An Overview of Data Visualization: Concepts, Basic Ideas, and Free Software

Data visualization is the scientific study of visual representations of data, defined as extracting information in a summarized form that includes various attributes and variables of the information units.

It is an evolving concept whose scope continuously expands, encompassing advanced technical methods that leverage graphics, image processing, computer vision, and user interfaces to model, display, and animate data in three‑dimensional, surface, and attribute forms, far broader than specialized techniques like 3D modeling.

Overview

The main goal of data visualization is to convey information clearly and effectively through graphical means. While it need not be dull or overly flashy, good visualizations balance aesthetics and functionality to intuitively highlight key aspects of sparse or complex datasets, enabling deeper insight. Poorly balanced designs can become ornamental without achieving the primary purpose of communication.

Data visualization is closely related to infographics, information visualization, scientific visualization, and statistical graphics, and it now serves as a critical, active area in research, teaching, and development, unifying mature scientific visualization with the newer field of information visualization.

Concept

Key concepts in data visualization technology include:

Data space: a multidimensional information space composed of n‑dimensional attributes and m elements.

Data development: the quantitative derivation and computation of data using algorithms and tools.

Data analysis: slicing, cubing, rotating, and other operations on multidimensional data to observe it from multiple perspectives.

Data visualization: representing large datasets as graphical images and using analysis and development tools to discover unknown information.

Various visualization methods have been proposed, which can be classified by principle into geometry‑based, pixel‑oriented, icon‑based, hierarchical, image‑based, and distributed techniques.

Basic Idea

The fundamental idea of data visualization technology is to represent each data item in a database as an individual graphic element, forming a data image from large datasets, while expressing each attribute value in a multidimensional form, allowing observation from different dimensions for deeper analysis.

Free Data Visualization Software

Biosphere3D

Cave5D

Drishti (software)

D3

ECharts

Gephi

Ggplot2

JGraph

Julia (programming language)

JUNG

MayaVi

Pajek

ParaView

Plotly

Prefuse

Renjin

Vis5D

VisAD

VisIt

VisTrails

Voreen

VTK

Chief Review

JavaScript: use D3, JGraph, or ECharts; D3 supports graph data analysis and visualization.

R: use Ggplot2.

Graph data visualization tool: Gephi.

Plotly supports Python, R, Julia, Matlab, and REST APIs.

JGraph supports Java, JavaScript, C#, and other languages for graph drawing.