MIT Press, Cambridge, MA, 02142; 2021; ISBN 9780262045957; 214 pp.; $39.95.Katy Börner’s Atlas of Forecasts lays out a road map of how computational and predictive models work and how they can “help us collectively identify pathways toward desirable futures.” It is easy to understand how years of work went into the Atlas, especially given its use of numerous examples, figures, and extensive references from many disciplines and subdisciplines, including biology, business, chemistry, computer science, ecology, economics, English, epidemiology, environmental science, geography, languages, math and statistics, physics, political science, public health, and sociology. I am sure I am still leaving out some disciplines, but the point in providing this long list reflects Börner’s larger point in writing the Atlas: there are maps and models that can be applied to just about anything today, and well-done models and visualizations can help us better understand complex, interdisciplinary systems to make more informed decisions about the future.This edition of the Atlas includes five parts: (1) Introduction and History, (2) Methods, (3) Models in Action, (4) Science Maps in Action, and (5) Envisioning Desirable Futures. Part 1 includes an overview of modeling basics, explains why models are built, and presents an overview of the different types of models that can be used. While I was excited to see discussions about visualization and validation included up front, given how important these steps are for well-built models, I found it frustrating that most of the overview invited readers to turn to Part 2 to learn more about the key terms. However, having the visualizations come before the discussion of the differences between conceptual, mathematical, computer, and physical models helps readers to quickly digest how systems work and the approaches used to work with data. While brief, both the “History of Models” and “Models that Matter” sections do a solid job conveying how human beings have strived to envision the future with both the successes in terms of implementation and the limitations, given that model outcomes are sometimes not possible or feasible.Part 2 covers modeling methods and is a sorely needed summary of major modeling concepts and terms that is easily consumed by the reader. Every day, data, maps, and models are shown to influence policy, perceptions, and decisions, but those who consume these models and visualizations are often not aware of how systems thinking underlies the framework of complex models. While good models and their resulting visualizations must clearly convey complex information, many decision makers only use the final product. In doing so, they may fail to assess the quality of the model being used. This is where Börner’s work has a great strength: it not only provides background on model design and visualization, but it also details the steps required to build, validate, and verify good models. With ever-increasing data and computing power, this section is necessary reading for everyone (including students, decision makers, and the public) who wants to understand how to evaluate the quality of models that influence public policy, as well as the detail involved in developing a single visualization. Through the use of language that can be understood by a wider audience, there is also enough information presented in this section to use the Atlas in undergraduate courses that require students to think about complex problems or model building (from the conceptual through computational).One major theme of the book comes into focus in Part 3, which explains how models can be used to help determine future constraints and how they can impact decision-making for complex problems such as population growth, natural resources, energy, climate, transportation, and urbanization. There are also valuable discussions on the domains where models can be used, issues of model scale, and how models are used to answer the “when, where, what, and with whom” types of questions that are important in understanding why certain models might be used over others in some circumstances. The Atlas makes use of numerous examples and figures, and examples in the latter half of Part 3 drive home the key points made in the first half of the book by showing multiple model visualizations at varying micro- and macroscales for each major domain (science, technology, education, and policy).Börner notes that the 30 maps contained in Part 4 are designed for different audiences, which include science maps for kids (age 5–14) and visualizations that help bridge academic, government, and industry gaps. However, it was difficult to understand how or why these maps and figures were chosen beyond being part of the larger Atlas series collection. In terms of format, this part is presented as a classical atlas. Each map or figure includes the names of the individuals who produced it, along with a paragraph that describes the data being visualized. As a reader, it would have helped to have more information about why a map or figure was used in the context of the other four parts of the Atlas. Though many of the maps and figures are nice to look at and can be used for various applications, Part 4 is disjointed from the earlier portions of the Atlas, which tell a coherent story about maps, modeling, and applicability to envisioning the future and decision-making. For example, I found myself asking why the “Science Maps for Kids” section included conceptual diagrams of Lord of the Rings, geologic time, the Khan Academy library, and an art museum map alongside visualizations of the political spectrum, gross domestic product, and the fundamental interconnectedness of all things, examples which better relate to the Atlas’s earlier interdisciplinary themes on systems and decision-making. Unfortunately, the disjointed theme continued into the “Science Maps Showing Trends and Dynamics” and “Future of Science Mapping” sections with nice figures and maps that do not tell a clear story. Especially confusing is the fact that, of the 30 maps and figures presented in the “Atlas of Forecasts,” nearly every example lacked future predictions.Part 5 wraps up by providing an overview of modeling opportunities, reducing bias, managing risk, building capacity, and creating actionable forecasts. Like the first three parts of the Atlas, Börner does a great job discussing the key components of how models can be used to help build the future by making sure our actions and decisions are as informed as possible. Following Part 5 are nearly 30 pages of well-researched references and credits, as well as a nice index.Börner’s Atlas of Forecasts is a good resource to have for those who teach concepts related to modeling, mapping, and decision-making. While the Atlas has some issues, it can be used as a solid reference text for faculty and students. Parts 1–3 and Part 5 can be used for early undergraduates who are learning about systems thinking, sustainability, and/or hazard modeling. The Atlas could also serve as a refresher for upper-level students who are working on building models or exploring complex interdisciplinary problems. With the importance of data and modeling increasing every day, from social media to addressing the myriad of environmental problems and hazards, there is value in understanding how models and visualizations work, especially for those from academia, industry, and government who want to make complex problems more relatable to the public. This Atlas demonstrates that by building quality models of our social, technical, and natural systems, scientists and science communicators can help society and policymakers better understand their world.

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