Mobility Databases -- Part III Mobility Analytics 9 Mobility Data Cleaning 10 Mobility Data Analysis 11 Urban Mobility Use Case 12 Concluding Remarks.

This textbook covers the key topics in mobility data analysis, including all steps of the data science pipeline illustrated with real-world examples. The book is composed of three parts. Part I "Fundamental Concepts" provides the background for this book by introducing spatial and temporal databases and motivating the need for mobility databases. Further chapters in this part are devoted to a formal model for representing mobility data, an introduction to mobility data visualization, and the topic of querying mobility databases. Part II "Advanced Topics" covers topics such as query processing and indexing, illustrated with PostgreSQL, introduces mobility data warehouses using synthetic data, and concludes with distributed mobility databases. Part III "Mobility Analytics" covers important topics like mobility data cleaning, including the identification of erroneous data, and mobility analysis using foundational algorithms for spatial and mobility data. It also includes an urban mobility use case that illustrates the concepts presented throughout the book in a real application setting. This textbook is written for undergraduate and graduate computer science courses on mobility data science. As such, it follows a pedagogical style to make the work of the instructor easier and to help students to understand the concepts being delivered, complementing the presentation with exercises and a companion GitHub repository. SQL is used as a high-level language for analytics, allowing students to write complex data science code, while abstracting away implementation details. Researchers and practitioners who are interested in an introduction to the area of mobility data science will also find the book a useful reference.

ISBN: 9783031826368

Standard No.: 10.1007/978-3-031-82636-8doiSubjects--Topical Terms:

562972
Data mining.

LC Class. No.: QA746.9.D343

Dewey Class. No.: 006.312

Mobility data science = from data to insights /
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505 0 $a Preface -- Part I Fundamental Concepts 1 Mobility Data Science 2 Spatial, Temporal, and Mobility Databases 3 Mobility Data Representation 4 Mobility Data Visualization 5 Querying Mobility Databases -- Part II Advanced Topics 6 Query Processing and Indexing 7 Mobility Data Warehouses 8 Distributed Mobility Databases -- Part III Mobility Analytics 9 Mobility Data Cleaning 10 Mobility Data Analysis 11 Urban Mobility Use Case 12 Concluding Remarks.
520 $a This textbook covers the key topics in mobility data analysis, including all steps of the data science pipeline illustrated with real-world examples. The book is composed of three parts. Part I "Fundamental Concepts" provides the background for this book by introducing spatial and temporal databases and motivating the need for mobility databases. Further chapters in this part are devoted to a formal model for representing mobility data, an introduction to mobility data visualization, and the topic of querying mobility databases. Part II "Advanced Topics" covers topics such as query processing and indexing, illustrated with PostgreSQL, introduces mobility data warehouses using synthetic data, and concludes with distributed mobility databases. Part III "Mobility Analytics" covers important topics like mobility data cleaning, including the identification of erroneous data, and mobility analysis using foundational algorithms for spatial and mobility data. It also includes an urban mobility use case that illustrates the concepts presented throughout the book in a real application setting. This textbook is written for undergraduate and graduate computer science courses on mobility data science. As such, it follows a pedagogical style to make the work of the instructor easier and to help students to understand the concepts being delivered, complementing the presentation with exercises and a companion GitHub repository. SQL is used as a high-level language for analytics, allowing students to write complex data science code, while abstracting away implementation details. Researchers and practitioners who are interested in an introduction to the area of mobility data science will also find the book a useful reference.
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