Information visualization or information visualization is the study of (interactive) visual representations of abstract data to reinforce human cognition. The abstract data include both numerical and non-numerical data, such as text and geographic information. The naming of subfields is sometimes confusing. One accepted definition is that it's information visualization when the spatial representation is chosen, whereas it's scientific visualization when the spatial representation is given.

The field of information visualization has emerged "from research in human-computer interaction, computer science, graphics, visual design, psychology, and business methods. It is increasingly applied as a critical component in scientific research, digital libraries, data mining, financial data analysis, market studies, manufacturing production control, and drug discovery".

Information visualization presumes that "visual representations and interaction techniques take advantage of the human eye’s broad bandwidth pathway into the mind to allow users to see, explore, and understand large amounts of information at once. Information visualization focused on the creation of approaches for conveying abstract information in intuitive ways."

Data analysis is an indispensable part of all applied research and problem solving in industry. The most fundamental data analysis approaches are visualization (histograms, scatter plots, surface plots, tree maps, parallel coordinate plots, etc.), statistics (hypothesis test, regression, PCA, etc.), data mining (association mining, etc.), and machine learning methods (clustering, classification, decision trees, etc.). Among these approaches, information visualization, or visual data analysis, is the most reliant on the cognitive skills of human analysts, and allows the discovery of unstructured actionable insights that are limited only by human imagination and creativity. The analyst does not have to learn any sophisticated methods to be able to interpret the visualizations of the data. Information visualization is also a hypothesis generation scheme, which can be, and is typically followed by more analytical or formal analysis, such as statistical hypothesis testing.

Specific methods and techniques

• Cartogram
• Cladogram (phylogeny)
• Concept Mapping
• Dendrogram (classification)
• Information visualization reference model
• Graph drawing
• Heatmap
• HyperbolicTree
• Multidimensional scaling
• Parallel coordinates
• Problem solving environment
• Treemapping

Applications

Information visualization insights are being applied in areas such as:

• Scientific research
• Digital libraries
• Data mining
• Information graphics
• Financial data analysis
• Health care
• Market studies
• Manufacturing production control
• Crime mapping
• eGovernance and Policy Modeling

American Journal of Computer Science and Engineering Survey (IPACSES) is a peer review open access journal publishing the research in computer science and engineering survey. Journal announces papers for the upcoming issue release. Interested can submit your manuscripts through online portal or trough email at computersci@scholarlymed.com

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American Journal of Computer Science and Engineering Survey (IPACSES)

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