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Visualization is "the formation of mental visual images, the act or process of interpreting in visual terms or of putting into visual form."[1]. It is "the graphical display of information. The purpose of this graphical display is to provide the viewer a visual means of processing the information."[2]
Visualization, in the sense of "the act or process of interpreting in visual terms or of putting into visual form", has been used in
maps,
technical drawings, and
data plots for over a thousand years.[1]
Overview
The term visualisation
According to the Merriam-Webster's Collegiate Dictionary (2004) the term visualisation originates from the year 1883, and has three distinguished meanings:
"1 : formation of mental visual images
.2 : the act or process of interpreting in visual terms or of putting into visible form"
.3 : the process of making an internal organ or part visible by the introduction (as by swallowing) of a radiopaque substance followed by radiography."[3]
Linda M. Phillips, Stephen P. Norris, John S. Macnab. Visualization in Mathematics, Reading and Science Education. 2010. p. 22.
Definitions of visualisation
Robert Kosara (2007) explained:
"A good part of the confusion about visualization comes from the fact that there is no clear or generally accepted definition of visualization. Such a definition would clearly vary between fields, but at least within one field (like computer science, design, illustration, etc.)..."[4]
Hereby Kosara (2007) made the following distinction in visualisation:
"Two cultures exist in visualization: very technical, analysis-oriented work on the one, and artistic pieces on the other hand.[4].
This article will focus on the first: the technical, analysis-oriented work.
The act of generating images
Visualization is an old term which has previously been defined as:
"the formation of visual images; the act or process of interpreting in visual terms or of putting into visual form."[1]
More recently in the
computer science community a new definition has been added:
"A tool or method for interpreting image data fed into a computer and for generating images from complex multi-dimensional data sets".[1]
In this approach
Information visualisation focusses on increasing our ability to perform these and other cognitive activities. Visualisation as a organized subfield of computer science dates from the Nation Science Foundation report "Visualization in Scientific Computing" by B.H. McCormick and others from 1987. The focuss on tools to permit handling large sets of scientific data and the enhancement of the ability to see phenomena in data resulted in the field of
scientific visualisation.[5]
Visualization and communication
In short visualization is the
graphical display of
information. To be effective visualization must draw upon the
knowledge base of the viewer. If the viewer does not posess the knowledge to understand the graphical entities and the relations between them the visualization does not achieve its goal. Visualization has many applications according to Steven Segenchuk (1997), which can be classified into two categories:[2]
Data Exploration: the practice of using visualization techniques to find unforeseen relationships between data points or sets of points in large databases.
Communicating Information: the application of visualization techniques to communicate information that is already known.
It is based on (non-visual) data. The data to be visualized must come from outside the program, and the program must be able (at least in principle) to work on different data sets. Also, visualization is not image processing or photography; if the source data is an image and is used as an image in the result, it is not being visualized[4].
It produces an image. Clearly, each visualization has the goal of producing one or more images from the data, and the visual must be the primary means of communicating the data. Other media can be part of a visualization, but the visualization must be able to stand on its own[4].
The result is readable and recognizable. There are many ways to transform data into images, most of which do not allow the viewer to understand the underlying data. A visualization must produce images that are readable by a viewer, even if that requires training and practice. Visualization images must also be recognizable as such, and not appear to be something else[4].
History
Visualization, in the sense of the act or process of interpreting in visual terms or of putting into visual form, has been used in
maps,
technical drawings, and
data plots for over a thousand years.[1]
The earliest known
map is a matter of some debate, both because the definition of "map" is not sharp and because some artifacts speculated to be maps might actually be something else. A wall painting, which may depict the ancient Anatolian city of
Çatalhöyük, previously known as Catal Huyuk or Çatal Hüyük, has been dated to the late 7th millennium BCE.[6] The
ancient Greeks and
Romans created maps, beginning at latest with
Anaximander in the 6th century BC.
Ptolemy's world map is a map of the known world to Western society in the 2nd century A.D. As early as the 700s, Arab scholars were translating the works of the
Greek geographers into Arabic.[7]
In
ancient China, geographical literature spans back to the 5th century BC. The oldest extant Chinese maps come from the
State of Qin, dated back to the 4th century BC, during the
Warring States Period. In the book of the Xin Yi Xiang Fa Yao, published in 1092 by the
Chinese scientist
Su Song, a
star map with cylindrical projection similar to the later and apparently, separately invented,
Mercator projection. Early forms of
cartography of India included legendary paintings; maps of locations described in Indian
epic poetry, for example, the Ramayana. Indian cartographic traditions also covered the locations of the
Pole star, and other constellations of use. These
charts may have been in use by the beginning of the
Common Era for purposes of navigation.
The beginning of contemporary
engineering drawing originates from 15th century renaissance artists like
Filippo Brunelleschi, who in about 1415 demonstrated the geometrical method of
perspective, used today by artists, by painting the outlines of various
Florentine buildings onto a mirror.
Leonardo da Vinci further developed perspective and technical drawing, using geometric principles from famous Greek mathematicians like
Pythagoras of Samos, and
Euclid of Alexandria.
The earliest seeds of
data visualization 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”.[8]
Charles Minard's information graphic of Napoleon's march, published in 1869.
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.[8]
Computer graphics has from its beginning been used to study scientific problems. However, in its early days the lack of graphics power often limited its usefulness. The recent emphasis on
scientific visualization started in 1987 with the special issue of Computer Graphics on Visualization in
Scientific Computing. Since then there have been several conferences and workshops, co-sponsored by the
IEEE Computer Society and
ACM SIGGRAPH, devoted to the general topic, and special areas in the field, for example volume visualization.
Computer graphics are graphics created by computers and, more generally, the
representation and
manipulation of
pictorial data by a
computer. The term computer graphics includes almost everything on computers that is not text or sound. Today nearly all computers use some graphics and users expect to control their computer through icons and pictures rather than just by typing.[9] The term Computer Graphics has several meanings:
the representation and manipulation of pictorial data by a computer
the various
technologies used to create and manipulate such pictorial data
the sub-field of
computer science which studies methods for digitally synthesizing and manipulating visual content.
Today computers and computer-generated images touch many aspects of our daily life. Computer imagery is found on television, in newspapers, in weather reports, and during surgical procedures. A well-constructed graph can present complex statistics in a form that is easier to understand and interpret. Such graphs are used to illustrate papers, reports, theses, and other presentation material. A range of tools and facilities are available to enable users to visualize their data, and computer graphics are used in many disciplines. [10]
A
chart is a visual representation of
data, in which the data are represented by
symbols such as bars in a
bar chart or lines in a
line chart.[11] A chart can represent
tabularnumeric data,
functions or some kinds of qualitative structures. The term "chart" as a visual representation of
data has multiple meanings.
A data chart is a type of
diagram or
graph, that organizes and represents a set of numerical or qualitative data.
Maps that are ardorned with extra information for some specific purpose are often known as charts, such as a
nautical chart or
aeronautical chart.
Other domain specific constructs are sometimes called charts, such as the
chord chart in music notation or a
record chart for album popularity.
Charts are often used to ease understanding of large quantities of data and the relationships between parts of the data. Charts can usually be read more quickly than the raw data that they are produced from. They are used in a wide variety of fields, and can be created by hand (often on
graph paper) or by computer using a
charting application.
Data visualization is 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.[8]
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, library and bibliographic databases, networks of relations on the internet, and so forth.[8]
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.[8]
Scientific visualization is another present field, 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.[8]
Business Information Visualization: Business Information Visualization is a relatively new field and has just started to gain researchers' and practitioners' attention. Similar to Scientific Visualization and Information Visualization, it is intended to consider human cognition and perception characteristics and provide insight into data by computer generated visual representations. However, owing to the nature of business data, Business InformationVisualization faces special challenges such as dealing with non-geometric data and incorporating human problem-solving processes. In research and practice, there is a need to understand the specific challengesof visualizing business data and the procedures of how to do it.[16]
^[1] "A Tale of two obsessed archeologists, one ancient city, and nagging doubts about whether science can ever hope to reveal the past" by Robert Kunzig. Discover Magazine, May 1999.
^Weimao Ke, Katy Borner and Lalitha Viswanath (2004).
"Major Information Visualization Authors, Papers and Topics in the ACM Library". In: Proceedings of the IEEE Symposium on Information Visualization table of contents p. 216.1.: The presented work aims to identify major research topics, co-authorships, and trends in the IV Contest 2004 dataset. Co-author, paper-citation, and burst analysis were used to analyze the dataset.
^These scientists listed where the first to publish books about these fields in the 1980s and 1990s.
^Dr. Ping Zhang (2000). [
http://melody.syr.edu/pzhang/publications/Encyclopedia_00_01_Zhang.pdf.
"Business Information Visualization: Guidance for Research and Practice". Published in: Encyclopedia of Microcomputers, Volume 27, Supplement 6, 61-77, 2001. And in: Encyclopedia of Library and Information Science, Volume 69, Supplement 32, 1-17, 2000.
NovoSpark Visualizer - an advanced visualization tool that enables qualitative analysis of multidimensional data through the exploration of a graphical image.