Stanford
Love Data Week

Love Data Reads

Looking for your next great data read? From sci-fi to maps to football to fashion, check out this list of recommended books about data from Stanford University Libraries, with a few words from staff. 📚

  1. Envisioning Information by Edward Tufte. Great data viz resource. It made data visualization cool before data viz became cool. 
  2. Dear data, a friendship in 52 weeks of postcards. Wonderful data visualizations of everyday life. Creative and joyful communication with data. 
  3. Democracy's data : the hidden stories in the U.S. census and how to read them by Dan Bouk. How do the US Decennial Census tables we often consume without much reflection  come into being? Using the 1944 census Bouk traces the process from legislative decisions to the ‘doorstep encounter’ to the aggregation and its publication, all along examining who is counted and how and who is left out. 
  4. Cooking data: culture and politics in an African research world by Crystal Biruk. An ethnographic study about the collection of quantitative health data in Malawi to combat the AIDS epidemic. Following the researchers, supervisors and fieldworkers as participant-observer Biruk argues that data are never 'clean', but inevitably 'cooked' by those involved in their production. 
  5. Counting feminicide : data feminism in action by Catherine D'Ignazio. Drawing from collaborations with activists in Latin America collecting and documenting feminicide. D'Ignazio offers a framework of restorative and transformative data science. This is a great guide for those interested in applying their data science skills for social justice. 
  6. The secret life of data : navigating hype and uncertainty in the age of algorithmic surveillance by Aram Sinnreich and Jesse Gilbert. The title says it all: Sinnreich and Gilbert take us on a journey through the many ways our data are collected and accumulated without our awareness, let alone consent. Eye opening!
  7. Numbered lives : life and death in quantum media by Jacqueline Wernimont.  A “feminist media history of quantification” by Historian of Science and Technology, this book traces the history of counting and measuring bodies, alongside the emergence of “counting technologies” over the last several centuries. 
  8. How Data Happened: A History from the Age of Reason to the Age of Algorithms by Chris Wiggins and Matthew L. Jones. 
  9. Invisible Women: Data Bias in a World Designed for Men by Caroline Criado Perez.
  10. Data Feminism by Catherine D’Ignazio, Lauren F. Klein. Provides historical and contemporary examples of how data collection and analysis relate to systems of power and are fundamentally political acts.
  11. Ethics in Linked Data by Alexandra Provo, Kathleen Burlingame, and BM Watson. Engaging in critical and ethical analysis is ultimately an optimistic endeavor aimed at exposing problematic issues, generating best practices and guidelines, and opening up positive and generative possibilities for the implementation and use of linked data in GLAMS  (Galleries, Libraries, Archives, Museums, Special Collections).
  12. Print Punch: Artefacts from the Punch Card Computing Era, Centre Centre. Data used to be physical. In an era when 1s and 0s seem to hover above our heads, Print Punch returns to the heyday of the punch card—to a time when you could touch (and punch) data. (out of print but still lovely!)
  13. Weapons of math destruction: how big data increases inequality and threatens democracy by Cathy O'Neil. Primer on algorithmic reinforcement of existing inequalities when applied to socioeconomic problems
  14. The Theory and Craft of Digital Preservation by Trevor Owens. It’s impossible to analyze data if you don’t know how to care for it over time so that it can be made accessible. This compact book outlines the practical steps that need to be take to care for data over time.
  15. History of information graphics edited by Sandra Rendgen, ed., Julius Wiedemann, with contributions from David Rumsey, Michael Friendly, Michael Stoll and Scott Klein.
  16. 100 Diagrams That Changed The World by Scott Christianson.  This collection includes multiple examples of data visualizations and information graphics, covering areas as disparate as anatomy, astronomy, and historical charts.  More information available at  this blog. 
  17. Record, Map and Capture in Textile Art: Data Visualization In Cloth And Stitch by Jordan Cunliffe. Read more about transforming data into textile art!
  18. Making with Data: Physical Design and Craft edited by Samuel Huron, Till Nagel, Lora Oehlberg, and Wesley Willett. This book provides a snapshot of the diverse practices contemporary creators are using to produce objects, spaces, and experiences imbued with data."
  19. Sorting Things Out: Classification and Its Consequences by Geoffrey C. Bowker, Susan Leigh Star. How do technical standards for metadata and classification impact the shape of data, and how it can be used? This classic book takes a look at this history which is even more relevant today as large amounts of data are collected for machine learning and AI systems. 
  20. W. E. B. Du Bois's Data Portraits: Visualizing Black America edited by Whitney Battle-Baptiste and Britt Rusert. Look through the first complete publication of W.E.B. Du Bois's groundbreaking charts, graphs, and maps presented at the 1900 Paris Exposition."
  21. Football Analytics with Python & R: Learning Data Science Through the Lens of Sports by Eric A. Eager and Richard A. Erickson. This book offers a clear intro to ...pro "using statistical models to analyze football data using both Python and R." 
  22. Everyday adventures with unruly data by Melanie Feinberg. This book is lovely because it explores organization of information from a personal, commonplace perspective, appealing to all the lumping vs. splitting, labels and categories-type questions that might arise, say, at the grocery store: a humanities-grounded approach to data criticism.
  23. Beautiful Data: A History of Vision and Reason since 1945 by Orit Halpern. This book is "a history of big data and interactivity, and a sophisticated meditation on ideas about vision and cognition in the second half of the twentieth century." 
  24. Theory on Demand: Good Data by Angela Daly, S. Kate Devitt, and Monique Mann. A multidisciplinary collection of case studies that explores what make data “good”. It’s broken up into six themes with several chapters each: Good Data Manifestos and Practices, Good Data and Justice, Good Data as Open and Shared Data, Good Data Activism and Research, Good Data and Smart Cities and Homes. The chapters on indigenous data sovereignty, data’s role in un/healthy democracy, and algorithmic risk assessment are particularly salient. 
  25. Declining Left-Handedness in Victorian England Seen in the Films of Mitchell and Kenyon by I.C. McManus and Alex Hartigan. I have for many years used this article, and the following one, to teach about how collections of historic media or personal records can provide sources of data for research in many fields. They’re also interesting examples of research design and methodology.
  26. Early Recognition of Children with Autism: A Study of First Birthday Home Videotapes by Julie Osterling and Geraldine Dawson. This article in particular improves upon earlier studies that used home movies as data, but were largely interpretive, overtly biased, and drew deeply flawed conclusions. In this study, the selection of materials and the research design addressed those flaws and enabled clearer, more reliable and less subjective interpretation of the visual data.
  27. The People and the Tech behind the Panama Papers by Mar Cabra and Erin Kissane. This famous data project employed Blackight as part of its data analysis. 
  28. Cryptonomicon by Neal Stephenson. Thriller novel set both in the days of the World War II codebreakers, and in the underground finance world of the 1990s.
  29. In American Fashion: Ruth Finley’s Fashion Calendar by Natalie Nudell: Bloomsbury Visual Arts. And the associated online database of the Fashion Calendar, hosted by FIT in New York, which is an amazing source of longitudinal data on the history and daily activities of the fashion world in New York City and beyond from 1941-2014.
  30. Fact Book Kenkyu Gyoseki Zukai Shu : Tabular and Graphic Presentation of ABCC Research Findings edited by Masanori Nakaidzumi. The Atomic Bomb Casualty Commission, a joint US-Japan research effort founded in the aftermath of the American bombings of Hiroshima and Nagasaki, conducted epidemiological and genetic studies of the survivors of the atomic bombs and of their children. This research program has provided the primary basis for radiation health standards, and this book presents significant portions of their findings.
  31. Semantic Media: Mapping Meaning on the Internet by Andrew Iliadis. Semantic Media is about the emerging era of meaning-making technologies. Companies like Apple, Google, Facebook, Amazon, and Microsoft organize information in new media products that seek to “intuitively” grasp what people want to know and the actions they want to take.
  32. Info we trust : how to inspire the world with data by RJ Andrews. Join award-winning data storyteller RJ Andrews as he pushes beyond the usual how-to, and takes you on an adventure into the rich art of informing. Creating Info We Trust is a craft that puts the world into forms that are strong and true. It begins with maps, diagrams, and charts—but must push further than dry defaults to be truly effective.
  33. The Visual Display of Quantitative Information by Edward R. Tufte. An inviting book that discusses the fundamentals of communicating data, something that so many of us consider in our work. I particularly like it because it both is a useful text to reference for projects, but also has nice pictures to briefly glance at.
  34. GIS and cartographic modeling by C. Dana Tomlin. Tomlin’s classic combination of technical specification for what we have come to call “Map Algebra” and his framework for “Spatial Thinking.” At once technical & existential. A must read for anyone who wants to move from mere descriptive analytics to modeling of spatial phenomena. https://archive.org/details/geographicinform00toml 
  35. Storytelling with data : a data visualization guide for business professionals by C.N. Knaflic.  Why? Bridges the gap between analysis and communication, particularly for a lay audience. 
  36. Cloud-based remote sensing with Google Earth Engine : fundamentals and applications edited by Jeffrey A. Cardille, Morgan A. Crowley, David Saah, Nicholas E. Clinton. The first and most complete textbook using Google Earth Engine for teaching fundamentals of Earth Observation Research, with Google Earth Engine. 
  37. Geospatial law, policy, and ethics : where geospatial technology is taking the law by K.D. Pomfret. Who is to blame when inaccurate routing data causes harm? Where do international boundaries derive their authority? How do intellectual property rights intersect with cartographic information? 
  38. Textiles, Community and Controversy: The Knitting Map edited by Jools Gilson and Nicola Moffat. A collection of  critical essays on The Knitting Map, a large-scale project merging data visualization and craft practice, which stimulated considerable controversy when it received public funding as part of the city of Cork, Ireland’s stint as European Capital of Culture in 2005.
  39. A Journal in Yarn: How to Plan a Temperature Blanket Knitting Project . A blog that outlines techniques for creating a textile-based data visualization based on weather data, in a similar vein to the Knitting Map from the resource above. 
  40. The fourth paradigm : data-intensive scientific discovery edited by Tony Hey, Stewart Tansley and Kristin Tolle. Why? The classic text on “Big Data Analytics” which explored the research problems that cloud compute solves. Jim Gray’s Introduction defined the problem: “Often it turns out to be more efficient to move the questions than to move the data.”
  41. Infinite City: San Francisco by Rebecca Solnit. Great data visualizations.
  42. Statistics and data visualization in climate science with R and Python by Samuel S. P. Shen and Gerald R. North. This resource covers a variety of analyses and data viz options for more than just climate science in both R and Python.
  43. A Half-Built Garden by Ruthanna Emrys. A sci-fi novel that is both climate fiction and first-contact story. 
  44. The Martian : a novel by Andy Weir. Weir's novel explores topics pertaining to open science and government data. 
  45. ICEF Artificial Intelligence for Climate Change Mitigation Roadmap (Second Edition) by David Sandalow et al. There is something for everyone in this detailed report that discusses examples, recommendations, and climate consequences of AI in different sectors from power to food systems. One interesting key takeaway: “Greenhouse gas emissions from computing operations for AI are less than 1%—and perhaps much less than 1%—of global GHG emissions. These emissions will very likely increase in the years ahead, in amounts that could be modest or significant.”
  46. Indigenous Data Sovereignty and Policy edited by Maggie Walter, Tahu Kukutai, Stephanie Russo Carroll, Desi Rodriguez-Lonebear. Provides examples of infringements on Indigenous Data Sovereignty and guidance for how to respect indigenous data governance. Particularly relevant is the chapter “Indigenous Data Sovereignty and the role of universities.”
  47. Doing Data Science: Straight Talk from the Frontline by Rachel Schutt & Cathy O’Neil. Now that people are aware that data can make the difference in an election or a business model, data science as an occupation is gaining ground. But how can you get started working in a wide-ranging, interdisciplinary field that's so clouded in hype? This insightful book, based on Columbia University's Introduction to Data Science class, tells you what you need to know. In many of these chapter-long lectures, data scientists from companies such as Google, Microsoft, and eBay share new algorithms, methods, and models by presenting case studies and the code they use. If you're familiar with linear algebra, probability, and statistics, and have programming experience, this book is an ideal introduction to data science.
  48. Race after Technology: Abolitionist Tools for the New Jim Code by Ruha Benjamin. This illuminating guide provides conceptual tools for decoding tech promises with sociologically informed skepticism. In doing so, it challenges us to question not only the technologies we are sold but also the ones we ourselves manufacture. Benjamin argues that automation, far from being a sinister story of racist programmers scheming on the dark web, has the potential to hide, speed up, and deepen discrimination while appearing neutral and even benevolent when compared to the racism of a previous era.
  49. The Three-Body Problem by Liu Cixin. A work of science fiction that blends concepts from physics into a mystery/thriller story. Data about atomic and subatomic interactions captured on Earth plays an important role, and data transfer between the Earth and other planets also takes center stage.
  50. The Traitor Baru Cormorant by Seth Dickinson. We'd argue that a majority of this book is about accounting data.
  51.  All Systems Red by Martha Wells. A short and sweet novella about a cyborg that has hacked its own system to give itself free will, and prefers watching soap operas over anything else.