Milestones in the History of
Thematic Cartography,
Statistical Graphics,
and Data Visualization

1.  Introduction

The only new thing in the world is the history you don't know.

Harry S. Truman, quoted by David McCulloch

The graphic portrayal of quantitative information has deep roots. These roots reach into histories of thematic cartography, statistical graphics, and data visualization, which are intertwined with each other. They also connect with the rise of statistical thinking up through the 19th century, and developments in technology into the 20th century. From above ground, we can see the current fruit; we must look below to see its pedigree and germination. There certainly have been many new things in the world of visualization; but unless you know its history, everything might seem novel.

A brief overview

The earliest seeds arose in geometric diagrams and in the making of maps to aid in navigation and exploration. By the 16th century, techniques and instruments for precise observation and measurement of physical quantities were well-developed- the beginnings of the husbandry of visualization. The 17th century saw great new growth in theory and the dawn of practice- the rise of analytic geometry, theories of errors of measurement, the birth of probability theory, and the beginnings of demographic statistics and ``political arithmetic''. Over the 18th and 19th centuries, numbers pertaining to people-social, moral, medical, and economic statistics began to be gathered in large and periodic series; moreover, the usefulness of these bodies of data for planning, for governmental response, and as a subject worth of study in its own right, began to be recognized.

This birth of statistical thinking was also accompanied by a rise in visual thinking: diagrams were used to illustrate mathematical proofs and functions; nomograms were developed to aid calculations; various graphic forms were invented to make the properties of empirical numbers- their trends, tendencies, and distributions- more easily communicated, or accessible to visual inspection. As well, the close relation of the numbers of the state (the origin of the word ``statistics'') and its geography gave rise to the visual representation of such data on maps, now called ``thematic cartography''.

Maps, diagrams and graphs have always been (and continue to be) hard to produce, still harder to publish. Initially they were hand drawn, piece-by-piece. Later they were etched on copper-plate and manually colored. Still later, lithography and photo-etching, and most recently, computer software was used, but graphic-makers have always had to struggle with the limitations of available technology- and still do today. Some note-worthy places in the history of visualization must therefore be reserved for those who contributed to the technology.

Most recently, advances in statistical computation and graphic display have provided tools for visualization of data unthinkable only a half century ago. Similarly, advances in human-computer interaction have created completely new paradigms for exploring graphical information in a dynamic way, with flexible user control.

While most of the recent contributions listed here relate to the visual display of statistical data, there has also been considerable interplay with advances in information visualization more generally, particularly for the display of large networks, hierarchies, data bases, text, and so forth, where problems of very-large scale data present continuing challenges.

Varieties of data visualization

Information visualization is the broadest term that could be taken to subsume all the developments described here. At this level, almost anything, if sufficiently organized, is information of a sort. Tables, graphs, maps and even text, whether static or dynamic, provide some means to see what lies within, determine the answer to a question, find relations, and perhaps apprehend things which could not be seen so readily in other forms.

In this sense, information visualization takes us back to the earliest scratches of forms on rocks, to the development of pictoria as mnemonic devices in illuminated manuscripts, and to the earliest use of diagrams in the history of science and mathematics.

But, as used today, the term information visualization is generally applied to the visual representation of large-scale collections of non-numerical information, such as files and lines of code in software systems [66], library and bibliographic databases, networks of relations on the internet, and so forth. In this document we avoid both the earliest, and most of the latest uses in this sense.

Another present field, called scientific visualization, is also under-represented here, but for reasons of lack of expertise rather than interest. This area is primarily concerned with the visualization of 3-D+ phenomena (architectural, meterological, medical, biological, etc.), where the emphasis is on realistic renderings of volumes, surfaces, illumination sources, and so forth, perhaps with a dynamic (time) component. Finally, the areas of visual design and information graphics both draw on, and contribute to, the content presented here, but are also under-represented.

Instead, we focus on the slightly narrower domain of data visualization, the science of visual representation of ``data'', defined as information which has been abstracted in some schematic form, including attributes or variables for the units of information. This topic could be taken to subsume the two main focii: statistical graphics, and thematic cartography.

Both of these are concerned with the visual representation of quantitative and categorical data, but driven by different representational goals. Cartographic visualization is primarily concerned with representation constrained to a spatial domain; statistical graphics applies to any domain in which graphical methods are employed in the service of statistical analysis. There is a lot of overlap, but more importantly, they share common historical themes of intellectual, scientific, and technological development.

In addition, cartography and statistical graphics share the common goals of visual representation for exploration and discovery. These range from the simple mapping of locations (land mass, rivers, terrain), to spatial distributions of geographic characteristics (species, disease, ecosystems), to the wide variety of graphic methods used to portray patterns, trends, and indications.

Milestones Project

The past only exists insofar as it is present in the records of today. And what those records are is determined by what questions we ask.
Wheeler [320,p. 24]

There are many historical accounts of developments within the fields of probability [116], statistics [226,239,273], astronomy [249], cartography [316], which relate to, inter alia, some of the important developments contributing to modern data visualization. There are other, more specialized accounts, which focus on the early history of graphic recording [137,138], statistical graphs [91,92,257,264,286], fitting equations to empirical data [69], cartography [88,162] and thematic mapping [253,223], and so forth; Robinson [253,Ch. 2] presents an excellent overview of some of the important scientific, intellectual, and technical developments of the 15th-18th centuries leading to thematic cartography and statistical thinking.

But there are no accounts that span the entire development of visual thinking and the visual representation of data, and which collate the contributions of disparate disciplines. In as much as their histories are intertwined, so too should be any telling of the development of data visualization. Another reason for interweaving these accounts is that practitioners in these fields today tend to be highly specialized, and unaware of related developments in areas outside their domain, much less their history. Extending Wheeler [320], the records of history also exist insofar as they are collected, illustrated, and made coherent.

This listing is but an initial step in portraying the history of the visualization of data. We started with the developments listed by Beniger and Robyn [21] and incorporated additional listings from Hankins [121], Tufte [291,292,293], Heiser [132], and others (now too numerous to cite individually). In most cases, we cite original sources (where known) for the record; occasional secondary sources are included as well, where they appear to contribute to telling the story.

To convey a real sense of the accomplishments requires much more context- words, images, and, most usefully, interpretation. In this chronological listing, it has proved convenient to make divisions by epochs, and we provide some more detailed commentaries for each of these. The careful reader will be able to discern other themes, relations, and connections, not stated explicitly.

More importantly, we envisage this Milestones Project as the beginning of a contribution to historiography, on the subject of visualization. Some related publications are [79] and [87]. One goal is to provide a flexible, and useful multi-media resource, containing descriptions of events and developments, illustrative images, and links to related sources (web and in print) or more detailed commentaries. Another goal is to build a database which collects, catalogs, organizes, and illustrates these significant historical developments.

The present listing is simply chronological, but, as noted above, we provide some overview for each epoch. We have also begun coding the listings to be dynamically searchable by other criteria, for example by person, place, theme, content, and so forth. A parallel web version may be viewed on the Gallery of Data Visualization site at:

Milestones web site:
In the listings below, PIC: refers to a web link (URL) to a portrait, while IMG: and FIG: refer to graphic images ( FIG for a larger copy of an IMG). To allow more extensive treatments, with commentaries on some people, events, or topics, we use TXT: to refer to a link to related text.

These links should be active in the .pdf and web versions of this document. As a result, the web URLs do not appear in a printed copy, and the many portraits and images we have collected are implicit, rather than shown inline.