Statistical Disclosure Control for Microdata Methods and Application
This book on statistical disclosure control presents the theory, applications and software implementation of the traditional approach to (micro)data anonymization, including data perturbation methods, disclosure risk, data utility, information loss and me
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Statistical Disclosure Control for Microdata Methods and Applications in R
Statistical Disclosure Control for Microdata
Matthias Templ
Statistical Disclosure Control for Microdata Methods and Applications in R
123
Matthias Templ Institute of Data Analysis and Process Design (IDP) School of Engineering (SoE) Zurich University of Applied Sciences (ZHAW) Winterthur, Switzerland and data-analysis OG Vienna, Austria www.data-analysis.at
ISBN 978-3-319-50270-0 DOI 10.1007/978-3-319-50272-4
ISBN 978-3-319-50272-4
(eBook)
Library of Congress Control Number: 2017937274 Mathematics Subject Classification (2010): 62D99, 62D05, 62-07, 62J05, 62P25 © Springer International Publishing AG 2017 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Printed on acid-free paper This Springer imprint is published by Springer Nature The registered company is Springer International Publishing AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland
To all who raised my interest in writing this book by not believing in our work and the success of free and open-source philosophy.
Preface
Introduction An increasing amount of data on persons and establishments are collected by statistical organizations. Also, the demand for microdata for researchers is increasing since economic or empirical analysis, and to make statements about our society on empirical basis is often only possible when investigating in data with detailed information. Moreover, a considerable increase in the production of socioeconomic data and their accessibility by researchers have been observed in recent years. Statistical agencies are making more of their survey and census microdata available, government agencies are publishing more of their administrative data, and the private sector has become a major provider of big data. This, however, comes with a variety of legal, ethical, and techn
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