Data Visualization for Success - Braun, Steven
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-Top designers discuss their approaches to data visualisation, offering insight into their commonly used design methods and tips for beginning practitioners in the field >What is data visualization? In Data Visualization for Success, 40 designers and their works demonstrate that data visualization is a vibrant and constantly evolving field that is as multimodal as it is interdisciplinary. Through the works showcased here, these designers discuss some of their approaches to working with data visualisation, offering insight into the design methods they commonly use and providing tips that will…mehr

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Produktbeschreibung
-Top designers discuss their approaches to data visualisation, offering insight into their commonly used design methods and tips for beginning practitioners in the field >What is data visualization? In Data Visualization for Success, 40 designers and their works demonstrate that data visualization is a vibrant and constantly evolving field that is as multimodal as it is interdisciplinary. Through the works showcased here, these designers discuss some of their approaches to working with data visualisation, offering insight into the design methods they commonly use and providing tips that will help beginning practitioners in the field. This book shows that data visualization is a practice and discipline whose fluid boundaries continue to be moved in new, exciting, and unprecedented directions by emerging and seasoned designers alike.
Autorenporträt
Steven Braun holds a BA in Chemistry and Asian Studies from St Olaf College in Northfield, Minnesota, USA, and earned his MS in molecular biophysics and biochemistry at Yale University. He has been the data analytics and visualisation specialist with the Digital Scholarship Group in the Northeastern University Libraries (Boston, Massachusetts, USA) since November 2015. His experiences living and studying in Japan have deeply informed his general philosophy about data visualisation: visualisation is constructed space, where data are manifold and our choices in design directly inform how those data are interpreted and used.