Episodes in the history of data, from early modern math problems to today's inescapable "dataveillance," that demonstrate the dependence of data on culture. We live in the era of Big Data, with storage and transmission capacity measured not just in terabytes but in petabytes (where peta- denotes a quadrillion, or a thousand trillion). Data collection is constant and even insidious, with every click and every "like" stored somewhere for something. This book reminds us that data is anything but "raw," that we shouldn't think of data as a natural resource but as a cultural one that needs to be generated, protected, and interpreted. The book's essays describe eight episodes in the history of data from the predigital to the digital. Together they address such issues as the ways that different kinds of data and different domains of inquiry are mutually defining; how data are variously "cooked" in the processes of their collection and use; and conflicts over what can--or can't--be "reduced" to data. Contributors discuss the intellectual history of data as a concept; describe early financial modeling and some unusual sources for astronomical data; discover the prehistory of the database in newspaper clippings and index cards; and consider contemporary "dataveillance" of our online habits as well as the complexity of scientific data curation. Essay Authors Geoffrey C. Bowker, Kevin R. Brine, Ellen Gruber Garvey, Lisa Gitelman, Steven J. Jackson, Virginia Jackson, Markus Krajewski, Mary Poovey, Rita Raley, David Ribes, Daniel Rosenberg, Matthew Stanley, Travis D. Williams
In Decoding the Social World, Sandra González-Bailón explains how data science and digital traces help us solve the puzzle of unintended consequences—offering the solution to a social paradox that has intrigued thinkers for centuries.
This is where Anderson made his intervention: at the point at which we have data collected on the entire population, we no longer need modeling, or any other “theory” to first test and then prove. We can look directly at the data ...
In Always Already New, Lisa Gitelman explores the newness of new media while she asks what it means to do media history.
In contexts from the everyday to the esoteric, machine learning is said to transform the nature of knowledge. In this book, Adrian Mackenzie investigates whether machine learning also transforms the practice of critical thinking.
I am especially thankful to Deborah Thomas, who has continued to be an important source of inspiration, advice, and mentorship through my junior faculty years, and kindly hosted me as a visiting scholar at Penn during my junior research ...
Paper Knowledge is a remarkable book about the mundane: the library card, the promissory note, the movie ticket, the PDF (Portable Document Format).
We Are Data will educate and inspire readers who want to wrest back some freedom in our increasingly surveilled and algorithmically-constructed world.
Influence action through data! This is not a book. It is a one-of-a-kind immersive learning experience through which you can become—or teach others to be—a powerful data storyteller.
Blending reportage, family history, and intellectual adventure, This Is Not Propaganda explores how we can reimagine our politics and ourselves when reality seems to be coming apart.
After reading this book, any brand should be in a position to make a step change in the value they derive from their data assets.