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=== Human perception/cognition and data visualization ===

=== Human perception/cognition and data visualization ===

人类感知/认知与数据可视化

人类感知/认知与数据可视化

Almost all data visualizations are created for human consumption. Knowledge of human perception and cognition is necessary when designing intuitive visualizations.<ref name=":0">{{Cite web|title = Data Visualization for Human Perception|url = https://www.interaction-design.org/literature/book/the-encyclopedia-of-human-computer-interaction-2nd-ed/data-visualization-for-human-perception|website = The Interaction Design Foundation|accessdate = 2015-11-23|archive-url = https://web.archive.org/web/20151123151958/https://www.interaction-design.org/literature/book/the-encyclopedia-of-human-computer-interaction-2nd-ed/data-visualization-for-human-perception|archive-date = 2015-11-23|url-status = live}}</ref> Cognition refers to processes in human beings like perception, attention, learning, memory, thought, concept formation, reading, and problem solving.<ref>{{Cite web|url = https://www.sfu.ca/gis/geog_x55/web355/icons/11_lec_vweb.pdf|title = Visualization|date = |accessdate = 2015-11-22|website = SFU|publisher = SFU lecture|last = |first = |archive-url = https://web.archive.org/web/20160122203157/http://www.sfu.ca/gis/geog_x55/web355/icons/11_lec_vweb.pdf|archive-date = 2016-01-22|url-status = dead}}</ref> Human visual processing is efficient in detecting changes and making comparisons between quantities, sizes, shapes and variations in lightness. When properties of symbolic data are mapped to visual properties, humans can browse through large amounts of data efficiently. It is estimated that 2/3 of the brain's neurons can be involved in visual processing. Proper visualization provides a different approach to show potential connections, relationships, etc. which are not as obvious in non-visualized quantitative data. Visualization can become a means of [[data exploration]].

Almost all data visualizations are created for human consumption. Knowledge of human perception and cognition is necessary when designing intuitive visualizations.<ref name=":0">{{Cite web|title = Data Visualization for Human Perception|url = https://www.interaction-design.org/literature/book/the-encyclopedia-of-human-computer-interaction-2nd-ed/data-visualization-for-human-perception|website = The Interaction Design Foundation|accessdate = 2015-11-23|archive-url = https://web.archive.org/web/20151123151958/https://www.interaction-design.org/literature/book/the-encyclopedia-of-human-computer-interaction-2nd-ed/data-visualization-for-human-perception|archive-date = 2015-11-23|url-status = live}}</ref> Cognition refers to processes in human beings like perception, attention, learning, memory, thought, concept formation, reading, and problem solving.<ref>{{Cite web|url = https://www.sfu.ca/gis/geog_x55/web355/icons/11_lec_vweb.pdf|title = Visualization|date = |accessdate = 2015-11-22|website = SFU|publisher = SFU lecture|last = |first = |archive-url = https://web.archive.org/web/20160122203157/http://www.sfu.ca/gis/geog_x55/web355/icons/11_lec_vweb.pdf|archive-date = 2016-01-22|url-status = dead}}</ref> Human visual processing is efficient in detecting changes and making comparisons between quantities, sizes, shapes and variations in lightness. When properties of symbolic data are mapped to visual properties, humans can browse through large amounts of data efficiently. It is estimated that 2/3 of the brain's neurons can be involved in visual processing. Proper visualization provides a different approach to show potential connections, relationships, etc. which are not as obvious in non-visualized quantitative data. Visualization can become a means of [[data exploration]].

==Terminology==

==Terminology==

术语

术语

Data visualization involves specific terminology, some of which is derived from statistics. For example, author Stephen Few defines two types of data, which are used in combination to support a meaningful analysis or visualization:

Data visualization involves specific terminology, some of which is derived from statistics. For example, author Stephen Few defines two types of data, which are used in combination to support a meaningful analysis or visualization:

== Other perspectives ==

== Other perspectives ==

其他视角

其他视角

There are different approaches on the scope of data visualization. One common focus is on information presentation, such as Friedman (2008). Friendly (2008) presumes two main parts of data visualization: [[statistical graphics]], and [[Thematic map|thematic cartography]].<ref name = "MF08">[[Michael Friendly]] (2008). [http://www.math.yorku.ca/SCS/Gallery/milestone/milestone.pdf "Milestones in the history of thematic cartography, statistical graphics, and data visualization"] {{Webarchive|url=https://web.archive.org/web/20080911042504/http://www.math.yorku.ca/SCS/Gallery/milestone/milestone.pdf |date=2008-09-11 }}.</ref> In this line the "Data Visualization: Modern Approaches" (2007) article gives an overview of seven subjects of data visualization:<ref>[http://www.smashingmagazine.com/2007/08/02/data-visualization-modern-approaches/ "Data Visualization: Modern Approaches"] {{Webarchive|url=https://web.archive.org/web/20080722233419/http://www.smashingmagazine.com/2007/08/02/data-visualization-modern-approaches/ |date=2008-07-22 }}. in: ''Graphics'', August 2nd, 2007</ref>

There are different approaches on the scope of data visualization. One common focus is on information presentation, such as Friedman (2008). Friendly (2008) presumes two main parts of data visualization: [[statistical graphics]], and [[Thematic map|thematic cartography]].<ref name = "MF08">[[Michael Friendly]] (2008). [http://www.math.yorku.ca/SCS/Gallery/milestone/milestone.pdf "Milestones in the history of thematic cartography, statistical graphics, and data visualization"] {{Webarchive|url=https://web.archive.org/web/20080911042504/http://www.math.yorku.ca/SCS/Gallery/milestone/milestone.pdf |date=2008-09-11 }}.</ref> In this line the "Data Visualization: Modern Approaches" (2007) article gives an overview of seven subjects of data visualization:<ref>[http://www.smashingmagazine.com/2007/08/02/data-visualization-modern-approaches/ "Data Visualization: Modern Approaches"] {{Webarchive|url=https://web.archive.org/web/20080722233419/http://www.smashingmagazine.com/2007/08/02/data-visualization-modern-approaches/ |date=2008-07-22 }}. in: ''Graphics'', August 2nd, 2007</ref>

=== Objectives ===

=== Objectives ===

目标

目标

DPA has two main objectives:

DPA has two main objectives:

=== Scope ===

=== Scope ===

范围

范围

With the above objectives in mind, the actual work of data presentation architecture consists of:

With the above objectives in mind, the actual work of data presentation architecture consists of:

== See also ==

== See also ==

另请参阅

另请参阅

{{Div col|colwidth=20em}}

{{Div col|colwidth=20em}}

* [[Analytics]]

* [[Analytics]]

 

* [[Balanced scorecard]]

* [[Balanced scorecard]]

 

* [[Big Data]]

* [[Big Data]]

 

* [[Business analysis]]

* [[Business analysis]]

 

* [[Business intelligence]]

* [[Business intelligence]]

 

* [[Climate change art]]

* [[Climate change art]]

 

* [[Data analysis]]

* [[Data analysis]]

 

* [[Data art]]

* [[Data art]]

 

* [[Data profiling]]

* [[Data profiling]]

 

* [[Data science]]

* [[Data science]]

 

* [[Data warehouse]]

* [[Data warehouse]]

 

* [[Exploratory data analysis]]

* [[Exploratory data analysis]]

 

* [[Infographic]]

* [[Infographic]]

 

* [[Information architecture]]

* [[Information architecture]]

 

* [[Information design]]

* [[Information design]]

 

* [[Information visualization]]

* [[Information visualization]]

 

* [[Interaction design]]

* [[Interaction design]]

 

* [[Interaction techniques]]

* [[Interaction techniques]]

 

* [[Scientific visualization]]

* [[Scientific visualization]]

 

* [[Software visualization]]

* [[Software visualization]]

 

* [[Statistical analysis]]

* [[Statistical analysis]]

 

* [[Statistical graphics]]

* [[Statistical graphics]]

 

* [[Visual analytics]]

* [[Visual analytics]]

 

* [[Visual journalism]]

* [[Visual journalism]]

 

* [[Warming stripes]]

* [[Warming stripes]]

 

{{Div col end}}

{{Div col end}}