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To communicate information clearly and efficiently, data visualization uses statistical graphics, plots, information graphics and other tools. Numerical data may be encoded using dots, lines, or bars, to visually communicate a quantitative message. Effective visualization helps users analyze and reason about data and evidence. It makes complex data more accessible, understandable and usable. Users may have particular analytical tasks, such as making comparisons or understanding causality, and the design principle of the graphic (i.e., showing comparisons or showing causality) follows the task. Tables are generally used where users will look up a specific measurement, while charts of various types are used to show patterns or relationships in the data for one or more variables.

To communicate information clearly and efficiently, data visualization uses statistical graphics, plots, information graphics and other tools. Numerical data may be encoded using dots, lines, or bars, to visually communicate a quantitative message. Effective visualization helps users analyze and reason about data and evidence. It makes complex data more accessible, understandable and usable. Users may have particular analytical tasks, such as making comparisons or understanding causality, and the design principle of the graphic (i.e., showing comparisons or showing causality) follows the task. Tables are generally used where users will look up a specific measurement, while charts of various types are used to show patterns or relationships in the data for one or more variables.

为了清晰和有效地传达信息，数据可视化使用统计图形、图表、信息图形和其他工具。数字数据可以用点、线或条进行编码，以直观地传达定量信息。有效的可视化帮助用户分析和推理数据和证据。它使复杂的数据更容易访问、理解和使用。用户可能有特定的分析任务，例如进行比较或理解因果关系，以及紧随任务的图形设计原则(例如显示比较或显示因果关系)。表格通常用于用户查找特定的度量指标，而各种类型的图则用于显示单变量或多变量数据中的模式或关系。

数据可视化使用统计图形、图表、信息图形和其他工具，以便清晰有效地传达信息。数字数据可以使用点、线或条进行编码，以直观地传达定量信息。有效的可视化帮助用户分析、推理和验证数据。它使复杂的数据更容易获取、理解和使用。用户可能有特定的分析任务，例如进行比较或理解因果关系，图形的设计原则(例如显示比较或显示因果关系)紧随任务。表通常用于用户查找特定的度量，而各种类型的图表用于显示一个或多个变量的数据中的模式或关系。

Data visualization is both an art and a science. It is viewed as a branch of descriptive statistics by some, but also as a grounded theory development tool by others. Increased amounts of data created by Internet activity and an expanding number of sensors in the environment are referred to as "big data" or Internet of things. Processing, analyzing and communicating this data present ethical and analytical challenges for data visualization. The field of data science and practitioners called data scientists help address this challenge.

Data visualization is both an art and a science. It is viewed as a branch of descriptive statistics by some, but also as a grounded theory development tool by others. Increased amounts of data created by Internet activity and an expanding number of sensors in the environment are referred to as "big data" or Internet of things. Processing, analyzing and communicating this data present ethical and analytical challenges for data visualization. The field of data science and practitioners called data scientists help address this challenge.

== Overview ==

== Overview ==

 

[[File:Data visualization process v1.png|upright=1.5|thumb|Data visualization is one of the steps in analyzing data and presenting it to users.]]

[[File:Data visualization process v1.png|upright=1.5|thumb|Data visualization is one of the steps in analyzing data and presenting it to users.]]

Data visualization refers to the techniques used to communicate data or information by encoding it as visual objects (e.g., points, lines or bars) contained in graphics. The goal is to communicate information clearly and efficiently to users. It is one of the steps in data analysis or data science. According to Vitaly Friedman (2008) the "main goal of data visualization is to communicate information clearly and effectively through graphical means. It doesn't mean that data visualization needs to look boring to be functional or extremely sophisticated to look beautiful. To convey ideas effectively, both aesthetic form and functionality need to go hand in hand, providing insights into a rather sparse and complex data set by communicating its key-aspects in a more intuitive way. Yet designers often fail to achieve a balance between form and function, creating gorgeous data visualizations which fail to serve their main purpose — to communicate information".

Data visualization refers to the techniques used to communicate data or information by encoding it as visual objects (e.g., points, lines or bars) contained in graphics. The goal is to communicate information clearly and efficiently to users. It is one of the steps in data analysis or data science. According to Vitaly Friedman (2008) the "main goal of data visualization is to communicate information clearly and effectively through graphical means. It doesn't mean that data visualization needs to look boring to be functional or extremely sophisticated to look beautiful. To convey ideas effectively, both aesthetic form and functionality need to go hand in hand, providing insights into a rather sparse and complex data set by communicating its key-aspects in a more intuitive way. Yet designers often fail to achieve a balance between form and function, creating gorgeous data visualizations which fail to serve their main purpose — to communicate information".

数据可视化是指通过将数据或信息编码为图形中的可视对象(如点、线或条)来传递数据或信息的技术。目标是清晰有效地向用户传递信息。它是数据分析或数据科学的步骤之一。根据 Vitaly Friedman (2008)的说法，数据可视化的主要目标是通过图形手段清晰有效地传递信息。这并不意味着数据可视化需要看起来无聊才能实用或者非常复杂才能看起来漂亮。为了有效地传达想法，美学形式和功能需要携手并进，通过更直观的方式传达关键方面，提供对一个相当稀疏和复杂的数据集的洞察力。然而，设计师往往无法在形式和功能之间取得平衡，创造华丽的数据可视化效果，而这些效果并不符合他们的主要目的——交流信息。”。

数据可视化是指将数据或信息编码为图形中包含的可视对象(例如点、线或条)来进行通信的技术。其目标是将信息清晰有效地传达给用户。它是数据分析或数据科学的步骤之一。根据Vitaly Friedman(2008)的说法，“数据可视化的主要目标是通过图形手段清晰有效地传递信息。这并不意味着数据可视化需要看起来乏味才能具有功能性，或者需要非常复杂才能看起来漂亮。为了有效地传达思想，美学形式和功能都需要结合在一起，通过以更直观的方式传递数据集的关键方面来提供对相当稀疏和复杂的数据集的洞察。然而，设计师经常不能在形式和功能之间取得平衡，创造了华丽的数据可视化，但却没能满足他们的主要目的——传达信息”。

Indeed, Fernanda Viegas and Martin M. Wattenberg suggested that an ideal visualization should not only communicate clearly, but stimulate viewer engagement and attention.

Indeed, Fernanda Viegas and Martin M. Wattenberg suggested that an ideal visualization should not only communicate clearly, but stimulate viewer engagement and attention.

Data visualization is closely related to information graphics, information visualization, scientific visualization, exploratory data analysis and statistical graphics. In the new millennium, data visualization has become an active area of research, teaching and development. According to Post et al. (2002), it has united scientific and information visualization.

Data visualization is closely related to information graphics, information visualization, scientific visualization, exploratory data analysis and statistical graphics. In the new millennium, data visualization has become an active area of research, teaching and development. According to Post et al. (2002), it has united scientific and information visualization.

数据可视化与信息图形、信息可视化、科学可视化、探索性数据分析和统计图形密切相关。在新的千年里，数据可视化已经成为一个活跃的研究、教学和发展领域。根据波斯特等人的研究。(2002) ，将科学与信息可视化结合起来。

数据可视化与信息图形、信息可视化、科学可视化、探索性数据分析以及统计图形密切相关。在新的千年里，数据可视化已经成为一个活跃的研究、教学和开发领域。根据Post等人的研究(2002) ，科学正与信息可视化结合起来。

==Characteristics of effective graphical displays==

==Characteristics of effective graphical displays==

 

[[File:Minard.png|thumb|upright=2|[[Charles Joseph Minard]]'s 1869 diagram of [[French invasion of Russia|Napoleonic France's invasion of Russia]], an early example of an information graphic]]

[[File:Minard.png|thumb|upright=2|[[Charles Joseph Minard]]'s 1869 diagram of [[French invasion of Russia|Napoleonic France's invasion of Russia]], an early example of an information graphic]]