visual data
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visual data
learning, conceptualizing + communicating data with infographics, visualizations, etc...
Curated by Lauren Moss
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Six Design Lessons from the Bauhaus: Masters of the Persuasive Graphic

Six Design Lessons from the Bauhaus: Masters of the Persuasive Graphic | visual data |

The Bauhaus school of art and architecture in early 20th century Germany was the birthplace of a revolution in modern design. Founder Walter Gropius’ form-follows-function philosophy transformed advertising, typography, architecture, people’s living spaces, and the public’s aesthetic expectations in fundamental ways.

The Bauhaus mission — to provide affordable, artistic, utilitarian design for every class of person — was a smashing success. Today, their crisp, geometric style is reflected in successful design everywhere: from billboards to infographics. And it still serves its original purpose: to honor functionality with beauty, to please the eye and capture the mind.

So what can today’s graphic designers learn from the Bauhaus? Let’s go to school!

Lauren Moss's insight:

Graphic design concepts from the Bauhaus that inform visual communication practices: form reflects function, the valuable roles of color and typography, why design should be accessible, and the importance of collaboration...

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Graphing the history of philosophy

Graphing the history of philosophy | visual data |

Each philosopher is a node in the network and the lines between them (or edges in the terminology of graph theory) represents lines of influence. The node and text are sized according to the number of connections. The algorithm that visualises the graph also tends to put the better connected nodes in the centre of the diagram so we the most influential philosophers, in large text, clustered in the centre. It all seems about right with the major figures in the western philosophical tradition taking the centre stage. (I need to also add the direction of influence with a arrow head – something I’ve not got round to yet.)

A shortcoming however is that this evaluation only takes into account direct lines of influence. Indirect influence via another person in the network does not enter into it. This probably explains why Descartes is smaller than you’d think.

It gets more interesting when we use Gephi to identify communities (or modules) within the network. Roughly speaking it identifies groups of nodes which are more connected with each other than with nodes in other groups. Philosophy has many traditions and schools so a good test would be whether the algorithm picks them out...

Via Martin Daumiller
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