The present work provides a platform for leading Data designers whose vision and creativity help us to anticipate major changes occurring in the Data Design field, and pre-empt the future. Each of them strives to provide new answers to the question, “What challenges await Data Design?” To avoid falling into too narrow a mind-set, each works hard to elucidate the breadth of Data Design today and to demonstrate its widespread application across a variety of business sectors. With end users in mind, designer-contributors bring to light the myriad of purposes for which the field was originally intended, forging the bond even further between Data Design and the aims and intentions of those who contribute to it. The first seven parts of the book outline the scope of Data Design, and presents a line-up of “viewpoints” that highlight this discipline’s main topics, and offers an in-depth look into practices boasting both foresight and imagination. The eighth and final part features a series of interviews with Data designers and artists whose methods embody originality and marked singularity. As a result, a number of enlightening concepts and bright ideas unfold within the confines of this book to help dispel the thick fog around this new and still relatively unknown discipline. A plethora of equally eye-opening and edifying new terms, words, and key expressions also unfurl. Informing, influencing, and inspiring are just a few of the buzz words belonging to an initiative that is, first and foremost, a creative one, not to mention the possibility to discern the ever-changing and naturally complex nature of today’s datasphere. Providing an invaluable and cutting-edge resource for design researchers, this work is also intended for students, professionals and practitioners involved in Data Design, Interaction Design, Digital & Media Design, Data & Information Visualization, Computer Science and Engineering.

The goal of the book is to present the latest research on the new challenges of data technologies. It will offer an overview of the social, ethical and legal problems posed by group profiling, big data and predictive analysis and of the different approaches and methods that can be used to address them. In doing so, it will help the reader to gain a better grasp of the ethical and legal conundrums posed by group profiling. The volume first maps the current and emerging uses of new data technologies and clarifies the promises and dangers of group profiling in real life situations. It then balances this with an analysis of how far the current legal paradigm grants group rights to privacy and data protection, and discusses possible routes to addressing these problems. Finally, an afterword gathers the conclusions reached by the different authors and discuss future perspectives on regulating new data technologies.

Data is at the center of many challenges in system design today. Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including relational databases, NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your application? How do you make sense of all these buzzwords? In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications. Peer under the hood of the systems you already use, and learn how to use and operate them more effectively Make informed decisions by identifying the strengths and weaknesses of different tools Navigate the trade-offs around consistency, scalability, fault tolerance, and complexity Understand the distributed systems research upon which modern databases are built Peek behind the scenes of major online services, and learn from their architectures

One of the "six best books for data geeks" - Financial Times With over 200 images and extensive how-to and how-not-to examples, this new edition has everything students and scholars need to understand and create effective data visualisations. Combining ‘how to think’ instruction with a ‘how to produce’ mentality, this book takes readers step-by-step through analysing, designing, and curating information into useful, impactful tools of communication. With this book and its extensive collection of online support, readers can: Decide what visualisations work best for their data and their audience using the chart gallery See data visualisation in action and learn the tools to try it themselves Follow online checklists, tutorials, and exercises to build skills and confidence Get advice from the UK’s leading data visualisation trainer on everything from getting started to honing the craft.

This book contains 16 chapters by researchers working in various fields of data science. They focus on theory and applications in language technologies, optimization, computational thinking, intelligent decision support systems, decomposition of signals, model-driven development methodologies, interoperability of enterprise applications, anomaly detection in financial markets, 3D virtual reality, monitoring of environmental data, convolutional neural networks, knowledge storage, data stream classification, and security in social networking. The respective papers highlight a wealth of issues in, and applications of, data science. Modern technologies allow us to store and transfer large amounts of data quickly. They can be very diverse - images, numbers, streaming, related to human behavior and physiological parameters, etc. Whether the data is just raw numbers, crude images, or will help solve current problems and predict future developments, depends on whether we can effectively process and analyze it. Data science is evolving rapidly. However, it is still a very young field. In particular, data science is concerned with visualizations, statistics, pattern recognition, neurocomputing, image analysis, machine learning, artificial intelligence, databases and data processing, data mining, big data analytics, and knowledge discovery in databases. It also has many interfaces with optimization, block chaining, cyber-social and cyber-physical systems, Internet of Things (IoT), social computing, high-performance computing, in-memory key-value stores, cloud computing, social computing, data feeds, overlay networks, cognitive computing, crowdsource analysis, log analysis, container-based virtualization, and lifetime value modeling. Again, all of these areas are highly interrelated. In addition, data science is now expanding to new fields of application: chemical engineering, biotechnology, building energy management, materials microscopy, geographic research, learning analytics, radiology, metal design, ecosystem homeostasis investigation, and many others.

An exploration of how design might be led by marginalized communities, dismantle structural inequality, and advance collective liberation and ecological survival. What is the relationship between design, power, and social justice? “Design justice” is an approach to design that is led by marginalized communities and that aims expilcitly to challenge, rather than reproduce, structural inequalities. It has emerged from a growing community of designers in various fields who work closely with social movements and community-based organizations around the world. This book explores the theory and practice of design justice, demonstrates how universalist design principles and practices erase certain groups of people—specifically, those who are intersectionally disadvantaged or multiply burdened under the matrix of domination (white supremacist heteropatriarchy, ableism, capitalism, and settler colonialism)—and invites readers to “build a better world, a world where many worlds fit; linked worlds of collective liberation and ecological sustainability.” Along the way, the book documents a multitude of real-world community-led design practices, each grounded in a particular social movement. Design Justice goes beyond recent calls for design for good, user-centered design, and employment diversity in the technology and design professions; it connects design to larger struggles for collective liberation and ecological survival.

Don't simply show your data—tell a story with it! Storytelling with Data teaches you the fundamentals of data visualization and how to communicate effectively with data. You'll discover the power of storytelling and the way to make data a pivotal point in your story. The lessons in this illuminative text are grounded in theory, but made accessible through numerous real-world examples—ready for immediate application to your next graph or presentation. Storytelling is not an inherent skill, especially when it comes to data visualization, and the tools at our disposal don't make it any easier. This book demonstrates how to go beyond conventional tools to reach the root of your data, and how to use your data to create an engaging, informative, compelling story. Specifically, you'll learn how to: Understand the importance of context and audience Determine the appropriate type of graph for your situation Recognize and eliminate the clutter clouding your information Direct your audience's attention to the most important parts of your data Think like a designer and utilize concepts of design in data visualization Leverage the power of storytelling to help your message resonate with your audience Together, the lessons in this book will help you turn your data into high impact visual stories that stick with your audience. Rid your world of ineffective graphs, one exploding 3D pie chart at a time. There is a story in your data—Storytelling with Data will give you the skills and power to tell it!

The system design interview is considered to be the most complex and most difficult technical job interview by many. Those questions are intimidating, but don't worry. It's just that nobody has taken the time to prepare you systematically. We take the time. We go slow. We draw lots of diagrams and use lots of examples. You'll learn step-by-step, one question at a time.Don't miss out.What's inside?- An insider's take on what interviewers really look for and why.- A 4-step framework for solving any system design interview question.- 16 real system design interview questions with detailed solutions.- 188 diagrams to visually explain how different systems work.

This book gathers the best papers presented at the first conference held by the Russian chapter of the Association for Information Systems (AIS). It shares the latest insights into various aspects of the digitalization of the economy and the consequences of transformation in public administration, business and public life. Integrating a broad range of analytical perspectives, including economic, social and, technological, this interdisciplinary book is particularly relevant for scientists, digital technology users, companies and public institutions.