{"id":939,"date":"2013-07-30T08:08:15","date_gmt":"2013-07-30T12:08:15","guid":{"rendered":"https:\/\/blogs.nature.com\/methagora\/?p=939"},"modified":"2016-03-11T09:02:45","modified_gmt":"2016-03-11T14:02:45","slug":"data-visualization-points-of-view","status":"publish","type":"post","link":"https:\/\/blogs.nature.com\/methagora\/2013\/07\/data-visualization-points-of-view.html","title":{"rendered":"Data visualization: A view of every Points of View column"},"content":{"rendered":"

We’ve organized all the Points of View columns on data visualization published in Nature Methods<\/em> and provide this as a guide to accessing this trove of practical advice on visualizing scientific data.<\/strong><\/p>\n

As of July 30, 2013 Nature Methods<\/em> 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 Kj\u00e6rgaard, 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.<\/p>\n

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.<\/p>\n

Update of March 28, 2015: <\/strong>A PDF eBook of the 38 Points of View articles published between August 2010 and February 2015 is now available at the Nature Shop<\/a> 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.<\/p>\n

. . . . . . . .<\/p>\n

Introduction<\/strong>
\nVisualizing biological data<\/strong><\/a> \u2013 December 2012
\nData visualization is increasingly important, but it requires clear objectives and improved implementation
\nThe overview figure<\/strong><\/a> \u2013 May 2011
\nAn economic overview figure to convey general concepts helps readers understand a research study<\/p>\n

. . . . . . . .<\/p>\n

Composition and layout<\/strong>
\nThe design process<\/strong><\/a> \u2013 December 2011
\nUse good design to balance self-expression with the need to satisfy an audience in a logical manner
\n\"FigureLayout<\/strong><\/a> \u2013 October 2011
\nProper layout reveals the hierarchical relationship of informational elements
\nGestalt principles (Part 1)<\/strong><\/a> \u2013 November 2010
\nGestalt principles (Part 2)<\/strong><\/a> \u2013 December 2010
\nExploit perceptual phenomena to meaningfully arrange elements on the page
\nNegative space<\/strong><\/a> \u2013 January 2011
\nWhitespace is a powerful way of improving visual appeal and emphasizing content
\nSalience to relevance<\/strong><\/a> \u2013 November 2011
\nEnsure that viewers notice the right content by making relevant information most noticeable
\nElements of visual style<\/strong><\/a> \u2013 May 2013
\nTranslate the principles of effective writing to the process of figure design
\nStorytelling<\/strong><\/a> \u2013 August 2013
\nRelate your data to the world around them using the age-old custom of telling a story<\/p>\n

. . . . . . . .<\/p>\n

Using color<\/strong>\"Using
\nColor coding<\/strong><\/a> \u2013 August 2010
\nChoose colors appropriately to avoid bias and unwanted artifacts in visuals
\nColor blindness<\/strong><\/a> \u2013 June 2011
\nMake your graphics accessible to those with color vision deficiencies
\nAvoiding color<\/strong><\/a> \u2013 July 2011
\nImprove the overall clarity and utility of data displays by using alternatives to color
\nMapping quantitative data to color<\/strong><\/a> \u2013 August 2012
\nColor is useful for compact visualizations of large data sets but must highlight salient features
\nHeat maps<\/strong><\/a> \u2013 March 2012
\nColor, clustering and parallel coordinate plots are essential for using heatmaps effectively<\/p>\n

. . . . . . . .<\/p>\n

\"ElementsElements of a figure<\/strong>
\nTypography<\/strong><\/a> \u2013 April 2011
\nChoose typefaces, sizes and spacing to clarify the structure and meaning of the text
\nAxes, ticks and grids<\/strong><\/a> \u2013 March 2013
\nMake navigational elements distinct and unobtrusive to maintain visual priority of data
\nLabels and callouts<\/strong><\/a> \u2013 April 2013
\nFigure labels require the same consistency and alignment in their layout as text
\nPlotting symbols<\/strong><\/a> \u2013 June 2013
\nChoose distinct symbols that overlap without ambiguity and communicate relationships in data
\nArrows<\/strong><\/a> \u2013 September 2011
\nUse well-proportioned arrows sparingly and consistently as a guide through complex information<\/p>\n

. . . . . . . .<\/p>\n

Plot types<\/strong>
\nBar charts and box plots<\/strong><\/a> \u2013 February 2014
\nChoose the appropriate plot according to the nature of the data and the task at hand
\nSets and intersections<\/strong><\/a> \u2013 July 2014
\nEuler and Venn diagrams are appropriate for up to three sets but for greater numbers use more scalable plots
\nHeat maps<\/strong><\/a> \u2013 March 2012
\nColor, clustering and parallel coordinate plots are essential for using heatmaps effectively
\nTemporal data<\/strong><\/a> \u2013 Feb 2015
\nUse inherent properties of time to create effective visualizations
\nUnentangling complex plots<\/strong><\/a> \u2013 July 2015
\nCarefully designed subplots scaled to the data are often superior to a single complex overview plot
\nPathways<\/strong><\/a> \u2013 January 2016
\nApply visual grouping principles to add clarity to information flow in pathway diagrams
\nNeural circuit diagrams<\/strong><\/a> \u2013 March 2016
\nUse alignment and consistency to untangle complex neural circuit diagrams<\/p>\n

. . . . . . . .<\/p>\n

Improving figure clarity<\/strong>\"Improving
\nSimplify to clarify<\/strong><\/a> \u2013 August 2011
\nSimplify your presentation to improve clarity
\nDesign of data figures<\/strong><\/a> \u2013 September 2010
\nImprove figure decoding by using strong visual cues to encode data
\nSalience<\/strong><\/a> \u2013 October 2010
\nUse salience to differentiate graphical symbols and speed up figure reading
\nPoints of review (Part 1)<\/strong><\/a> \u2013 February 2011
\nExamples of figure redesigns
\nPoints of review (Part 2)<\/strong><\/a> \u2013 March 2011
\nSimple tips to improve pie chart, scatter plot and color scale data displays<\/p>\n

. . . . . . . .<\/p>\n

Multidimensional data<\/strong>
\n\"VisualizingInto the third dimension<\/strong><\/a> \u2013 September 2012
\n3D visualizations are effective for spatial data but rarely for other data types
\nPower of the plane<\/strong><\/a> \u2013 October 2012
\nCombine 2D plots for effective visualization of multivariate data
\nMultidimensional data<\/strong><\/a> \u2013 July 2013
\nVisually organize complex data by mapping them onto familiar representations of biological systems<\/p>\n

. . . . . . . .<\/p>\n

Data exploration<\/strong>
\nPencil and paper<\/strong><\/a> \u2013 November 2012
\nQuick sketches and doodles of data or models aids thinking and the scientific process\"Visualization
\nData exploration<\/strong><\/a> \u2013 January 2012
\nCreate \u2018slices\u2019 of data to enhance the process of pattern discovery
\nNetworks<\/strong><\/a> \u2013 February 2012
\nChoose your network visualization based on the patterns you are looking for
\nHeat maps<\/strong><\/a> \u2013 March 2012
\nColor, clustering and parallel coordinate plots are essential for using heatmaps effectively
\nIntegrating data<\/strong><\/a> \u2013 April 2012
\nCombine visualizations of multiple data types to find correlations and potential relationships
\nRepresenting the genome<\/strong><\/a> \u2013 May 2012
\nLimit what is displayed based on the question being asked
\nManaging deep data in genome browsers<\/strong><\/a> \u2013 June 2012
\nCompaction and summarization help find patterns in overwhelming data
\nRepresenting genomic structural variation<\/strong><\/a> \u2013 July 2012
\nUse arcs, color, dot plots and node graphs to show relations between distant genomic positions<\/p>\n

. . . . . . . .<\/p>\n","protected":false},"excerpt":{"rendered":"

We have 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.  Read more<\/a> Continue reading →<\/span><\/a><\/p>\n","protected":false},"author":257,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[101,121],"tags":[72,122,103,95],"class_list":["post-939","post","type-post","status-publish","format-standard","hentry","category-featured","category-visualization-2","tag-data","tag-data-visualization","tag-points-of-view","tag-visualization"],"_links":{"self":[{"href":"https:\/\/blogs.nature.com\/methagora\/wp-json\/wp\/v2\/posts\/939","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/blogs.nature.com\/methagora\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/blogs.nature.com\/methagora\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/blogs.nature.com\/methagora\/wp-json\/wp\/v2\/users\/257"}],"replies":[{"embeddable":true,"href":"https:\/\/blogs.nature.com\/methagora\/wp-json\/wp\/v2\/comments?post=939"}],"version-history":[{"count":0,"href":"https:\/\/blogs.nature.com\/methagora\/wp-json\/wp\/v2\/posts\/939\/revisions"}],"wp:attachment":[{"href":"https:\/\/blogs.nature.com\/methagora\/wp-json\/wp\/v2\/media?parent=939"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blogs.nature.com\/methagora\/wp-json\/wp\/v2\/categories?post=939"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blogs.nature.com\/methagora\/wp-json\/wp\/v2\/tags?post=939"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}