Note: this is the foreword of the book Data Visualization in Society (Amsterdam University Press, 2020)

注意：這是《 社會中的數據可視化 》一書的前言 (阿姆斯特丹大學出版社，2020年)

Geographer John Pickles once wrote that “GIS is a set of tools, technologies, approaches and ideas that are vitally embedded in broader transformations of science, society, and culture.” That’s true of data visualization too, therefore the relevance of the book that you [will] have in your hands, Data Visualization in Society.

地理學家約翰·皮克爾斯(John Pickles)曾經寫道：“地理信息系統(GIS)是一組工具，技術，方法和思想，它們牢固地嵌入了科學，社會和文化的廣泛變革中。” 數據可視化也是如此，因此，您[將]掌握的這本書的相關性，即《 社會中的數據可視化》 。

I often joke — although I’m inclined to believe — that a field X reaches maturity when a parallel field of “philosophy of X” springs into existence. That hasn’t happened yet with data visualization, at least formally. Might we be on the path to it, though? I hope so. Some books have paved the way. Think of David J. Staley’s Computers, Visualization, and History, Charles Kostelnick and Michael Hassett’s Shaping Information, and Wolff-Michael Roth’s Toward and Anthropology of Graphing, all from the early 2000’s. Or, more recently, Orit Halpern’s Beautiful Data (2014), Johanna Drucker’s Graphesis (2014), R.J. Andrews’s Info We Trust (2019), Sandra Rendgen and Julius Wiedemann’s History of Information Graphics (2019), or Data Feminism (2020), by Catherine D’Ignazio and Lauren Klein, who have also contributed to this volume.

我經常開玩笑-雖然我傾向于相信-一個字段X達到成熟時的彈簧“X哲學”到生存的平行場。 數據可視化還沒有發生，至少是正式的。 但是，我們可能會走上這條路嗎？ 但愿如此。 有些書鋪平了道路。 想一想David J. Staley的《 計算機，可視化和歷史》 ，Charles Kostelnick和Michael Hassett的《 Shaping Information 》以及Wolff-Michael Roth的《 Toward and Anthropology of Graphing》 ，都是從2000年代初期開始的。 或者最近， 奧利特·哈珀恩 (Orit Halpern)的《 美麗的數據》 (2014)，約翰娜·德魯克(Johanna Drucker)的Graphesis (2014)，RJ安德魯斯的《 信息我們信任》 (2019)，桑德拉·倫根(Sandra Rendgen)和朱利葉斯·維德曼(Julius Wiedemann)的信息圖形史 (2019)或數據女權主義 (2020) Catherine D'Ignazio和Lauren Klein也為這一卷做出了貢獻。

Books like these prove that writing about visualization doesn’t mean just writing about how to design visualizations, but also about what visualization is, why it is the way it is — and what it could be. Data visualization is a technology — or set of technologies — and, like artifacts such as the clock, the compass, the abacus, or the map, it transforms the way we see and relate to reality. As Langdon Winner suggested in The Whale and the Reactor (1986), a foundational book in the philosophy of technology, to create technologies doesn’t consist just of crafting stuff; rather, when technologies come about “new worlds are being made”. What “new worlds” does visualization generate? That’s a question for a potential philosophy of visualization.

諸如此類的書籍證明，關于可視化的寫作不僅意味著撰寫有關如何設計可視化的文章，而且還涉及關于可視化是什么 ，為什么如此的方式以及可能的方式。 數據可視化是一項技術或一組技術，并且像時鐘，指南針，算盤或地圖等人工制品一樣，它改變了我們觀察和與現實相關的方式。 正如蘭登·溫納 (Langdon Winner)在《鯨魚和React堆》 (1986)中所建議的那樣， 這是一本關于技術哲學的基礎書籍，創造技術并不僅僅包括手工制作。 相反，當技術問世時“正在創造新世界”。 可視化會產生哪些“新世界”？ 這是潛在的可視化哲學的問題。

A philosophy of visualization may derive themes, methodologies, and language from a wide range of disciplines: not only from the philosophy of technology, but also from epistemology, sociology, semiotics, history, ethics, critical theory fields such as critical cartography, or from the philosophies of science, statistics and, art. Philosophers of visualization should reason about visualization’s history, assumptions, conventions, practices, and impacts on individuals, cultures, and societies. They will combine the observational, descriptive, and hermeneutical — dealing with what currently exists and why, — the normative — asking what should or shouldn’t exist or happen, — and the critical — challenging visualization’s core tenets.

可視化哲學可以從廣泛的學科中衍生出主題，方法論和語言：不僅可以從技術哲學中獲得，而且還可以從認識論，社會學，符號學，歷史，倫理學，批評性制圖學等批評性理論領域中獲得，或者從科學，統計和藝術哲學。 可視化的哲學家應該考慮可視化的歷史，假設，慣例，實踐以及對個人，文化和社會的影響。 他們將結合觀察性，描述性和詮釋性-處理當前存在的內容以及為什么-規范性-詢問應該存在或不應該存在或發生什么，以及至關重要的-挑戰可視化的核心原則。

Data Visualization in Society is a collection of chapters by scholars and professionals who don’t call themselves philosophers of visualization but who, in practice, operate as such. I see this book as a relevant step toward the possible inception of the philosophy of visualization as a discipline. I hope it will serve as a starting point for many inquiries by other thinkers. This includes myself: I read all chapters with pleasure and took copious notes on the margins. I know these scribbles will later echo in my own work.

社會中的數據可視化是學者和專業人士所撰寫的章節的集合，這些學者不稱自己為可視化哲學家，但實際上是這樣操作的。 我認為這本書是邁向可視化哲學這一學科可能邁出的重要一步。 我希望它可以作為其他思想家進行許多詢問的起點。 這包括我自己：我很高興地閱讀了所有章節，并在頁邊空白處做了很多注釋。 我知道這些涂鴉稍后會在我自己的作品中產生回響。

That’s the virtue of the best philosophical writing: it doesn’t aspire to settle matters outright, but to inspire further reflection. Data Visualization in Society may spur questions such as: Does visualization pretend to be “objective”, or is it just wrongly perceived as such? What does “objective” mean in the first place? What is the influence of visualization on politics? Is numeracy — numerical literacy — enough to design or read visualizations? Doesn’t the fact that a substantial portion of the public isn’t numerate — or “graphicate”, graphically literate — deepen existing inequalities and even create new ones? What do we mean when we say that a visualization is “beautiful”? Is the goal of visualization to convey facts and data, or can it also spark profound emotional experiences? If so, how? And many more.

那就是最好的哲學著作的優點：它不是渴望徹底解決問題，而是希望引起更多思考。 社會中的數據可視化可能引發諸如以下的問題：可視化是假裝是“客觀的”還是只是被錯誤地認為是這樣？ 首先，“目標”是什么意思？ 可視化對政治有何影響？ 計算能力(數字讀寫能力)是否足以設計或閱讀可視化效果？ 很大一部分公眾不是數字化或“圖形化”，圖形化識字的事實不是加深了現有的不平等甚至造成了新的不平等嗎？ 當我們說可視化是“美麗的”時，我們是什么意思？ 可視化的目的是傳達事實和數據，還是可以激發深刻的情感體驗？ 如果是這樣，怎么辦？ 還有很多。

The variety of topics and approaches of the chapters in this book is astounding, but what most have in common is an open ending: they are links in a chain of reasoning — a dialogue — that extends from the distant past and that, conceivably, and with the contribution of a large critical mass of academics and practitioners of the craft, will continue beyond the foreseeable future. That’s where you come in: do any of these chapters inspire you? Do you agree or disagree with it? Reason why. Argue. Maintain a conversation with the authors. Write and publish, and be open to further responses and critiques. That’s how philosophy begins.

本書各章的主題和方法各異，令人震驚，但它們的最大共同點是開放的結局：它們是推理鏈中的鏈接，即對話，它源于遙遠的過去，并且可以想象，在大量的手Craft.io學者和實踐者的貢獻下，將在可預見的未來繼續發展。 那就是您的來歷：這些章節是否激發了您的靈感？ 您同意還是不同意？ 原因。 爭論。 與作者保持對話。 撰寫和出版，并歡迎進一步的回應和批評。 這就是哲學的開始。

Alberto Cairo is the Knight Chair at the University of Miami and author of How Charts Lie: Getting Smarter About Visual Information

阿爾貝托·開羅 ( Alberto Cairo)是邁阿密大學的騎士主席，并著有《圖表如何說謊：使視覺信息變得更聰明》一書的作者