Information Visualization Definition
Information visualization refers to the use of computer-supported, interactive visual representations of numerical and non-numerical abstract data sets in order to amplify human cognition.
What is Information Visualization?
Information visualization is the practice of giving a computer program a set of instructions for the abstraction and perceptualization of large amounts of inherently non-spatial, unstructured bodies of complex data, with the goal of transforming raw information into visual form and actionable insights. Research in the fields of human-computer interaction, psychology, visual design, graphics, business methods, and computer science supports the presumption that human perceptual processes are more effectively engaged with the use of interactive, visual metaphors than in strictly semantic domains.
One of the most fundamental and intuitive approaches to data analysis, visual information processing is a crucial aid in decision-making, exploration and discovery, communication, and inspiration in applications such as scientific research, financial data analysis, digital libraries, market studies, data mining, drug discovery, crime mapping, and manufacturing production control.
Information visualization and visual analytics play an integral role in modern business intelligence practices, implemented with the help of visual information software and graphic designers. Some information visualization examples include scatter plots, surface plots, histograms, parallel coordinate plots, and tree maps.
How to Organize Information Visually
The first step in the information visualization process is the establishment of the information needs of the target user group through qualitative research, which can then be used to determine the most effective approach for information organization. The process of organizing visual information is fairly linear and consistent:
- Define the problem: Establish what problem the information visualization will solve by asking what the user needs and how they will work with it. Complexity should be determined by the skill level of the user.
- Define the data to be represented: Data should be categorized in order to determine the manner in which it is mapped -- quantitative data, original data, or categorical data.
- Define the dimensions required to represent the data: Dimensions and attributes should be outlined in order to determine the types of analysis that can be conducted -- univariate analysis, bivariate analysis, trivariate analysis, or multivariate analysis.
- Define the structures of the data: Data relationships are commonly structured as either linear, temporal, spatial, hierarchical, or networked relationships.
- Define the interaction required from the visualization: Define how much interaction the user will require from the information visualization in order to determine which model will be the most effective -- static models, transformable models, or manipulable models.
Types of Information Visualization
There is a wide variety of information visualization types, each with unique characteristics designed to help people interpret and understand the information. Some popular tools and visualization techniques and methods for presenting visual information include:
- Cladogram (phylogeny)
- Concept Mapping
- Dendrogram (classification)
- Information visualization reference model
- Graph drawing
- Multidimensional scaling
- Parallel coordinates
- Problem solving environment
Sources of Visual Information and Media
The importance of visual storytelling is greater than ever as humans are confronted with the continuously expanding information explosion. Statistically, engagement is increased markedly with the incorporation of visual elements into content. There are many sources of visual information design and media that act as a repository for general infographics, data visualizations and information visualizations, offering a wide range of interactivity and design elements.
Some popular sources of visual information and media and visual information software include Siege Media, Inforgram, Piktochart, Visme, Easel.ly, Blugraphic, Canva, Venngage, Ceros, Getabout.me, and Visually.
Does OmniSci Offer an Information Visualization Solution?
OmniSci Render is a server-side engine designed for rendering pointmap, scatterplot and polygon visualizations of massive datasets. This gives users zero-latency, exploratory interaction with complex visualizations. OmniSci helps you interactively query, visualize, and power data science workflows over billions of records, helping you find hidden insights beyond the reach of mainstream analytics.