visual data
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visual data
learning, conceptualizing + communicating data with infographics, visualizations, etc...
Curated by Lauren Moss
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If The Planet Really Did Revolve Around Your City: Isidro Blasco's 3D Urban Panoramas

If The Planet Really Did Revolve Around Your City: Isidro Blasco's 3D Urban Panoramas | visual data |
When you’re in a big city humming with activity, it’s not unusual to feel like the world revolves around you. On each trip to a new place, artist Isidro Blasco climbs up to the tallest buildings and documents what exactly “the world” looks like through the city’s eyes.

The result: the “Planet” series, which takes us to the bubbles of places like New York, São Paulo, Sydney, and Madrid.

The artist assembles photographs into meticulously circular panoramas. Reminding us that Photoshop techniques have origins in the physical world, each series is painstakingly incised and trimmed by hand. The three-dimensional works challenge perceptions of our everyday "orbits" through their creative use of representation.

More at the link.

jewell Moss's curator insight, March 2, 2014 1:31 PM

What do you see through your city?

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Iconostory: Minimalist Designs Represent History

Iconostory: Minimalist Designs Represent History | visual data |

From the big bang all the way to Usain Bolt’s 9.58 second hundred- meter dash record in 2009, French graphic designer René Mambembé takes us on a minimalist journey through history. 

With clean, simple designs to represent each major event, looking through his work is almost like taking a history quiz to see how many key moments you can identify. After the dinosaurs and the Ice Age, Mambembé starts with Cubism in the 1900′s and goes decade by decade highlighting the most memorable occasions, ending with some likely predictions for the 2010′s. Brush up on your history by trying to label each minimalist design as you scroll through!

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Vintage Data Visualization: 35 examples from before the Digital Era

Vintage Data Visualization: 35 examples from before the Digital Era | visual data |

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...

Mariana Soffer's comment, July 20, 2013 9:39 AM
my pleasure
Charlley Luz's curator insight, July 20, 2013 10:26 AM

muito legal, os Infográficos antes de existir a internet. 35 exemplos de infográficos no papel :) Achei falta do Marcha para Moscou do Minard ;

Leoncio Lopez-Ocon's curator insight, July 20, 2013 2:57 PM

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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What not to do when designing infographics for the web

What not to do when designing infographics for the web | visual data |
With the rampant usage of the internet these days, most people get information using it for it is the easiest way to acquire one.

Infographics, visual representations of information, data or knowledge are an important tool in teaching, in business, in giving inspiration and in presenting information. It is one of the most strongest ways to communicate with complex data.

However, the effectiveness of an infographics greatly relies on how it is designed. Hence, to aid designers, here is a list of what not to do to create a successful infographic or visualization...

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A Line Walks Into a Bar

A Line Walks Into a Bar | visual data |
We all know visualizations can be a great way to represent data, but some visualizations are better than others at certain data.

Sometimes, a bar chart is better than a line chart. This is because visualizations don’t just represent data, they also represent qualities of data.


One of these qualities is the degree of continuity. There are three main levels of continuity that data can have.

-Continuous: These are values like Temperature or Time. They can be subdivided into infinitely small increments.
-Discrete: These are values like Number of Elephants. They have a set amount of accuracy, often nothing smaller than 1. Usually each member of these values is numbered, not named.
-Categorical: These are values like States or Fruits. These are also discrete, but the values are different enough from each other to each have a name.

Now that we know we have these levels, and we know what they are, how do we visualize them best?

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Vizualize.Me - Visualize your resume in one click

Vizualize.Me is launching soon- make sure to sign up and get in line for an invite! has built a Web app that ingests a user’s work history and then spits out a design-y timeline, with details about each experience layered in.
Data like this is often messy, so, rather than trying to get users to manually enter their work history, just connects to LinkedIn, pulls out the already-structured data, and converts it into the visualization.

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The Science Behind Data Visualisation

The Science Behind Data Visualisation | visual data |

'Over the last couple of centuries, data visualisation has developed to the point where it is in everyday use across all walks of life. Many recognise it as an effective tool for both storytelling and analysis, overcoming most language and educational barriers. But why is this? How are abstract shapes and colours often able to communicate large amounts of data more effectively than a table of numbers or paragraphs of text?

An understanding of human perception will not only answer this question, but will also provide clear guidance and tools for improving the design of your own visualisations.

In order to understand how we are able to interpret data visualisations so effectively, we must start by examining the basics of how we perceive and process information, in particular visual information.'

Ignasi Alcalde's curator insight, October 11, 2013 5:02 AM

De la memoria icónica a la memoria visual.

Paul P Roberts's curator insight, October 11, 2013 12:55 PM

Interesting article, how our brain see data, possible implication for how mobile research apps are designed

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Here's What The Internet Looks Like: Visualizing the Web

Here's What The Internet Looks Like: Visualizing the Web | visual data |

These data visualizations, caricatures, and images capture the internet in all it's wiry glory.

Though we use it every day in countless ways, the Internet remains mostly faceless to us. Like a faint memory, we feel we know it intimately but have no sense of its size, its scale, or its design.

To give form to what we too prevalently consider a formless entity, we've rounded up some impressive attempts at capturing its likeness--from data visualization to caricature--to better answer the question: What is the Internet, anyway?

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Visualizing Connections In Data & Analyzing Information

Visualizing Connections In Data & Analyzing Information | visual data |

For many data visualization projects, information comes from a source that has already done some aggregation. This is both a blessing and a curse. Aggregation definitely simplifies the analysis and visualization process, but it can also greatly reduce the visualization and analysis options. This is because aggregation often destroys connections in data. For this reason, it's critical to have an in-depth and thorough knowledge and understanding of the information from aggregated information. There are several different visualization techniques that open up once we have the original data, such as Euler diagrams and parallel sets.

The extra information that can be obtained from visualizations is important to gaining a full understanding of the data, and it can lead to a much more interesting story, as well as far better visualizations and more accurate connections and links within those visualizations.

So, when gathering data about something, remember to dig deeper into it, as there are many important connections that happen within data that can provide knowledge beyond just a simple average or total.

To learn more about the value of these connections, sourcing accurate data, and how it is transformed into useful graphics, read the complete article and check out the case study used to convey the main points outlined above...

kurakura's comment, November 15, 2012 5:17 AM
the last graph on that page is really useful for understanding the data?
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11 of the Most Influential Infographics of the 19th-Century...

11 of the Most Influential Infographics of the 19th-Century... | visual data |
We live in a world steeped in graphic information. From Google Maps and GIS to the proliferation of infographics and animated maps, visual data surrounds us.

While we may think of infographics as a relatively recent development to make sense of the immense amount of data available on the Web, they actually are rooted in the 19th century.

Two major developments led to a breakthrough in infographics: advances in lithography and chromolithography, which made it possible to experiment with different types of visual representations, and the availability of vast amounts of data, including from the American Census as well as natural scientists, who faced heaps of information about the natural world, such as daily readings of wind, rainfall, and temperature spanning decades.

But such data was really only useful to the extent that it could be rendered in visual form. And this is why innovation in cartography and graphic visualization mattered so greatly...

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Visualizing Databases | Digital Humanities Specialist

Visualizing Databases | Digital Humanities Specialist | visual data |

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.

luiy's curator insight, March 25, 2013 9:11 AM

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.