Data Management for Social Scientists: From Files to Databases

Nils B. Weidmann

doi:10.1017/9781108990424

Data Management for Social Scientists

From Files to Databases

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Hertz, Marla I. McNeill, Ashley S. and Ouellette, B.F. Francis 2024. Eleven quick tips for properly handling tabular data. PLOS Computational Biology, Vol. 20, Issue. 11, p. e1012604.

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Goben, Abigail and Briney, Kristin 2025. Data Management Books for Researchers - An Annotated Bibliography. Research Ideas and Outcomes, Vol. 11, Issue. ,

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Nils B. Weidmann, Universität Konstanz, Germany

Publisher:: Cambridge University Press
Online publication date:: March 2023
Print publication year:: 2023
Online ISBN:: 9781108990424
DOI:: https://doi.org/10.1017/9781108990424
Creative Commons:: This content is Open Access and distributed under the terms of the Creative Commons Attribution licence CC-BY-NC 4.0 https://creativecommons.org/creativelicenses

Subjects:: Political Theory, Research Methods in Politics, Statistical Theory and Methods, Politics and International Relations, Research Methods In Politics
Series:: Methodological Tools in the Social Sciences

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The 'data revolution' offers many new opportunities for research in the social sciences. Increasingly, social and political interactions can be recorded digitally, leading to vast amounts of new data available for research. This poses new challenges for organizing and processing research data. This comprehensive introduction covers the entire range of data management techniques, from flat files to database management systems. It demonstrates how established techniques and technologies from computer science can be applied in social science projects, drawing on a wide range of different applied examples. This book covers simple tools such as spreadsheets and file-based data storage and processing, as well as more powerful data management software like relational databases. It goes on to address advanced topics such as spatial data, text as data, and network data. This book is one of the first to discuss questions of practical data management specifically for social science projects. This title is also available as Open Access on Cambridge Core.

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