Mapping Scientific Frontiers: The Quest for Knowledge Visualization

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Science mapping is still in its infancy and many intellectual challenges remain to be investigated and many of which are outlined in the final chapter. In this new edition Chaomei Chen has provided an essential text, useful both as a primer for new entrants and as a comprehensive overview of recent developments for the seasoned practitioner. Beyond the Horizon Springer, , Allow this favorite library to be seen by others Keep this favorite library private.

Mapping Scientific Frontiers: The Quest for Knowledge Visualization

Find a copy in the library Finding libraries that hold this item Electronic books Ebook Additional Physical Format: The Quest for Knowledge Visualization. Document, Internet resource Document Type: Chaomei Chen Find more information about: In its revised edition, this book examines the history and current developments in knowledge visualization from an interdisciplinary perspective, from theories of invisible colleges and competing paradigms to practical applications of visualization techniques.

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Cancel Forgot your password? Second edition View all editions and formats. Communication in science -- Graphic methods. Pioneer 10 was headed towards the constellation of Taurus The Bull. It will take Pioneer over 2 million years to pass by one of the stars in the constellation. Pioneer 11 was launched in It is headed toward the constellation of Aquila The Eagle , Northwest of the constellation of Sagittarius. Pioneer 11 may pass near one of the stars in the constellation in about 4 million years. One of the correspondents, Eric Burgess, visualized Pioneer 10 as mankind's first emissary beyond our Solar System.

This spacecraft should carry a special message from mankind, a message that would tell any finder of the spacecraft a million or even a billion years that planet Earth had evolved an intelligent species that could think beyond its own time and beyond its own Solar System. A short while earlier, Sagan had been involved in a conference in the Crimea devoted to the problems of com- municating with extraterrestrial intelligence.

Frank Drake, Di- rector of the National Astronomy and Ionosphere Center at Cornell University, Sagan designed a type of message that might be used to communicate with an al- ien intelligence. Sagan was enthusiastic about the idea of a message on the Pioneer spacecraft.

He and Drake designed a plaque, and Linda Salzman Sagan prepared the artwork. They presented the design to NASA; it was accepted to put on the spacecraft. The plaque design was etched into a gold- anodized aluminum plate The bracketing bars on the far right are the representation of the number 8 in binary form , where one is indicated above by the spin-flip radiation transition of a hydrogen at- om from electron state spin up to state spin down that gives a characteristic radio wave length of 21 cm 8.

The bottom of the plaque shows schematically the path that Pi- oneers 10 and 11 took to escape the solar system - starting at the third planet from the Sun accelerating with a gravity assist from Jupiter out of the solar system. Al- so shown to help identify the origin of the spacecraft is a radial pattern etched on the plaque that represents the position of our Sun relative to 14 nearby pulsars i. The plaque may be considered as the cosmic equivalent to a message in a bottle cast into the sea.

Sometime in the far distant future, perhaps billions of years from now, Pioneer may pass through a planetary system of a remote stellar neighbor, one of whose planets may have evolved intelligent life. If that life possesses the technical ability and curiosity, it may detect and pick up the spacecraft and inspect it. Then the plaque with its message from Earth may be found and deciphered.

Pioneer 10 will be out there in interstellar space for billions of years. One day it may pass through the planetary system of a remote stellar neighbor, one of whose planets may have evolved intelligent life. Then the plaque with its mes- sage from Earth should be found and possibly deciphered. Due to the loss of communication, we may never hear from it again unless one day it could be picked up by intelligent aliens in the deep space. Voyager 1 and 2 were launched in the summer of They have become the third and fourth human built artifacts to escape our solar system.

The two space- craft will not make a close approach to another planetary system for at least 40, years. The Voyager carried sounds and images to portray the diversity of life and cul- ture on Earth. These materials are recorded on a inch gold-plated copper disk. They assembled images and a variety of natural sounds, such as those made by surf, wind and thunder, birds, whales, and other animals. Each record is encased in a protective aluminum jacket, together with a cartridge and a needle.

Instructions, in symbolic language, explain the origin of the spacecraft and indicate how the record is to be played. The images are en- coded in analog form. It contains the spoken greetings, begin- ning with Akkadian, which was spoken in Sumer about six thousand years ago, and ending with Wu, a modern Chinese dialect. Following the section on the sounds of Earth, there is an eclectic minute selection of music, including both Eastern and Western classics and a variety of ethnic music. It will be forty thou- sand years before they make a close approach to any other planetary system.

But the launching of this bottle into the cosmic ocean says something very hopeful about life on this planet. The disks are like a phonograph record. Car- tridge and needle are supplied, along with some simple diagrams, which represent symbolically the spacecraft's origin and instructions for playing the disk. Now see if you would be able to understand them if you were an alien. This is the story behind the creation of the record, and includes a full list of everything on the record.

On the other hand, this surrealistic paint- ing certainly makes us think deeper about the role of our language. The apparent contradiction between the visual message conveyed by the picture of a pipe and the statement made in words underlines the nature of language and interrelation- ships between what we see, what we think, and what we say.

Philosophers study such questions in the name of hermeneutics. Hermeneutics can be traced back to the Greeks and to the rise of Greek philosophy. Hermes is the messenger of the gods, he brings a word from the realm of the wordless; hermeios brings the word from the Oracle. The root word for hermeneutics is the Greek verb hermeneuein, which means to interpret. We see through, with, and by means of instruments Ihde, Science has found ways to en- hance, magnify, and modify its perceptions.

Ihde refers to this approach as perceptual hermeneutics. Key features of perceptual hermeneutics are repeatable Gestalt, visualizable, and isomorphic. Ihde noted that Leonardo da Vinci's depictions of human anatomy show mus- culature, organs, and the like and his depictions of imagined machines in his tech- nical diaries were indeed in the same style - both exteriors and interiors were visu- alized. What had been invisible or occluded became observable. These imaging technologies have similar effects as da Vinci's exploded diagram style — they transform non-visual information to vis- ual representations.

Two types of imaging technologies are significant: Imaging technologies increasingly dominate contemporary scientific herme- neutics. The simplest of Gestalt features is the appearance of a figure against a ground, or the appearance of a foreground figure in a background. Usually, we are able to single out some features from a background without any problems, alt- hough sometimes it takes a lot more perceptual and cognitive processing before we can be certain what forms the foreground and what forms the background.

Ge- stalt patterns, for example, are often connected to the moment of an "Aha! Do you see a vase or two people facing each other in Figure 1. It depends on which one you think is the figure. If you take the white vase as the figure, then the two faces will recede into the background. The figure-ground switch in this picture represents a typical Gestalt switch. The same set of pixels can be interpret- ed as the parts of totally different patterns at a higher level. Does the figure show a vase or two faces? The isomorphism, meaning the same shape, makes it easy to connect.

In Ih- de's words: For example, the transparent and translucent microor- ganisms in "true color" were difficult to see. It was false coloring that turned mi- croscopic imaging techniques to a standard technique within scientific visual her- meneutics. Hermeneutics brings a word from the wordless. Information visualization aims to bring insights into abstract information to the viewer.

In particular, information visualization deals with information that may not readily lend itself to geometric or spatial representations. The subject of this book is about ways to depict and in- terpret a gigantic "pipe" of scientific frontiers with reference to the implications of how visualized scientific frontiers and real ones are interrelated. As shown in the history of the continent drift theory, a common feature of a re- search front is the presence of constant debates between competing theories and how the same evidence could be interpreted from different views.

These debates at a disciplinary scale will be used to illustrate the central theme of this book - map- ping scientific frontiers. How can we take snapshots of a "battle ground" in scien- tific literature? How can we track the development of competing schools of thought over time? From a hermeneutic point of view, what are the relationships between "images" of science and science itself? How do we differentiate the foot- prints of science and scientific frontiers? Some show the power of visual languages throughout the history of man- kind.

Some underline limitations of visual languages. Through these examples, we will be able to form an overview of the most fundamental issues in grasping the dynamics of the forefront of science and technology. In other words, our vision is biased and selective. Gestalt is a Germany word, which essen- tially means a tendency of recognizing a pattern, i. The study of pattern-seeking behavior is a branch of psychology called Gestalt psychology. Human being's perception has a tendency to seek patterns out of what we see, or what we expect to see.

A widely known example is the face on Mars, which reminds us how our perceptual system can sometimes cheat on us. Gestalt psychology emphasizes the importance of organizational processes of perception, learning, and problem solving. They believe that individuals are pre- disposed to organize information in particular ways. This includes optical illusions. The word Gestalt in vidual parts. German means structured whole. For example, according to the law of proximity, people tend to perceive as a unit those things that are close together in space.

Problem solving in- other. Human beings have the tendency of seeking patterns. Gestalt psychology con- siders perception an active force. We perceive a holistic image that means more than the sum of parts. We first see an overall pattern, then go on to analyze its de- tails. Personal needs and interests drive the detailed analysis. Like a magnetic field, perception draws sensory imagery together into holistic patterns.

According to Gestalt theory, perception obeys an innate urge towards simplification by coher- ing complex stimuli into simpler groups. Grouping effects include proximity, similarity, continuity, and line of direction. See if you can see two figures alternatively, or even simulta- neously.

This often implies that information visualization primarily deals with ab- stract, non-spatial data. Transforming such non-spatial data to intuitive and meaningful graphical representations is therefore of fundamental importance to the field. The transformation is also a creative process in which designers assign new meanings into graphical patterns.

Like art, information visualization aims to communicate complex ideas to its audience and inspire its users for new connec- tions. Like science, information visualization must present information and asso- ciated patterns rigorously, accurately, and faithfully C. There are a number of widely read reviews and surveys of information visuali- zation S.

There are several books on information visualization, notably S. Chen, a; Spence, ; Ware, A more recent overview can be found in C. The goal of information visualization is to reveal patterns, trends, and other new insights into an information rich phenomenon. Information visualization par- ticularly aims to make sense of abstract information. A major challenge in infor- mation visualization is to develop intuitive and meaningful visual representations of non-spatial and non-numerical information so that users can interactive explore the same dataset from a variety of perspectives.

The mission of information visu- alization is well summarized in S. A simple answer is that they are unique in terms of their corresponding research communities. They do overlap, but largely differ. Here are some questions that might further clarify the scope of information visualization. First, is the original data numerical? Graphical depictions of quantitative infor- mation are often seen in the fields of data visualization, statistical graphics, and cartography. For example, is a plot of daily temperatures of a city for the last 2 years qualified as information visualization?

The answer to this question may de- pend on another question: As Michael Friendly and Daniel J. Denis put it, unless you know its history, everything might seem novel. By the same token, what is complex and novel today may become trivial in the future. A key point to differentiate infor- mation visualization from data visualization and scientific visualization is down to the presence or absence of data in quantitative forms and how easy one can trans- form them to quantitative forms.

This is why researchers emphasize the ability to represent nonvisual data in information visualization. Second, if the data is not spatial or quantitative in nature, what does it take to transform it to something that is spatial and visual? This step involves visual de- sign and the development of computer algorithms. It is this step that clearly distin- guishes information visualization from its nearest neighbors such as quantitative data visualization. More formally, this step can be found in an earlier taxonomy of information visualization, which models the process of information visualization in terms of data transformation, visualization transformation, and visual mapping transformation.

Data transformation turns raw data into mathematical forms. Vis- ualization transformation establishes a visual—spatial model of the data. Visual mapping transformation determines the appearance of the visual—spatial model to the user. On the other hand, if the data is quantitative in nature, researchers and designers are in a better position to capitalize on this valuable given connection.

The connection between scientific and artistic aspects of information visualiza- tion is discussed in terms of functional information visualization and aesthetic in- formation visualization. The holy grail of information visualization is for users to gain insights.

In gen- eral, the notion of insight is broadly defined, including unexpected discoveries, a deepened understanding, a new way of thinking, eureka-like experiences, and oth- er intellectual breakthroughs. In early years of information visualization, it is believed that the ability to view the entirety of a data set at a glance is important to discover interesting and other- wise hidden connections and other patterns. More recently, it is realized, with the rise of visual analytics, that the actionability of information visualization is essen- tial and it emphasizes the process of searching for insights instead of the notion of insights per se.

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Researchers have identified a number of stages of the process of information visualization, namely mapping data to visual form, designing visual structures, and view transformations. Mapping data to visual form involves the transfor- mations of data tables, variable types, and metadata. Visual structures can be di- vided into spatial substrate, marks, connection and enclosure, retinal properties, and temporal coding. View transformations concern location probes, viewpoint controls, and distortion.

The origins of information visualization involve computer graphics, scientific visualization, information retrieval, hypertext, geographic information systems, software visualization, multivariate analysis, citation analysis and others such as social network analysis. A motivation for applying visualization techniques is a need to abstract and transform a large amount of data to manageable and meaning- ful proportions. Analysis of multidimensional data is one of the earliest applica- tion areas of information visualization.

For example, Alfred Inselberg demonstrat- ed how information visualization could turn a multivariate analysis into a 2- dimensional pattern recognition problem using a visualization scheme called par- allel coordinates Inselberg, Research in visual information retrieval has made considerable contributions to information visualization. However, a dashboard that is full of blinking lights is probably not informative either.

The precise mean- ings conveyed by specific colors are strongly influenced by the local culture where the system is located. For example, trends colored in green in a financial visualiza- tion would be interpreted positively, whereas contours colored in dark blue in a geographic information system may imply something that is under the sea level. Mapping scientific frontiers can draw valuable insights from many exciting ex- emplars of information visualization. We will see in later chapters what constitutes the paradigmatic structure of hypertext.

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It is geographic configurations that pro- vide the base map of a thematic map. Indeed, thematic maps provide a prosperous metaphor for a class of information visualization known as information landscape. Notable examples include ThemeView J. ManyEyes is a more recent example. ManyEyes enables many people to have a taste of what is like to create your own information visualization that they would otherwise have no such chance at all.

The public-oriented design significantly simplifies the entire process of infor- mation visualization. Furthermore, ManyEyes is indeed a community-building en- vironment in which one can view visualizations made by other users, make com- ments, and make your own visualizations. These reasons alone would be enough to earn ManyEyes a unique position in the development of information visualiza- tion.

ManyEyes and Wikipedia share some interesting characteristics—both tap in social construction and both demonstrate emergent properties of a self-organizing underlying system. Modeling and visualizing intellectual structures from scientific literature have reached a new level in terms of the number of computer applications available, the number of researchers actively engaged in relevant areas, and the number of rele- vant publications.

Traditionally, the scientific discipline that has been actively ad- dressing issues concerning science mapping and intellectual structure mapping is information science.

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Information science itself constitutes of two sub-fields: Both information retrieval and citation analysis take the widely accessible scientific literature as their input. However, in- formation retrieval and citation analysis concentrate on disjoint sections of a doc- ument. The ultimate challenge for information visualization is to invent and adapt powerful visual-spatial metaphors that can convey the underly- ing semantics.

Information retrieval has brought many fundamental inspirations and challeng- es to the field of information visualization. It becomes a unique field of study on its own and yet it has the po- tential to be applicable to a wide range of scientific domains. Our focus is on the growth of scientific knowledge and what are the key problems to solve and what are the central tasks to support.

Instead of focusing on locating specific items in scientific literature, we turn to higher levels of granularity — scientific paradigms and their movements in scientific frontiers. Visual analytics can be seen as the second generation of information visualiza- tion.

Visual analytics is the science of analytical reasoning facilitated by vis- ual interactive interfaces that focuses on analytical reasoning facilitated by interac- tive visual interfaces J. Visual analytics is a multidisciplinary field. It brings together several scientific and technical communities from computer science, information visualization, cog- nitive and perceptual sciences, interactive design, graphic design, and social sci- ences. It addresses challenges involving analytical reasoning, data representations and transformations, visual representations and interaction techniques, and tech- niques to support production, presentation, and dissemination of the results.

Alt- hough visual analytics has some overlapping goals and techniques with infor- mation visualization and scientific visualization, it is especially concerned with sense-making and reasoning and it is strongly motivated by solving problems and making sound decisions.

Visual analytics integrates new computational and theory-based tools with in- novative interactive techniques and visual representations based on cognitive, de- sign, and perceptual principles. Today, visual analytics centers are found in several countries, including Canada, Germa- ny, the United Kingdom, and the United States; and universities integrated visual analytics into their core information sciences curricula which made the new field a recognized and promising outgrowth of the fields of information visualization and scientific visualization P.

The key contribution of visual analytics is that it is motivated by analytic rea- soning and decision making needs with high uncertainty data. This is precisely what is needed for mapping scientific frontiers, i. In the second edition of the book, we introduce the latest development of visual analytics in relation to supporting analytic tasks pertinent to mapping scientific frontiers.

The book is also suitable for readers who are interested in scientometrics, information visualization, and visual analytics as well as science of science policy and research evaluation. The story was later expanded to six blind men in India. As the folktale goes, six blind men went to figure out what the elephant looks like.

The sixth, seizing on the swinging tail and, was convinced that the elephant must be like a rope.

Mapping scientific frontiers : the quest for knowledge visualization

They could not agree what an elephant is really like. The moral of this folktale is that we are in a similar situation in which scientists receive all sorts of messages about scientific frontiers. According to this model, the work of scientists consists of the enrolment and juxtaposition of heterogeneous elements — rats, test tubes, colleagues, journal articles, grants, papers at scientific confer- ences, and so on — which need continual management.

Scientists simultaneously reconstruct social contexts — labs simultaneously rebuild and link the social and natural contexts upon which they act. Examining inscriptions is a key approach used for ANT. The other is to "follow the actor," via interviews and ethnographic research. Inscriptions include journal articles, conference papers, presentations, grant proposals, and patents.

Inscriptions are the major products of scientific work Latour and Woolgar, ; Callon, Law, and Rip, In Chapter 3, we will describe co-word analysis, which was originally developed for analyzing inscrip- tions. Different genres of inscriptions may send messages to scientists. On the one hand, messages from each genre of inscriptions form a snapshot of scientific fron- tiers. Each individual discipline has its own research agenda and practices, its own theories and methods. On the other hand, mapping scientific frontiers by its very nature is interdisciplinary. One must transcend disciplinary boundaries so that each contributing approach can fit into the context.

Such maps can also simply be used as a convenient means of depicting the way research areas are distributed and conveying added meaning to their relationships. Even with a database that is completely up-to-date, we are still only able to cre- ate maps that show where research fronts have been. Because of the publication cycle, research has already moved on by the time the corresponding journal arti- cles are published.

Except in one's own area of expertise, these maps give an oth- erwise unrealized view of where the action is and give a hint where it may be go- ing. However, as we expand the size of the database from one year to a decade or more, the map created through citation analysis provides a historical, indeed histo- riographical, window on the field that we are investigating.

From a global viewpoint, these maps show relationships among fields or disci- plines. The labels attached or embedded in the graphics reveal their semantic con- nections and may hint at why they are linked to one another. Furthermore, the maps reveal which realms of science or scholarship are being investigated today and the individuals, publications, institutions, regions, or nations currently pre- eminent in these areas. By using a series of chronologically sequential maps, one can see how knowledge advances. While maps of current data alone cannot predict where re- search will go, they can be useful indicators in the hands of informed analysts.

By observing changes from year to year, trends can be detected. Thus, the maps be- come forecasting tools. And since some co-citation maps include core works, even a novice can instantly identify those articles and books used most often by mem- bers of the "invisible college.

This stands in contrast to the relatively simple but arduous manual method we used over 30 years ago to create a historical map of DNA research from the time of Mendel up to the work of Nierenberg and others.

Mapping Scientific Frontiers

Samuel Bradford referred to "a picture of the universe of dis- course as a globe, on which are scattered, in promiscuous confusion, the mutually related, separate things we see or think about. Indeed, it gave birth to scientometrics and new life to bibliometrics. John Bernal , a prominent international scientist and an X-ray crys- tallography scientist, was a pioneer in social studies of science or "science of sci- ence".

To Bernal, science is the very basis of philosophy. There was no sharp distinction between the natural sciences and the social sciences for Bernal, and the scientific analysis of society was an enterprise continuous with the scientific analysis of nature. For Bernal, there was no philosophy, no social theory, and no knowledge independent of science. Science was the foundation of it all. A new- born theory may grow stronger and become dominant over time. On the other hand, it might well be killed in its cradle. What are the factors that determine the fate of a new theory?

In his new book, Chaomei Chen takes us on a journey through this history, touching on predecessors, and then leading us firmly into the new world of Mapping Scientific Frontiers. Building on the foundation of his earlier book, Information Visualization and Virtual Environments, Chen's new offering is much less a tutorial in how to do information visualization, and much more a conceptual exploration of why and how the visualization of science can change the way we do science, amplified by real examples.

The first, consisting of the initial four chapters, covers history and predecessors. Kuhn's theory of normal science punctuated by periods of revolution, now commonly known as paradigm shifts, motivates the work. Relevant predecessors outside the traditional field of information science such as cartography both terrestrial and celestial , mapping the mind, and principles of visual association and communication, are given ample coverage.

Chen also describes enabling techniques known to information scientists, such as multi-dimensional scaling, advanced dimensional reduction, social network analysis, Pathfinder network scaling, and landscape visualizations. No algorithms are given here; rather, these techniques are described from the point of view of enabling 'visual thinking'. Information and computer science professionals would be wise not to skip through these early chapters.

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