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Data Feminism (Strong Ideas)
by Lauren F. Klein Catherine D'IgnazioA new way of thinking about data science and data ethics that is informed by the ideas of intersectional feminism. Today, data science is a form of power. It has been used to expose injustice, improve health outcomes, and topple governments. But it has also been used to discriminate, police, and surveil. This potential for good, on the one hand, and harm, on the other, makes it essential to ask: Data science by whom? Data science for whom? Data science with whose interests in mind? The narratives around big data and data science are overwhelmingly white, male, and techno-heroic. In Data Feminism, Catherine D'Ignazio and Lauren Klein present a new way of thinking about data science and data ethics—one that is informed by intersectional feminist thought.Illustrating data feminism in action, D'Ignazio and Klein show how challenges to the male/female binary can help challenge other hierarchical (and empirically wrong) classification systems. They explain how, for example, an understanding of emotion can expand our ideas about effective data visualization, and how the concept of invisible labor can expose the significant human efforts required by our automated systems. And they show why the data never, ever “speak for themselves.”Data Feminism offers strategies for data scientists seeking to learn how feminism can help them work toward justice, and for feminists who want to focus their efforts on the growing field of data science. But Data Feminism is about much more than gender. It is about power, about who has it and who doesn't, and about how those differentials of power can be challenged and changed.
Data Fusion Mathematics: Theory and Practice
by Jitendra R. RaolFills the Existing Gap of Mathematics for Data FusionData fusion (DF) combines large amounts of information from a variety of sources and fuses this data algorithmically, logically and, if required intelligently, using artificial intelligence (AI). Also, known as sensor data fusion (SDF), the DF fusion system is an important component for use in va
Data Fusion and Data Mining for Power System Monitoring
by Arturo Román MessinaData Fusion and Data Mining for Power System Monitoring provides a comprehensive treatment of advanced data fusion and data mining techniques for power system monitoring with focus on use of synchronized phasor networks. Relevant statistical data mining techniques are given, and efficient methods to cluster and visualize data collected from multiple sensors are discussed. Both linear and nonlinear data-driven mining and fusion techniques are reviewed, with emphasis on the analysis and visualization of massive distributed data sets. Challenges involved in realistic monitoring, visualization, and analysis of observation data from actual events are also emphasized, supported by examples of relevant applications. Features Focuses on systematic illustration of data mining and fusion in power systems Covers issues of standards used in the power industry for data mining and data analytics Applications to a wide range of power networks are provided including distribution and transmission networks Provides holistic approach to the problem of data mining and data fusion using cutting-edge methodologies and technologies Includes applications to massive spatiotemporal data from simulations and actual events
Data Governance: A Guide
by Dimitrios SargiotisThis book is a comprehensive resource designed to demystify the complex world of data governance for professionals across various sectors. This guide provides in-depth insights, methodologies, and best practices to help organizations manage their data effectively and securely. It covers essential topics such as data quality, privacy, security, and management ensuring that readers gain a holistic understanding of how to establish and maintain a robust data governance framework. Through a blend of theoretical knowledge and practical applications, this book addresses the challenges and benefits of data governance, equipping readers with the tools needed to navigate the evolving data landscape. In addition to foundational principles, this book explores real-world case studies that illustrate the tangible benefits and common pitfalls of implementing data governance. Emerging trends and technologies, including artificial intelligence, machine learning, and blockchain are also examined to prepare readers for future developments in the field. Whether you are a seasoned data management professional or new to the discipline, this book serves as an invaluable resource for mastering the intricacies of data governance and leveraging data as a strategic asset for organizational success. This resourceful guide targets data management professionals, IT managers, Compliance officers, Data Stewards, Data Owners Data Governance Managers and more. Business leaders, business executives academic researchers, students focused on computer science in data-related fields will also find this book a useful resource.
Data Grab: The New Colonialism of Big Tech and How to Fight Back
by Nick Couldry Ulises A. MejiasA compelling argument that the extractive practices of today’s tech giants are the continuation of colonialism—and a crucial guide to collective resistance. Large technology companies like Meta, Amazon, and Alphabet have unprecedented access to our daily lives, collecting information when we check our email, count our steps, shop online, and commute to and from work. Current events are concerning—both the changing owners (and names) of billion-dollar tech companies and regulatory concerns about artificial intelligence underscore the sweeping nature of Big Tech’s surveillance and the influence such companies hold over the people who use their apps and platforms. As trusted tech experts Ulises A. Mejias and Nick Couldry show in this eye-opening and convincing book, this vast accumulation of data is not the accidental stockpile of a fast-growing industry. Just as nations stole territories for ill-gotten minerals and crops, wealth, and dominance, tech companies steal personal data important to our lives. It’s only within the framework of colonialism, Mejias and Couldry argue, that we can comprehend the full scope of this heist. Like the land grabs of the past, today’s data grab converts our data into raw material for the generation of corporate profit against our own interests. Like historical colonialism, today’s tech corporations have engineered an extractive form of doing business that builds a new social and economic order, leads to job precarity, and degrades the environment. These methods deepen global inequality, consolidating corporate wealth in the Global North and engineering discriminatory algorithms. Promising convenience, connection, and scientific progress, tech companies enrich themselves by encouraging us to relinquish details about our personal interactions, our taste in movies or music, and even our health and medical records. Do we have any other choice? Data Grab affirms that we do. To defy this new form of colonialism we will need to learn from previous forms of resistance and work together to imagine entirely new ones. Mejias and Couldry share the stories of voters, workers, activists, and marginalized communities who have successfully opposed unscrupulous tech practices. An incisive discussion of the digital media that’s transformed our world, Data Grab is a must-read for anyone concerned about privacy, self-determination, and justice in the internet age.
Data Integration in the Life Sciences: 13th International Conference, Dils 2018, Hannover, Germany, November 20-21, 2018, Proceedings (Lecture Notes in Computer Science #11371)
by Maria-Esther Vidal Sören AuerThis book constitutes revised selected papers from the 13th International Conference on Data Integration in the Life Sciences, DILS 2018, held in Hannover, Germany, in November 2018. The 5 full, 8 short, 3 poster and 4 demo papers presented in this volume were carefully reviewed and selected from 22 submissions. The papers are organized in topical sections named: big biomedical data integration and management; data exploration in the life sciences; biomedical data analytics; and big biomedical applications.
Data Intelligence and Cognitive Informatics: Proceedings of ICDICI 2020 (Algorithms for Intelligent Systems)
by Selwyn Piramuthu I. Jeena Jacob Selvanayaki Kolandapalayam Shanmugam Przemyslaw Falkowski-GilskiThis book discusses new cognitive informatics tools, algorithms and methods that mimic the mechanisms of the human brain which lead to an impending revolution in understating a large amount of data generated by various smart applications. The book is a collection of peer-reviewed best selected research papers presented at the International Conference on Data Intelligence and Cognitive Informatics (ICDICI 2020), organized by SCAD College of Engineering and Technology, Tirunelveli, India, during 8–9 July 2020. The book includes novel work in data intelligence domain which combines with the increasing efforts of artificial intelligence, machine learning, deep learning and cognitive science to study and develop a deeper understanding of the information processing systems.
Data Intelligence and Cognitive Informatics: Proceedings of ICDICI 2021 (Algorithms for Intelligent Systems)
by Robert Bestak I. Jeena Jacob Selvanayaki Kolandapalayam ShanmugamThe book is a collection of peer-reviewed best selected research papers presented at the International Conference on Data Intelligence and Cognitive Informatics (ICDICI 2021), organized by SCAD College of Engineering and Technology, Tirunelveli, India, during July 16–17, 2021. This book discusses new cognitive informatics tools, algorithms, and methods that mimic the mechanisms of the human brain which leads to an impending revolution in understating a large amount of data generated by various smart applications. The book includes novel work in data intelligence domain which combines with the increasing efforts of artificial intelligence, machine learning, deep learning, and cognitive science to study and develop a deeper understanding of the information processing systems.
Data Intelligence and Cognitive Informatics: Proceedings of ICDICI 2022 (Algorithms for Intelligent Systems)
by I. Jeena Jacob Selvanayaki Kolandapalayam Shanmugam Ivan IzoninThe book is a collection of peer-reviewed best selected research papers presented at the International Conference on Data Intelligence and Cognitive Informatics (ICDICI 2021), organized by SCAD College of Engineering and Technology, Tirunelveli, India, during July 6–7, 2022. This book discusses new cognitive informatics tools, algorithms and methods that mimic the mechanisms of the human brain which lead to an impending revolution in understating a large amount of data generated by various smart applications. The book includes novel work in data intelligence domain which combines with the increasing efforts of artificial intelligence, machine learning, deep learning and cognitive science to study and develop a deeper understanding of the information processing systems.
Data Intelligence and Cognitive Informatics: Proceedings of ICDICI 2023 (Algorithms for Intelligent Systems)
by Selwyn Piramuthu I. Jeena Jacob Przemyslaw Falkowski-GilskiThe book is a collection of peer-reviewed best selected research papers presented at the International Conference on Data Intelligence and Cognitive Informatics (ICDICI 2023), organized by SCAD College of Engineering and Technology, Tirunelveli, India, during June 27–28, 2023. This book discusses new cognitive informatics tools, algorithms and methods that mimic the mechanisms of the human brain which lead to an impending revolution in understating a large amount of data generated by various smart applications. The book includes novel work in data intelligence domain which combines with the increasing efforts of artificial intelligence, machine learning, deep learning and cognitive science to study and develop a deeper understanding of the information processing systems.
Data Intensive Industrial Asset Management: IoT-based Algorithms and Implementation
by Tian Zhao Farhad Balali Jessie Nouri Adel NasiriThis book presents a step by step Asset Health Management Optimization Approach Using Internet of Things (IoT). The authors provide a comprehensive study which includes the descriptive, diagnostic, predictive, and prescriptive analysis in detail. The presentation focuses on the challenges of the parameter selection, statistical data analysis, predictive algorithms, big data storage and selection, data pattern recognition, machine learning techniques, asset failure distribution estimation, reliability and availability enhancement, condition based maintenance policy, failure detection, data driven optimization algorithm, and a multi-objective optimization approach, all of which can significantly enhance the reliability and availability of the system.
Data Management Technologies and Applications: 10th International Conference, DATA 2021, Virtual Event, July 6–8, 2021, and 11th International Conference, DATA 2022, Lisbon, Portugal, July 11-13, 2022, Revised Selected Papers (Communications in Computer and Information Science #1860)
by Alfredo Cuzzocrea Slimane Hammoudi Oleg Gusikhin Christoph QuixThis book constitutes the refereed post-proceedings of the 10th International Conference and 11th International Conference on Data Management Technologies and Applications, DATA 2021 and DATA 2022, was held virtually due to the COVID-19 crisis on July 6–8, 2021 and in Lisbon, Portugal on July 11-13, 2022.The 11 full papers included in this book were carefully reviewed and selected from 148 submissions. They were organized in topical sections as follows: engineers and practitioners interested on databases, big data, data mining, data management, data security and other aspects of information systems and technology involving advanced applications of data.
Data Management Technologies and Applications: 12th International Conference, DATA 2023, Rome, Italy, July 11–13, 2023, Revised Selected Papers (Communications in Computer and Information Science #2105)
by Alfredo Cuzzocrea Slimane Hammoudi Oleg GusikhinThis book constitutes the proceedings of the 12th International Conference on Data Management Technologies and Applications, DATA 2023 , held in Rome,Italy during July 11–13, 2023, Proceedings. The 6 full paper were carefully reviewed and selected from 106 submissions. The papers are organized in subject areas as follows: Big Data Applications, Data Analytics, Data Science, NoSQL Databases, Social Data Analytics, Dimensional Modelling, Deep Learning and Big Data, Decision Support Systems, Data Warehouse Management and Data Management for Analytics.
Data Management Technologies and Applications: 9th International Conference, DATA 2020, Virtual Event, July 7–9, 2020, Revised Selected Papers (Communications in Computer and Information Science #1446)
by Slimane Hammoudi Jorge Bernardino Christoph QuixThis book constitutes the thoroughly refereed proceedings of the 9th International Conference on Data Management Technologies and Applications, DATA 2020, which was supposed to take place in Paris, France, in July 2020. Due to the Covid-19 pandemic the event was held virtually. The 14 revised full papers were carefully reviewed and selected from 70 submissions. The papers deal with the following topics: datamining; decision support systems; data analytics; data and information quality; digital rights management; big data; knowledge management; ontology engineering; digital libraries; mobile databases; object-oriented database systems; data integrity.
Data Management and Analysis: Case Studies in Education, Healthcare and Beyond (Studies in Big Data #65)
by Reda Alhajj Mohammad Moshirpour Behrouz FarData management and analysis is one of the fastest growing and most challenging areas of research and development in both academia and industry. Numerous types of applications and services have been studied and re-examined in this field resulting in this edited volume which includes chapters on effective approaches for dealing with the inherent complexity within data management and analysis. This edited volume contains practical case studies, and will appeal to students, researchers and professionals working in data management and analysis in the business, education, healthcare, and bioinformatics areas.
Data Management, Analytics and Innovation: Proceedings Of Icdmai 2018, Volume 2 (Advances In Intelligent Systems and Computing #839)
by Valentina Emilia Balas Amlan Chakrabarti Neha SharmaThe volume on Data Management, Analytics and Innovations presents the latest high-quality technical contributions and research results in the areas of data management and smart computing, big data management, artificial intelligence and data analytics along with advances in network technologies. It deals with the state-of-the-art topics and provides challenges and solutions for future development. Original, unpublished research work highlighting specific research domains from all viewpoints are contributed from scientists throughout the globe. This volume is mainly designed for professional audience, composed of researchers and practitioners in academia and industry.
Data Management, Analytics and Innovation: Proceedings of ICDMAI 2018, Volume 1 (Advances in Intelligent Systems and Computing #808)
by Valentina Emilia Balas Amlan Chakrabarti Neha SharmaThe book presents the latest, high-quality, technical contributions and research findings in the areas of data management and smart computing, big data management, artificial intelligence and data analytics, along with advances in network technologies. It discusses state-of-the-art topics as well as the challenges and solutions for future development. It includes original and previously unpublished international research work highlighting research domains from different perspectives. This book is mainly intended for researchers and practitioners in academia and industry.
Data Management, Analytics and Innovation: Proceedings of ICDMAI 2019, Volume 1 (Advances in Intelligent Systems and Computing #1042)
by Valentina Emilia Balas Amlan Chakrabarti Neha SharmaThis book presents the latest findings in the areas of data management and smart computing, big data management, artificial intelligence and data analytics, along with advances in network technologies. It addresses state-of-the-art topics and discusses challenges and solutions for future development. Gathering original, unpublished contributions by scientists from around the globe, the book is mainly intended for a professional audience of researchers and practitioners in academia and industry.
Data Management, Analytics and Innovation: Proceedings of ICDMAI 2019, Volume 2 (Advances in Intelligent Systems and Computing #1016)
by Valentina Emilia Balas Amlan Chakrabarti Neha SharmaThis book presents the latest findings in the areas of data management and smart computing, big data management, artificial intelligence and data analytics, along with advances in network technologies. It addresses state-of-the-art topics and discusses challenges and solutions for future development. Gathering original, unpublished contributions by scientists from around the globe, the book is mainly intended for a professional audience of researchers and practitioners in academia and industry.
Data Management, Analytics and Innovation: Proceedings of ICDMAI 2020, Volume 1 (Advances in Intelligent Systems and Computing #1174)
by Valentina Emilia Balas Amlan Chakrabarti Neha Sharma Jan MartinovicThis book presents the latest findings in the areas of data management and smart computing, big data management, artificial intelligence and data analytics, along with advances in network technologies. Gathering peer-reviewed research papers presented at the Fourth International Conference on Data Management, Analytics and Innovation (ICDMAI 2020), held on 17–19 January 2020 at the United Services Institute (USI), New Delhi, India, it addresses cutting-edge topics and discusses challenges and solutions for future development. Featuring original, unpublished contributions by respected experts from around the globe, the book is mainly intended for a professional audience of researchers and practitioners in academia and industry.
Data Management, Analytics and Innovation: Proceedings of ICDMAI 2020, Volume 2 (Advances in Intelligent Systems and Computing #1175)
by Valentina Emilia Balas Amlan Chakrabarti Neha Sharma Jan MartinovicThis book presents the latest findings in the areas of data management and smart computing, big data management, artificial intelligence and data analytics, along with advances in network technologies. Gathering peer-reviewed research papers presented at the Fourth International Conference on Data Management, Analytics and Innovation (ICDMAI 2020), held on 17–19 January 2020 at the United Services Institute (USI), New Delhi, India, it addresses cutting-edge topics and discusses challenges and solutions for future development. Featuring original, unpublished contributions by respected experts from around the globe, the book is mainly intended for a professional audience of researchers and practitioners in academia and industry.
Data Management, Analytics and Innovation: Proceedings of ICDMAI 2021, Volume 1 (Lecture Notes on Data Engineering and Communications Technologies #70)
by Valentina Emilia Balas Amlan Chakrabarti Neha Sharma Alfred M. BrucksteinThis book presents the latest findings in the areas of data management and smart computing, machine learning, big data management, artificial intelligence, and data analytics, along with advances in network technologies. The book is a collection of peer-reviewed research papers presented at Fifth International Conference on Data Management, Analytics and Innovation (ICDMAI 2021), held during January 15–17, 2021, in a virtual mode. It addresses state-of-the-art topics and discusses challenges and solutions for future development. Gathering original, unpublished contributions by scientists from around the globe, the book is mainly intended for a professional audience of researchers and practitioners in academia and industry.
Data Management, Analytics and Innovation: Proceedings of ICDMAI 2021, Volume 2 (Lecture Notes on Data Engineering and Communications Technologies #71)
by Valentina Emilia Balas Amlan Chakrabarti Neha Sharma Alfred M. BrucksteinThis book presents the latest findings in the areas of data management and smart computing, machine learning, big data management, artificial intelligence, and data analytics, along with advances in network technologies. The book is a collection of peer-reviewed research papers presented at Fifth International Conference on Data Management, Analytics and Innovation (ICDMAI 2021), held during January 15–17, 2021, in a virtual mode. It addresses state-of-the-art topics and discusses challenges and solutions for future development. Gathering original, unpublished contributions by scientists from around the globe, the book is mainly intended for a professional audience of researchers and practitioners in academia and industry.
Data Management, Analytics and Innovation: Proceedings of ICDMAI 2023 (Lecture Notes in Networks and Systems #662)
by Amlan Chakrabarti Neha Sharma Alfred M. Bruckstein Amol GojeThis book presents the latest findings in the areas of data management and smart computing, big data management, artificial intelligence and data analytics, along with advances in network technologies. The volume is a collection of peer reviewed research papers presented at Seventh International Conference on Data Management, Analytics and Innovation (ICDMAI 2023), held during 20 – 22 January, 2023 in Pune, India. It addresses state-of-the-art topics and discusses challenges and solutions for future development. Gathering original, unpublished contributions by scientists from around the globe, the book is mainly intended for a professional audience of researchers and practitioners in academia and industry.
Data Management, Analytics and Innovation: Proceedings of ICDMAI 2024, Volume 1 (Lecture Notes in Networks and Systems #997)
by Amlan Chakrabarti Neha Sharma Alfred M. Bruckstein Amol C. GojeThis book presents the latest findings in the areas of data management and smart computing, big data management, artificial intelligence, and data analytics, along with advances in network technologies. The book is a collection of peer-reviewed research papers presented at 8th International Conference on Data Management, Analytics and Innovation (ICDMAI 2024), held during 19–21 January 2024 in Vellore Institute of Technology, Vellore, India. It addresses state-of-the-art topics and discusses challenges and solutions for future development. Gathering original, unpublished contributions by scientists from around the globe, the book is mainly intended for a professional audience of researchers and practitioners in academia and industry. The book is divided into two volumes.