How Charts Lie by
Today, public conversations are increasingly driven by numbers. Although charts, infographics, and diagrams can make us smarter, they can also deceive?intentionally or unintentionally. To be informed citizens, we must all be able to decode and use the visual information that politicians, journalists, and even our employers present to us each day. How Charts Lie examines contemporary examples ranging from election result infographics to global GDP maps and box office record charts, demystifying an essential new literacy for our data-driven world.
Communicating with Data by
Communication is a critical yet often overlooked part of data science. Communicating with Data aims to help students and researchers write about their insights in a way that is both compelling and faithful to the data. General advice on science writing is also provided, including how to distill findings into a story and organize and revise the story, and how to write clearly, concisely, and precisely. This is an excellent resource for students who want to learn how to write about scientific findings, and for instructors who are teaching a science course in communication or a course with a writing component. Communicating with Data consists of five parts. Part I helps the novice learn to write by reading the work of others. Part II delves into the specifics of how to describe data at a level appropriate for publication, create informative and effective visualizations, and communicate an analysis pipeline through well-written, reproducible code. Part III demonstrates how to reduce a data analysis to a compelling story and organize and write the first draft of a technical paper. Part IV addresses revision; this includes advice on writing about statistical findings in a clear and accurate way, general writing advice, and strategies for proof reading and revising. Part V offers advice about communication strategies beyond the page, which include giving talks, building a professional network, and participating in online communities. This book also provides 22 portfolio prompts that extend the guidance and examples in the earlier parts of the book and help writers build their portfolio of data communication.
Data Feminism by
A 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 Action by
How to use data as a tool for empowerment rather than oppression. Big data can be used for good--from tracking disease to exposing human rights violations--and for bad--implementing surveillance and control. Data inevitably represents the ideologies of those who control its use; data analytics and algorithms too often exclude women, the poor, and ethnic groups. In Data Action, Sarah Williams provides a guide for working with data in more ethical and responsible ways. Too often data has been used--and manipulated--to make policy decisions without much stakeholder input. Williams outlines a method that emphasizes collaboration among data scientists, policy experts, data designers, and the public. This approach creates trust and co-ownership in the data by opening the process to those who know the issues best.
Indigenous Data Sovereignty and Policy by
This book examines how Indigenous Peoples around the world are demanding greater data sovereignty, and challenging the ways in which governments have historically used Indigenous data to develop policies and programs. In the digital age, governments are increasingly dependent on data and data analytics to inform their policies and decision-making. However, Indigenous Peoples have often been the unwilling targets of policy interventions and have had little say over the collection, use and application of data about them, their lands and cultures. At the heart of Indigenous Peoples' demands for change are the enduring aspirations of self-determination over their institutions, resources, knowledge and information systems. With contributors from Australia, Aotearoa New Zealand, North and South America and Europe, this book offers a rich account of the potential for Indigenous data sovereignty to support human flourishing and to protect against the ever-growing threats of data-related risks and harms.
More Judgment Than Data: data literacy and decision-making by
More data has been produced in the 21st century than all of human history combined. Yet, are we making better decisions today than in the past? How many poor decisions result from the absence of data? The existence of an overwhelming amount of data has affected how we make decisions, but it has not necessarily improved how we make decisions. To make better decisions, people need good judgment based on data literacy--the ability to extract meaning from data. Including data in the decision-making process can bring considerable clarity in answering our questions. Nevertheless, human beings can become distracted, overwhelmed, and even confused in the presence of too much data. The book presents cautionary tales of what can happen when too much attention is spent on acquiring more data instead of understanding how to best use the data we already have. Data is not produced in a vacuum, and individuals who possess data literacy will understand the environment and incentives in the data-generating process. Readers of this book will learn what questions to ask, what data to pay attention to, and what pitfalls to avoid in order to make better decisions. They will also be less vulnerable to those who manipulate data for misleading purposes.
The Data Journalism Handbook by
When you combine the sheer scale and range of digital information now available with a journalist's "nose for news" and her ability to tell a compelling story, a new world of possibility opens up. With The Data Journalism Handbook, you'll explore the potential, limits, and applied uses of this new and fascinating field. This valuable handbook has attracted scores of contributors since the European Journalism Centre and the Open Knowledge Foundation launched the project at MozFest 2011. Through a collection of tips and techniques from leading journalists, professors, software developers, and data analysts, you'll learn how data can be either the source of data journalism or a tool with which the story is told--or both. Examine the use of data journalism at the BBC, the Chicago Tribune, the Guardian, and other news organizations Explore in-depth case studies on elections, riots, school performance, and corruption Learn how to find data from the Web, through freedom of information laws, and by "crowd sourcing." Extract information from raw data with tips for working with numbers and statistics and using data visualization. Deliver data through infographics, news apps, open data platforms, and download links.
The Data Journalism Handbook: towards a critical data practice by
The Data Journalism Handbook: Towards a Critical Data Practice provides a rich and panoramic introduction to data journalism, combining both critical reflection and practical insight. It offers a diverse collection of perspectives on how data journalism is done around the world and the broader consequences of datafication in the news, serving as both a textbook and a sourcebook for this emerging field. With more than 50 chapters from leading researchers and practitioners of data journalism, it explores the work needed to render technologies and data productive for journalistic purposes. It also gives a 'behind the scenes' look at the social lives of datasets, data infrastructures, and data stories in newsrooms, media organizations, startups, civil society organizations and beyond. The book includes sections on 'doing issues with data', 'assembling data', 'working with data', 'experiencing data', 'investigating data, platforms and algorithms', 'organizing data journalism', 'learning data journalism together' and 'situating data journalism'.
The Data Detective by
From "one of the great (greatest') contemporary popular writers on economics" (Tyler Cowen) comes a smart, lively, and encouraging rethinking of how to use statistics. Today we think statistics are the enemy, numbers used to mislead and confuse us. That's a mistake, Tim Harford says in The Data Detective. We shouldn't be suspicious of statistics'we need to understand what they mean and how they can improve our lives: they are, at heart, human behavior seen through the prism of numbers and are often "the only way of grasping much of what is going on around us." If we can toss aside our fears and learn to approach them clearly'understanding how our own preconceptions lead us astray'statistics can point to ways we can live better and work smarter. As "perhaps the best popular economics writer in the world" (New Statesman), Tim Harford is an expert at taking complicated ideas and untangling them for millions of readers. In The Data Detective, he uses new research in science and psychology to set out ten strategies for using statistics to erase our biases and replace them with new ideas that use virtues like patience, curiosity, and good sense to better understand ourselves and the world. As a result, The Data Detective is a big-idea book about statistics and human behavior that is fresh, unexpected, and insightful.
