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Data and information visualization (data viz/vis or info viz/vis) [2] is the practice of designing and creating easy-to-communicate and easy-to-understand graphic or visual representations of a large amount [3] of complex quantitative and qualitative data and information with the help of static, dynamic or interactive visual items.
A chord diagram is a graphical method of displaying the inter-relationships between data in a matrix. The data are arranged radially around a circle with the relationships between the data points typically drawn as arcs connecting the data. The format can be aesthetically pleasing, making it a popular choice in the world of data visualization.
A co-occurrence network created with KH Coder. Co-occurrence network, sometimes referred to as a semantic network, [1] is a method to analyze text that includes a graphic visualization of potential relationships between people, organizations, concepts, biological organisms like bacteria [2] or other entities represented within written material.
Exploratory data analysis is an analysis technique to analyze and investigate the data set and summarize the main characteristics of the dataset. Main advantage of EDA is providing the data visualization of data after conducting the analysis.
ELKI – Data mining framework in Java with data mining oriented visualization functions. KNIME – The Konstanz Information Miner, a user friendly and comprehensive data analytics framework. Orange – A visual programming tool featuring interactive data visualization and methods for statistical data analysis, data mining, and machine learning.
[3] [4] Similar pursuits are information visualization, data visualization, statistical graphics, information design, or information architecture. [2] Infographics have evolved in recent years to be for mass communication, and thus are designed with fewer assumptions about the readers' knowledge base than other types of visualizations. [5]