The Data Economy: Implications from Singapore: Routledge Research in Public Administration and Public Policy
Autor Sree Kumar, Warren Chik, See-Kiong Ng, Sin Gee Teoen Limba Engleză Paperback – 30 iun 2020
This book outlines the findings and conclusions of a multidisciplinary team of data scientists, lawyers, and economists tasked with studying both the possibilities of exploiting the rich data sets made available from many human–technology interactions and the practical and legal limitations of trying to do so. It revolves around a core case study of Singapore’s public transport system, using data from both the private company operating the contactless payment system (EZ-Link) and the government agency responsible for public transport infrastructure (Land Transport Authority). In analysing both the possibilities and the limitations of these data sets, the authors propose policy recommendations in terms of both the uses of large data sets and the legislation necessary to enable these uses while protecting the privacy of users.
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Paperback (1) | 140.98 lei 6-8 săpt. | |
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Specificații
ISBN-13: 9780367606718
ISBN-10: 0367606712
Pagini: 126
Dimensiuni: 138 x 216 mm
Greutate: 0.45 kg
Ediția:1
Editura: Taylor & Francis
Colecția Routledge
Seria Routledge Research in Public Administration and Public Policy
Locul publicării:Oxford, United Kingdom
ISBN-10: 0367606712
Pagini: 126
Dimensiuni: 138 x 216 mm
Greutate: 0.45 kg
Ediția:1
Editura: Taylor & Francis
Colecția Routledge
Seria Routledge Research in Public Administration and Public Policy
Locul publicării:Oxford, United Kingdom
Public țintă
Postgraduate and UndergraduateCuprins
Foreword
Acknowledgement
1. Introduction
2. An Outline of the Data Economy
3. The Search for Data
4. The Analysis of Data
5. The Legal Contours of the Data Economy
6. Redefining the Data Economy
7. Implications for the Future
Selected Bibliography
Index
Acknowledgement
1. Introduction
2. An Outline of the Data Economy
3. The Search for Data
4. The Analysis of Data
5. The Legal Contours of the Data Economy
6. Redefining the Data Economy
7. Implications for the Future
Selected Bibliography
Index
Notă biografică
Sree Kumar is a Director of Sreekumar Siddique & Co., a regional research and consulting firm based in Singapore. At the Lee Kuan Yew Centre for Innovative Cities, he is an Adjunct Senior Fellow. Mr Kumar holds degrees in law, economics, English, management, and engineering from universities in the United Kingdom and Singapore. He has been called to the Bar of England and Wales and has an interest in international tax and investment law. He is a Fellow of the Royal Statistical Society.
Warren B. Chik is an Associate Professor in the School of Law at Singapore Management University. He obtained his LLB from National Univeristy of Singapore Law School and his master's degrees from Tulane University and University College London. Associate Professor Chik has been called to the Bar of England and Wales, Singapore, and New York. He currently researches and writes in the areas of information and communications technology and the law, Internet intermediaries, data protection, cybersecurity, and the intersection between intellectual property and information technology law.
See-Kiong Ng is a Professor of Practice at the National University of Singapore's School of Computing and Director of Translational Research for the university's Institute of Data Science. He holds a PhD from Carnegie-Mellon University and is a practising data scientist with diverse and cross-disciplinary research interests. From using data mining to unravel the biology of the human body to applying machine learning to understand the "biology" of complex human cities, See-Kiong aims to push the boundary of data science through trans-disciplinary upstream research and to create impact by translating research outcomes into real-life applications.
Sin Gee Teo is a research scientist at the Institute for Infocomm Research (I2R) in Singapore. He holds a PhD in Computer Science from Monash University, Australia. Before joining I2R, he worked at the Lee Kuan Yew Centre for Innovative Cities, Singapore University of Technology and Design, as a research fellow. His research interests include data privacy, applied cryptography, deep learning, data mining, and cloud computing.
Warren B. Chik is an Associate Professor in the School of Law at Singapore Management University. He obtained his LLB from National Univeristy of Singapore Law School and his master's degrees from Tulane University and University College London. Associate Professor Chik has been called to the Bar of England and Wales, Singapore, and New York. He currently researches and writes in the areas of information and communications technology and the law, Internet intermediaries, data protection, cybersecurity, and the intersection between intellectual property and information technology law.
See-Kiong Ng is a Professor of Practice at the National University of Singapore's School of Computing and Director of Translational Research for the university's Institute of Data Science. He holds a PhD from Carnegie-Mellon University and is a practising data scientist with diverse and cross-disciplinary research interests. From using data mining to unravel the biology of the human body to applying machine learning to understand the "biology" of complex human cities, See-Kiong aims to push the boundary of data science through trans-disciplinary upstream research and to create impact by translating research outcomes into real-life applications.
Sin Gee Teo is a research scientist at the Institute for Infocomm Research (I2R) in Singapore. He holds a PhD in Computer Science from Monash University, Australia. Before joining I2R, he worked at the Lee Kuan Yew Centre for Innovative Cities, Singapore University of Technology and Design, as a research fellow. His research interests include data privacy, applied cryptography, deep learning, data mining, and cloud computing.
Descriere
This book outlines the findings and conclusions of a multi-disciplinary team of data scientists, lawyers and economists tasked with studying both the possibilities of exploiting the rich datasets made available from many human-technology interactions, and the practical and legal limitations in trying to do so.