Computational Techniques in Visual Analytics
Visual analytics approaches combine interactive visualisations with the use of computational techniques for data processing and analysis. Combining visualisation and computation has two sides. One side is computational support to visual analysis: outcomes
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ytics for Data Scientists
Visual Analytics for Data Scientists
Natalia Andrienko • Gennady Andrienko Georg Fuchs • Aidan Slingsby • Cagatay Turkay Stefan Wrobel
Visual Analytics for Data Scientists
Natalia Andrienko Fraunhofer Institute Intelligent Analysis and Information Systems IAIS Schloss Birlinghoven Sankt Augustin, Germany
Gennady Andrienko Fraunhofer Institute Intelligent Analysis and Information Systems IAIS Schloss Birlinghoven Sankt Augustin, Germany
Department of Computer Science City, University of London Northampton Square, London, UK
Department of Computer Science City, University of London Northampton Square, London, UK
Georg Fuchs Fraunhofer Institute Intelligent Analysis and Information Systems IAIS Schloss Birlinghoven Sankt Augustin, Germany
Aidan Slingsby Department of Computer Science City, University of London Northampton Square, London, UK
Cagatay Turkay Centre for Interdisciplinary Methodologies University of Warwick Coventry, UK
Stefan Wrobel Fraunhofer Institute Intelligent Analysis and Information Systems IAIS Schloss Birlinghoven Sankt Augustin, Germany University of Bonn Bonn, Germany
ISBN 978-3-030-56146-8 (eBook) ISBN 978-3-030-56145-1 https://doi.org/10.1007/978-3-030-56146-8 © Springer Nature Switzerland AG 2020 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, expressed 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. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland
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Preface
There are several disciplines concerned with developing computer-oriented methods for data analysis: statistics, machine learning, data mining, as well as disciplines specific to various application domains, such as geographic information science, microbiology, or astronomy. Until recent years, it was customary to believe in num
