InfographInfographics versus data visualizationics Versus Data Visualization
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Infographics versus data visualization
In this new era of visualization, innovative design and rapid increase of data, mostly we use the two term “data visualization" and "infographics," interchangeably. They overlap each other as both are informative, interactive as well as animated and need highly trained people like designers, statisticians, economists, developers, programmers and geneticists. In spite of having common motto in different field, technically there are lots of differences between them.
In data visualization the information is quantifiable and in the form of figure. The entire dataset should be objective and without editing may be well presented. They are much more focused in the gestalt rather than the application of editorial process. In infographics the information is unquantifiable, constructed upon numbers, facts or events and is designed with sensitivity. Sometimes in both cases the source of information are in conformity but the process is different.
The purpose of the visualization is to create sense making dataset or to make it more accessible. Most of the time due to huge dataset and its unwieldy nature, it can just be impossible for human processing. Therefore, generally we like to generate it automatically with the application of algorithms or computer programs on raw numbers. But the purpose of hand-crafted infographics explains the story very specifically to specific audience and is subjective. For infographics, a designer creates visual representation of processed data manually. In visualization, information is presented without context but in infographics, elaborate and explanatory information is presented with context.
The method of presentation in visualization is general but in infographics the presentation method is specific and we cannot use it for another purpose. Data visualization needs much more effort to find an insight into the patterns deeply. But infographics are produced faster compared to data visualization and conveys data quickly. The interesting difference between them is that, there is some hidden, unexpected or surprising part in the dataset that the designer may or may not reveal to its final outcome. But to create infographics designers are aware of the final outcome from the beginning.
Infographics versus data visualization – this debate is never ending, as the line to some extent is less distinct. But for the designer, even this faint distinction matters as without this the appropriate process to the ultimate goal cannot be achieved.
Through this article I want to clarify the fact that, in a discussion on the topic Infographics versus data visualization, the key difference lies in the process. For the user or viewer the difference doesn’t matter as there are no changes visible in the outcome which is valuable for them. But for the designer this is very important, due to the distinction lying in the process. In both process prototypes must be constructed so that Infographics can stand without Data visualization but visualization cannot stand without it. Despite the difference, both give us hope to refined knowledge.
In this new era of visualization, innovative design and rapid increase of data, mostly we use the two term “data visualization" and "infographics," interchangeably. They overlap each other as both are informative, interactive as well as animated and need highly trained people like designers, statisticians, economists, developers, programmers and geneticists. In spite of having common motto in different field, technically there are lots of differences between them.
In data visualization the information is quantifiable and in the form of figure. The entire dataset should be objective and without editing may be well presented. They are much more focused in the gestalt rather than the application of editorial process. In infographics the information is unquantifiable, constructed upon numbers, facts or events and is designed with sensitivity. Sometimes in both cases the source of information are in conformity but the process is different.
The purpose of the visualization is to create sense making dataset or to make it more accessible. Most of the time due to huge dataset and its unwieldy nature, it can just be impossible for human processing. Therefore, generally we like to generate it automatically with the application of algorithms or computer programs on raw numbers. But the purpose of hand-crafted infographics explains the story very specifically to specific audience and is subjective. For infographics, a designer creates visual representation of processed data manually. In visualization, information is presented without context but in infographics, elaborate and explanatory information is presented with context.
The method of presentation in visualization is general but in infographics the presentation method is specific and we cannot use it for another purpose. Data visualization needs much more effort to find an insight into the patterns deeply. But infographics are produced faster compared to data visualization and conveys data quickly. The interesting difference between them is that, there is some hidden, unexpected or surprising part in the dataset that the designer may or may not reveal to its final outcome. But to create infographics designers are aware of the final outcome from the beginning.
Infographics versus data visualization – this debate is never ending, as the line to some extent is less distinct. But for the designer, even this faint distinction matters as without this the appropriate process to the ultimate goal cannot be achieved.
Through this article I want to clarify the fact that, in a discussion on the topic Infographics versus data visualization, the key difference lies in the process. For the user or viewer the difference doesn’t matter as there are no changes visible in the outcome which is valuable for them. But for the designer this is very important, due to the distinction lying in the process. In both process prototypes must be constructed so that Infographics can stand without Data visualization but visualization cannot stand without it. Despite the difference, both give us hope to refined knowledge.
