Data visualization: A view of every Points of View column

Data visualization: A view of every Points of View column

We’ve organized all the Points of View columns on data visualization published in Nature Methods and provide this as a guide to accessing this trove of practical advice on visualizing scientific data.

As of July 30, 2013 Nature Methods has published 35 Points of View columns written by Bang Wong, Martin Krzywinski and their co-authors: Nils Gehlenborg, Cydney Nielsen, Noam Shoresh, Rikke Schmidt Kjærgaard, Erica Savig and Alberto Cairo. As we prepare to launch a new column in our September issue we felt this would be a good time to collect and organize links to all the Points of View articles together in one place to make it easier to navigate this wonderful resource that the authors have provided us. For the month of August we will be making all the columns free to access so everyone can benefit from this practical advice on data visualization.

This should not be the end of the Points of View column though. We will be inviting new visualization experts to author articles on new topics that have not been covered so far or which can be expanded on. This page will be continuously updated whenever a new article is published so stay tuned. If you have a suggestion for a topic you would like to see covered in a future points of view article please comment below.

Update of March 28, 2015: A PDF eBook of the 38 Points of View articles published between August 2010 and February 2015 is now available at the Nature Shop for $7.99 under the title “Visual strategies for biological data: the collected Points of View”. The article summaries below provide a nice overview of what is contained in that eBook collection.

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 Pathways – January 2016 Apply visual grouping principles to add clarity to information flow in pathway diagrams Neural circuit diagrams – March 2016 Use alignment and consistency to untangle complex neural circuit diagrams

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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