Raw Data Is an Oxymoron

Raw Data Is an Oxymoron examines the concept of data through historical, cultural, and technological perspectives. The book consists of essays from scholars across disciplines who analyze how data has been created, interpreted, and used throughout different time periods. The collection traces data practices from early record-keeping and statistics to modern digital information systems. Through case studies ranging from colonial recordkeeping to contemporary big data, the authors demonstrate how data is never truly "raw" but always shaped by human choices and contexts. The essays explore topics including scientific measurement, government statistics, database design, and information visualization. Key examples include nineteenth-century census methods, the development of stock market data, and the rise of standardized medical records. At its core, this book challenges the notion of data as neutral or objective facts. The work reveals data as a cultural artifact that reflects and shapes how societies understand and organize knowledge.

Readers describe this as an academic text that challenges assumptions about data's objectivity. The book resonates with data scientists, historians, and social science researchers who appreciate its examination of how data is constructed and interpreted. Liked: - Clear examples from history showing data's contextual nature - Strong theoretical framework for critical data studies - Valuable insights for researchers and practitioners Disliked: - Dense academic writing style that can be difficult to follow - Some essays more engaging than others - Limited practical applications for non-academics - High price point for length As one reader noted: "Important ideas but wrapped in unnecessarily complex language that limits its reach." Ratings: Goodreads: 3.8/5 (89 ratings) Amazon: 4.1/5 (22 reviews) Google Books: 4/5 (13 reviews) The collection receives stronger reviews from academic readers than general audiences, with multiple reviewers suggesting it's best suited for graduate-level studies or research purposes.

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📚 Lisa Gitelman draws from her experience as both a journalist and an academic, bringing unique insights into how data is never truly "raw" but always shaped by cultural and historical contexts. 🎓 The book features contributions from multiple scholars across different disciplines, including Geoffrey Bowker, Daniel Rosenberg, and Ellen Gruber Garvey. 📊 The term "data" originally meant something that was given or granted in an argument, quite different from its modern meaning as collected information or facts. 📜 One chapter explores how early Japanese officials in the 1720s collected and visualized data about commodity prices, revealing that sophisticated data practices existed long before the digital age. 🔍 The book examines how punch cards, used for the 1890 U.S. census, marked a pivotal moment in data processing history, laying groundwork for modern computing systems.