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Keywords: Diagramming, Diagrams in UML, Information visualization


Visualization is any technique for creating images, animations, or diagrams to communicate a message. Since the beginning of time, visualization through visual imagery, has been an essential form of communication when it comes to communicating abstract or concrete ideas. Throughout history, visualization is seen from cave paintings, Greek geometry, to Egyptian hieroglyphs. Just as its use cases expand time and space, today visualization has an ever expanding application in science, education, engineering, multimedia, medicine, computer graphics, etc. Visualization is a powerful tool. The process of generating visual mental imagery with your eyes open or closed, is known as creative visualization, which goes back to the notion of a "mind's eye."

Scientific visualization

Scientific visualization is a branch of science that is concerned with visualizing scientific phenomenas.

Data visualization

Data visualization is a field that deals with graphic representation of data.

Information visualization

Information visualization is the field of abstract data (numerical and non-numerical) to reinforce human cognition.

Education visualization

Educational visualization is to facilitate the learning of some knowledge (idea, concept, fact, etc.) through visual cues.

Knowledge visualization

Knowledge visualization is associated with knowledge transfer through visuals from person to person.

Product visualization

Product visualization (product rendering) is the act of using renders, images, and artwork to visually communicate products to customers.

Visual communication

Visual communication is the use of visual cues to convey ideas or information.

Visual analytics

Visual analytics is a field that focuses on analytical reasoning through interactive visual interfaces.

The use of visualization to present information is not a new phenomenon, it has been used since the dawn of time in maps, data plots, and scientific drawings. Examples include Ptolemy's Geographia (2nd century AD), a map of China (1137 AD), and Minard's map (1861) of Napoleon's invasion of Russia. Many of these visualizations carry over to computer graphics. The recent emphasis on visualization started in 1987 with the publication of Visualization in Scientific Computing, a special issue of Computer Graphics. 

Decision making increasingly relies on data, often in large volume that is cannot be comprehended without a layer of abstraction, such as a visual representation. However even information that is not statistically demanding may require visual expression. Visualization that uses data is known as data visualization. Data visualization has its roots in the field of statistics and is considered a branch of Descriptive Statistics, although it is often argued to be an art and a science. 


Thanks to the internet and a growing number of affordable tools such as, translating information into visuals is now easy for everyone, regardless of data skills or design skills. However, all visualization should begin by answering two questions to ensure that convenient isn't replacing quality. 

Conceptual or Data-driven?

Is the information conceptual or data-driven?

Declared or Explored?

Is something being declared or explored?

The first question refers to what you have- Information is either visualized as qualitative information (ideas) or plotted as quantitative information (statistics). This refers to the information itself rather than the visual form that is used to represent it. The second question refers to what you are doing- either communication information (declarative) or trying to figure something out (exploratory). Many managers work with declarative visualization, however explanatory visuals are used to confirm or refute a hypothesis or mind for more patterns or trends. These questions combined reveal that there are four types of visual communications. 

Idea illustrations clarify complex ideas by drawing on our ability to understand metaphors and simple designs. Organizational charts or tree diagrams are classical examples of idea illustration. Idea illustrations are clear communication, structure, and logic of ideas.

Idea Generation (ideation, creative process, brainstorming) relies on conceptual metaphors, but it takes place in more informal settings such as early innovation phases or strategy sessions. Idea generation can be done by an individual, team, or organizations. It can also be done alone or in collaboration with design thinking. Diagrams such as mindmaps are helpful in illustrating ideas.

Visual Discovery this is the most complex quadrant, because it holds two categories: testing a hypothesis and minding for patterns and trends. 

Everyday Dataviz Whereas data scientists do most of the work on visual exploration, managers do most of the work on everyday visualizations (Everyday Dataviz). This comprises of usual line charts, bar graphs, pies, and scatter plots. The visualization will communicae a single message, charting only a few variables. The goal is to affirm and set context, since Everyday Dataviz are often used in formal presentation to illustrate clear information about the context of the diagram. The ability to perceive information in graphs and charts is known as graphical perception. Visual information seen in graphs (including color, size, etc.) are said to be 'coded' while the human capacity to infer these codes is known as 'decoding'. 

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