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Nature Methods: 做图方法科普系列 (Points of View)

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licheng 发表于 2015-12-27 11:45:17 | 显示全部楼层 |阅读模式
下面是Nature Methods上的Points of View系列文章,介绍画出好图的各方面经验。
http://blogs.nature.com/methagora/2013/07/data-visualization-points-of-view.html

转自上面的网页(需要Nature Methods订阅):

Introduction
Visualizing biological data – December 2012
Data visualization is increasingly important, but it requires clear objectives and improved implementation
The overview figure – May 2011
An economic overview figure to convey general concepts helps readers understand a research study
. . . . . . . .
Composition and layout
The design process – December 2011
Use good design to balance self-expression with the need to satisfy an audience in a logical manner
Layout – October 2011
Proper layout reveals the hierarchical relationship of informational elements
Gestalt principles (Part 1) – November 2010
Gestalt principles (Part 2) – December 2010
Exploit perceptual phenomena to meaningfully arrange elements on the page
Negative space – January 2011
Whitespace is a powerful way of improving visual appeal and emphasizing content
Salience to relevance – November 2011
Ensure that viewers notice the right content by making relevant information most noticeable
Elements of visual style – May 2013
Translate the principles of effective writing to the process of figure design
Storytelling – August 2013
Relate your data to the world around them using the age-old custom of telling a story
. . . . . . . .
Using color
Color coding – August 2010
Choose colors appropriately to avoid bias and unwanted artifacts in visuals
Color blindness – June 2011
Make your graphics accessible to those with color vision deficiencies
Avoiding color – July 2011
Improve the overall clarity and utility of data displays by using alternatives to color
Mapping quantitative data to color – August 2012
Color is useful for compact visualizations of large data sets but must highlight salient features
Heat maps – March 2012
Color, clustering and parallel coordinate plots are essential for using heatmaps effectively
. . . . . . . .
Elements of a figure
Typography – April 2011
Choose typefaces, sizes and spacing to clarify the structure and meaning of the text
Axes, ticks and grids – March 2013
Make navigational elements distinct and unobtrusive to maintain visual priority of data
Labels and callouts – April 2013
Figure labels require the same consistency and alignment in their layout as text
Plotting symbols – June 2013
Choose distinct symbols that overlap without ambiguity and communicate relationships in data
Arrows – September 2011
Use well-proportioned arrows sparingly and consistently as a guide through complex information
. . . . . . . .
Plot types
Bar charts and box plots – February 2014
Choose the appropriate plot according to the nature of the data and the task at hand
Sets and intersections – July 2014
Euler and Venn diagrams are appropriate for up to three sets but for greater numbers use more scalable plots
Heat maps – March 2012
Color, clustering and parallel coordinate plots are essential for using heatmaps effectively
Temporal data – Feb 2015
Use inherent properties of time to create effective visualizations
Unentangling complex plots – July 2015
Carefully designed subplots scaled to the data are often superior to a single complex overview plot
. . . . . . . .
Improving figure clarity
Simplify to clarify – August 2011
Simplify your presentation to improve clarity
Design of data figures – September 2010
Improve figure decoding by using strong visual cues to encode data
Salience – October 2010
Use salience to differentiate graphical symbols and speed up figure reading
Points of review (Part 1) – February 2011
Examples of figure redesigns
Points of review (Part 2) – March 2011
Simple tips to improve pie chart, scatter plot and color scale data displays
. . . . . . . .
Multidimensional data
Into the third dimension – September 2012
3D visualizations are effective for spatial data but rarely for other data types
Power of the plane – October 2012
Combine 2D plots for effective visualization of multivariate data
Multidimensional data – July 2013
Visually organize complex data by mapping them onto familiar representations of biological systems
. . . . . . . .
Data exploration
Pencil and paper – November 2012
Quick sketches and doodles of data or models aids thinking and the scientific process
Data exploration – January 2012
Create ‘slices’ of data to enhance the process of pattern discovery
Networks – February 2012
Choose your network visualization based on the patterns you are looking for
Heat maps – March 2012
Color, clustering and parallel coordinate plots are essential for using heatmaps effectively
Integrating data – April 2012
Combine visualizations of multiple data types to find correlations and potential relationships
Representing the genome – May 2012
Limit what is displayed based on the question being asked
Managing deep data in genome browsers – June 2012
Compaction and summarization help find patterns in overwhelming data
Representing genomic structural variation – July 2012
Use arcs, color, dot plots and node graphs to show relations between distant genomic positions

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