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training-tutorials-and-templates.html
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<title>Training, Tutorials and Templates</title>
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<meta name="description" content="OxShef promotes and supports the use of interactive data visualisations for communicating research datasets and outputs. This is a collaboration between University of Oxford and University of Sheffield, with dedicated support for hosting visualisations for researchers at these universities on a number of different services." />
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<a class="menuItem" href="index.html">OxShef: dataviz</a>
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<a class="menuItem" href="training-resources.html">Training, Templates and Tutorials</a>
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<h1 class="title toc-ignore">Training, Tutorials and Templates</h1>
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<p><link href="https://use.fontawesome.com/releases/v5.0.6/css/all.css" rel="stylesheet"></p>
<p><strong>OxShef: Charts</strong> provides general advice on choosing the most appropriate visualisation for your data and to avoid making common mistakes or pitfalls in data viz. However, we do not provide interactive tools for matching your data to charts (or vice versa).</p>
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<div class="col-sm-7">
<p>There are many tools (Excel, Google Sheets, Plotly, Tableau) which automatically suggest charts based on the properties of your dataset. This is possible thanks to excellent research into visual perception theory and machine vision from back in the <a href="http://doi.org/10.2307/2288400">1980s</a> through to today.</p>
<p>In fact, some tools like <a href="https://doi.org/10.1145/2047196.2047247">ReVision</a> are even capable of taking existing charts and re-designing them to be more accessible and easy to read by humans. The example here shows a number of badly designed pie charts that have been converted into much easier to understand barcharts.</p>
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<p><img src='images/revision-pie.png'></img></p>
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<p><strong>OxShef: Charts</strong> maintains a collection of tools and resources to assist you in developing and designing effective visualisations, split into the following three categories:</p>
<!-- There are many excellent tools which can help -->
<!-- **OxShef: Charts** is designed to help you select the most appropriate visualisations for your data, primarily by using the [Financial Times' Visual Vocabulary](http://ft-interactive.github.io/visual-vocabulary/) and roughly dividing dataviz into the following categories; Charts, Geoviz (Maps), Networks and Time Series. Unfortunately, this is not sufficient advice for us to guarantee you select the best (and effectively designed) dataviz. There are a number of third-party resources and tutorials that we split into the following three categories: -->
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<h5>
Choosing a dataviz
</h5>
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<p>Some charts are more suitable for specific purposes than others. In some cases these resources can automate the chart selection process, or at least help exclude some chart options.</p>
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<h5>
Designing good dataviz
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<p>There are many best practices for dataviz which radically improve the legibility of a chart, for instance: horizontal barcharts with bars arranged from longest to shortest are significantly easier to interpet than unordered vertical barcharts.</p>
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<h5>
Adding interactivity
</h5>
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<p>Sadly, there’s little general advice for effectively adding interactivity to charts. However, two extremely useful rules of thumb are <a href="https://twitter.com/brianboyer/status/784874560009150464">“Make the least interactive thing that works”</a> (<a href="https://twitter.com/brianboyer">@BrianBoyer</a>) and Ben Shneiderman’s mantra <a href="https://doi.org/10.1109/VL.1996.545307">Overview first, zoom and filter, then details-on-demand</a>.</p>
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<script type="application/json" data-for="htmlwidget-d09e4eb1a2a26d291a5c">{"x":{"filter":"none","data":[["<a href='https://doi.org/10.1109/VL.1996.545307' target='_blank'><h5>Ben Shneiderman's mantra<\/h5><\/a>","<a href='http://chartmaker.visualisingdata.com/' target='_blank'><h5>Chart Maker (Visualising Data)<\/h5><img src='images/table-of-viz-tutorials-etc/chartmaker-logo.jpg' style='max-height:150px'><\/img><\/a>","<a href='https://eagereyes.org' target='_blank'><h5>Eager Eyes<\/h5><img src='images/table-of-viz-tutorials-etc/eager-eyes-logo.png' style='max-height:150px'><\/img><\/a>","<a href='https://github.com/ft-interactive/chart-doctor/blob/master/visual-vocabulary/Visual-vocabulary.pdf' target='_blank'><h5>Financial Times Visual Vocabulary<\/h5><img src='images/table-of-viz-tutorials-etc/ft-vocabulary-logo.png' style='max-height:150px'><\/img><\/a>","<a href='https://github.com/archietse/malofiej-2016/blob/master/tse-malofiej-2016-slides.pdf' target='_blank'><h5>Why We Are Doing Fewer Interactives <br> Archie Tse<\/h5><\/a>"],["<a href='https://doi.org/10.1109/VL.1996.545307' target='_blank'>Ben Shneiderman's mantra<\/a> is one of the few general purpose pieces of advice for adding interactivity to dataviz:\r\n<br>\r\n<blockquote>Overview first, zoom and filter, then details-on-demand<\/blockquote>","Andy Kirk designed and maintains the Chart Maker as a tool for selecting data visualisation tools based on specific charts. Andy has put a lot of effort into designing minimal explanations of each chart, this is a great reference tool when selecting both charts and dataviz tools.","Eager Eyes provides long-form articles and investigations into a wide variety of data visualisation topics and best practices. This website is not only useful for designing good dataviz, but also in choosing which chart to use in the first place.","The Financial Times has invested significantly in their data visualisation toolkit, part of which is a \"visual vocabulary\" that they use to help automatically choose the most appropriate dataviz for each dataset. In the future the FT are planning on open sourcing their tools based on this visual vocabularly, for the time being this remains a useful cheat sheet.","Archie Tse from the New York Times spoke at the 26th Infographics World Summit in 2016 about how their team has reduced the number of interactives they've developed in response to user testing. Archie's overall advice can be summed up as \"if anything other than scrolling is required, make something spectacular happen\"."],["Research paper","Interactive tool for comparing different charts","Robert Kosara’s website and blog dedicated to long-form articles on data viz.","Poster presenting the Financial Times' taxonomy of dataviz types.","Conference presentation"],["<i class='fa fa-magic fa-2x'><\/i>","<i class='fa fa-search fa-2x'><\/i>","<i class='fa fa-eye fa-2x'><\/i>","<i class='fa fa-search fa-2x'><\/i>","<i class='fa fa-magic fa-2x'><\/i>"]],"container":"<table class=\"display\">\n <thead>\n <tr>\n <th>Resources<\/th>\n <th>Description<\/th>\n <th>Resource description<\/th>\n <th>Type of Advice<\/th>\n <\/tr>\n <\/thead>\n<\/table>","options":{"scrollX":true,"autoWidth":true,"columnDefs":[{"width":"150px","targets":0},{"width":"550px","targets":1},{"width":"100px","targets":3},{"className":"dt-center","targets":[0,3]}],"dom":"t","order":[],"orderClasses":false}},"evals":[],"jsHooks":[]}</script>
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