Data management for social scientists from files to databases Nils B. Weidmann

Format:

Book

Author/Creator:

Weidmann, Nils B., 1976- author.

Series:

Methodological tools in the social sciences

Language:

English

Subjects (All):

Social sciences--Research.

Social sciences.

Social sciences--Data processing.

Physical Description:

1 online resource

Place of Publication:

Cambridge Cambridge University Press 2023

Summary:

Much training in quantitative social science focuses on data analysis and fails to equip researchers with the skills to prepare the data required for this. This book is a comprehensive introduction to simple and advanced tools for data management, drawing on established concepts and techniques from computer science

Contents:

Cover

Half-title

Series information

Title page

Copyright information

Dedication

Contents

Preface

Part I Introduction

1 Motivation

1.1 Data Processing and the Research Cycle

1.2 What We Do (and Don't Do) in this Book

1.3 Why Focus on Data Processing?

1.4 Data in Files vs. Data in Databases

1.5 Target Audience, Requirements and Software

1.6 Plan of the Book

2 Gearing Up

2.1 R and RStudio

2.2 Setting Up the Project Environment for Your Work

2.3 The PostgreSQL Database System

2.4 Summary and Outlook

3 Data = Content + Structure

3.1 What Is Data?

3.2 Data Content and Structure

3.3 Tables, Tables, Tables

3.4 The Structure of Tables Matters

3.5 Summary and Outlook

Part II Data in Files

4 Storing Data in Files

4.1 Text and Binary Files

4.2 File Formats for Tabular Data

4.3 Transparent and Efficient Use of Files

4.4 Summary and Outlook

5 Managing Data in Spreadsheets

5.1 Application: Spatial Inequality

5.2 Spreadsheet Tables and (the Lack of) Structure

5.3 Retrieving Data from a Table

5.4 Changing Table Structure and Content

5.5 Aggregating Data from a Table

5.6 Exporting Spreadsheet Data

5.7 Results: Spatial Inequality

5.8 Summary and Outlook

6 Basic Data Management in R

6.1 Application: Inequality and Economic Performance in the US

6.2 Loading the Data

6.3 Merging Tables

6.4 Aggregating Data from a Table

6.5 Results: Inequality and Economic Performance in the US

6.6 Summary and Outlook

7 R and the tidyverse

7.1 Application: Global Patterns of Inequality across Regime Types

7.2 A New Operator: The Pipe

7.3 Loading the Data

7.4 Merging the WID and Polity IV Datasets

7.5 Grouping and Aggregation

7.6 Results: Global Patterns of Inequality across Regime Types

7.7 Other Useful Functions in the tidyverse

7.8 Summary and Outlook

Part III Data in Databases

8 Introduction to Relational Databases

8.1 Database Servers and Clients

8.2 SQL Basics

8.3 Application: Electoral Disproportionality by Country

8.4 Creating a Table with National Elections

8.5 Computing Electoral Disproportionality

8.6 Results: Electoral Disproportionality by Country

8.7 Summary and Outlook

9 Relational Databases and Multiple Tables

9.1 Application: The Rise of Populism in Europe

9.2 Adding the Tables

9.3 Joining the Tables

9.4 Merging Data from the PopuList

9.5 Maintaining Referential Integrity

9.6 Results: The Rise of Populism in Europe

9.7 Summary and Outlook

10 Database Fine-Tuning

10.1 Speeding Up Data Access with Indexes

10.2 Collaborative Data Management with Multiple Users

10.3 Summary and Outlook

Part IV Special Types of Data

11 Spatial Data

11.1 What Is Spatial Data?

11.2 Application: Patterns of Violence in the Bosnian Civil War

11.3 Reading and Visualizing Spatial Data in R

11.4 Spatial Data in a Relational Database

11.5 Results: Patterns of Violence in the Bosnian Civil War

11.6 Summary and Outlook

12 Text Data

12.1 What Is Textual Data?

12.2 Application: References to (In)equality in UN Speeches

12.3 Working with Strings in (Base) R

12.4 Natural Language Processing with quanteda

12.5 Using PostgreSQL to Manage Documents

12.6 Results: References to (In)equality in UN Speeches

12.7 Summary and Outlook

13 Network Data

13.1 What Is Network Data?

13.2 Application: Trade and Democracy

13.3 Exploring Network Data in R with igraph

13.4 Network Data in a Relational Database

13.5 Results: Trade and Democracy

13.6 Summary and Outlook

Part V Conclusion

14 Best Practices in Data Management

14.1 Two General Recommendations

14.2 Collaborative Data Management

14.3 Disseminating Research Data and Code

14.4 Summary and Outlook

Bibliography

Index

Notes:

Also issued in print: 2023

Includes bibliographical references and index

Description based on online resource; title from PDF title page (viewed on April 11, 2023)

Vendor-supplied metadata

Other Format:

ebook version :

ISBN:

1108990428

9781108990424

OCLC:

1376019195

Access Restriction:

Restricted for use by site license