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antropologo.net, dataviz, collective intelligence, algorithms, social learning, social change, digital humanities
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Vintage Data Visualization: 35 examples from before the Digital Era | #dataviz #history

Vintage Data Visualization: 35 examples from before the Digital Era | #dataviz #history | e-Xploration | Scoop.it

Graphics, charts, diagrams and visual data representations have been published on books, newspapers and magazines since they've existed, not to mention old maps and scientific illustrations...

 

Despite the lack of tools such as the ones we have at our disposal nowadays, they are as inspiring and important as the best contemporary visualizations. Visit the article link for a gallery of vintage visualizations...


Via Lauren Moss, Jim Lerman
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Mariana Soffer's comment, July 20, 2013 6:39 AM
my pleasure
Charlley Luz's curator insight, July 20, 2013 7:26 AM

muito legal, os Infográficos antes de existir a internet. 35 exemplos de infográficos no papel :) Achei falta do Marcha para Moscou do Minard http://www.datavis.ca/gallery/re-minard.php ;

Leoncio Lopez-Ocon's curator insight, July 20, 2013 11:57 AM

El brasileño Tiago Veloso, fundador de Visual Loop, nos ofrece 35 interesantísimas representaciones visuales de distintos fenómenos y eventos que permiten hacer un paseo por la historia de la ilustración científica.

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Visualizing Databases | Digital Humanities Specialist

Visualizing Databases | Digital Humanities Specialist | e-Xploration | Scoop.it

Summaries and statistics drawn from within the structure of the database are not enough. If there is to be any real grappling with the database as an culturally-embedded construct, then it has to be done in a manner that reveals the data, the model and the population simultaneously.


Via Lauren Moss
luiy's insight:

I’ve become quite the fan of Gephi, lately, and received a good-natured challenge by one of my colleagues, which went something like, “Why is a everything a network with you, now?”  Obviously, in the case of social network-like phenomena, such as mapping collaboration in the Digital Humanities with the DH@Stanford graph–network theory and network language (whether visual or theoretical) make sense.  Network analytical tools like Gephi are also only a short step away from spatial analytical tools, like ArcGIS, many of which are used to ask questions about geographic networks and not about the kind of continuous data found in topography.

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