Visualizing The Data City

This book investigates novel methods and technologies for the collection, analysis and representation of real-time user-generated data at the urban scale in order to explore potential scenarios for more participatory design, planning and management processes. For this purpose, the authors present a set of experiments conducted in collaboration with urban stakeholders at various levels (including citizens, city administrators, urban planners, local industries and NGOs) in Milan and New York in 2012. It is examined whether geo-tagged and user-generated content can be of value in the creation of meaningful, real-time indicators of urban quality, as it is perceived and communicated by the citizens. The meanings that people attach to places are also explored to discover what such an urban semantic layer looks like and how it unfolds over time. As a conclusion, recommendations are proposed for the exploitation of user-generated content in order to answer hitherto unsolved urban questions. Readers will find in this book a fascinating exploration of techniques for mining the social web that can be applied to procure user-generated content as a means of investigating urban dynamics.

Visualizing the Street investigates the social and cultural significance of new developments at the intersection of visual culture and urban space.

Today we are witnessing an increased use of data visualization in society. Across domains such as work, education and the news, various forms of graphs, charts and maps are used to explain, convince and tell stories. In an era in which more and more data are produced and circulated digitally, and digital tools make visualization production increasingly accessible, it is important to study the conditions under which such visual texts are generated, disseminated and thought to be of societal benefit. This book is a contribution to the multi-disciplined and multi-faceted conversation concerning the forms, uses and roles of data visualization in society. Do data visualizations do 'good' or 'bad'? Do they promote understanding and engagement, or do they do ideological work, privileging certain views of the world over others? The contributions in the book engage with these core questions from a range of disciplinary perspectives.

This is the age of data. There are more innovations and more opportunities for interesting work with data than ever before, but there is also an overwhelming amount of quantitative information being published every day. Data visualisation has become big business, because communication is the difference between success and failure, no matter how clever the analysis may have been. The ability to visualize data is now a skill in demand across business, government, NGOs and academia. Data Visualization: Charts, Maps, and Interactive Graphics gives an overview of a wide range of techniques and challenges, while staying accessible to anyone interested in working with and understanding data. Features: Focusses on concepts and ways of thinking about data rather than algebra or computer code. Features 17 short chapters that can be read in one sitting. Includes chapters on big data, statistical and machine learning models, visual perception, high-dimensional data, and maps and geographic data. Contains more than 125 visualizations, most created by the author. Supported by a website with all code for creating the visualizations, further reading, datasets and practical advice on crafting the images. Whether you are a student considering a career in data science, an analyst who wants to learn more about visualization, or the manager of a team working with data, this book will introduce you to a broad range of data visualization methods. Cover image: Landscape of Change uses data about sea level rise, glacier volume decline, increasing global temperatures, and the increasing use of fossil fuels. These data lines compose a landscape shaped by the changing climate, a world in which we are now living. Copyright © Jill Pelto (jillpelto.com).

Data Visualization for Design Thinking helps you make better maps. Treating maps as applied research, you’ll be able to understand how to map sites, places, ideas, and projects, revealing the complex relationships between what you represent, your thinking, the technology you use, the culture you belong to, and your aesthetic practices. More than 100 examples illustrated with over 200 color images show you how to visualize data through mapping. Includes five in-depth cases studies and numerous examples throughout.

Information may be beautiful, but our decisions about the data we choose to represent and how we represent it are never neutral. This insightful history traces how data visualization accompanied modern technologies of war, colonialism and the management of social issues of poverty, health and crime. Discussion is based around examples of visualization, from the ancient Andean information technology of the quipu to contemporary projects that show the fate of our rubbish and take a participatory approach to visualizing cities. This analysis places visualization in its theoretical and cultural contexts, and provides a critical framework for understanding the history of information design with new directions for contemporary practice.

This book offers an engaging and accessible introduction to data visualization for communicators, covering everything from data collection and analysis to the creation of effective data visuals. Straying from the typical "how to visualize data" genre often written for technical audiences, Big Data in Small Slices offers those new to data gathering and visualization the opportunity to better understand data itself. Using the concept of the "data backstory," each chapter features discussions with experts, from marine scientists to pediatricians and city government officials, who produce datasets in their daily work. The reader is guided through the process of designing effective visualizations based on their data, delving into how datasets are produced and vetted, and how to assess their weaknesses and strengths, ultimately offering readers the knowledge needed to produce their own effective data visuals. This book is an invaluable resource for anyone interested in data visualization and storytelling, from journalism and communications students to public relations professionals. A detailed accompanying website features additional material for readers, including links to all the original datasets used in the text, at www.bigdatainsmallslices.com

Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results