文件名称:
A Practical Guide to Designing with Data.pdf
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上传时间: 2019-08-21
详细说明： Over the years, I have been digging through large data sets both for work and pleasure. I love numbers, charts, graphs, visualizations, zeitgeists, raumzeitgeists, infographics and old maps. Getting to peek into what companies like Google get to see on a daily basis – trends, fads, search volume, relatedness, all bundled up in a n interesting illustration – makes my day. Some people re-read the same book over and over; I can stare at a dense illustration and re-read its story. It makes me ask, “What caused these numbers? Where did they all come from?” It has been estimated that the Large Hadron Collider produces fifteen petabytes (fifteen million gigabytes) of data a year. Itʼs impossible to look at a table of fifteen petabytes of information – there has to be a graphical representation for anyone to comprehend data at this volume. This is what excites me: the challenge of how to take these boring numbers and design something more compelling. To tell the story behind the data, we need to stop grasping for the perfect visualization and instead return to the basic language of charts and graphs. Only then can we begin to uncover the meaning and relationships the data has to offer. Beyond the basic bar charts and line graphs taught in schools, a new breed of illustrations has recently appeared. These new ʻvisualizationsʼ are an attempt to explain the underlying information with a powerful visual impact. They take complex ideas and distil them into beautiful graphics revealing the interrelationships in the data. Some are so brilliantly executed that there are now annual awards for newspaper and magazine infographics to highlight their achievements. Sadly, over recent years terms such as visualization and infographic have been bandied around with almost no regard to their proper use or meaning. Existing chart types and even slide shows have been saddled with the more gratuitous term ʻinfographsʼ to sound more impressive. There is a new vernacular in the realm of data representation, but that doesnʼt mean we should ignore the underlying principles and best practices of humble charts and graphs. Once you have mastered the basics, more complex designs and visualizations become easier to create.
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