Born in 1888, German scientist, doctor, and author Fritz Kahn was the grandfather of modern data visualization.
We’re in the golden age of infographicw, where charts, graphs, and maps transform dense and dry facts into eye candy, and the Internet can’t get enough. But where did this data-viz craze begin?
Born in 1888, German scientist, doctor, and author Fritz Kahn was the grandfather of modern data visualization. A new 390-page monograph of Kahn’s work, published by Taschen, takes readers into an illustrated world that features winged fish, insect-size parachutists, and blood cells used as boats. Surreal as these scenes seem, they're actually meant to visualize scientific facts...
During the past few years the demand regarding Data Info-graphics has increased in volume and demand as well as in clarity. The range of technologies available by which to collect and examine data is constantly on the rise- both in web and desktop applications, which provide several great interfaces. From a technological aspect , such tools have created efficiency based models which have gone onto disrupting existing paradigms of the past. These vary and range from data synthesis to data visualization encompassing every type of data.
Within this scope, such new tools are continually emerging whose main purpose is to- simplify the process within being able to harness data in lending impact and insight generation...
As data visualization expands its reach – through the rise of Massive Online Courses, the countless events and, most significantly, the interconnection between different disciplines and knowledge fields that produce inspiring works and innovative projects -, it’s only natural that the number of folks writing about it keeps rising.
There are literally hundreds of interesting blogs out there, covering all the aspects surrounding the production of quality, effective data visualizations.
Visit the link to find a collection of resources and interesting projects that give a pretty good idea of how vast and rich the data visualization community is...
Social Network Analysis, as an analytic method, has inarguable applicability to the field of intelligence and is progressively reshaping the analytic landscape in terms of how analysts understand networks. For example, analysts currently use SNA to identify key people in an organization or social network, develop a strategic agent network, identify new agents and simulate information flows through a network.The most obvious use of SNA is its ability to identify key actors and entities within a network. Centrality measures within a network are means for measuring a node’s relative importance within the network.  It is well-accepted that “the ability to measure centrality in social networks has been a particularly useful development in social network analysis.” What is more interesting, however, is the number of centrality measures that social network analysts use to reveal different things about how key actors interact within a network.
We have more data available to us than ever before and in an increasingly visual world, audiences look to images to make sense of things. We must refine how we present information visually in order to better inform audiences and ourselves.
There are many tools available to make data visualizations, but the tools and the visualizations alone are not enough. We need to enlighten users by guiding them through the complexity, using stories and design. In this exploding landscape of many visual data forms, multimedia and interactivity, we need to create content not only for our “super users,” but also actively help our larger audience understand them...
This seems like a straightforward question, but it’s proven to be a difficult one to answer. Even visualization researchers don’t have a clear definition.
Is it synonymous with information graphics? Does visualization have to be computer generated? Does data have to be involved, or can it be abstract? The answers vary depending on who you ask.
Visualization is a medium. It’s not just an analysis tool nor just a way to prove a point more clearly through data.
Visualization is like books. There are different writing styles and categories, there are textbooks and there are novels, and they communicate ideas in different ways for varied purposes. And just like authors who use words to communicate, there are rules that you should always follow and others that are guidelines that you can bend and break...
"One of the best techniques to catch and record ideas is through using visual graphs. Data that is visually encoded is more likely to be processed by the mind in a faster and easier way. This is probably the reason why students love it when comics and graphic are included in instruction. In this regard, Educational Technology and Mobile Learning has curated a list of some powerful iPad apps that you and your students can use to visually grab ideas and create sketchy mindmaps. I invite you to check the collection below and share with us what you think of them."
The negative impact that cognitive biases can have on the quality of strategic decision making is increasingly recognized by academics and business practitioners globally. These biases manifest themselves across all industries but are exacerbated within the resources industry (e.g. mining, oil and gas etc.) as a result of three specific characteristics: Relatively slow structural supply demand cycles (clock-speed); Requirement for large capital investments to add new capacity;Typically long payback periods for investments. The authors’ identify seven cognitive biases with greatest impact on the resources industry along with three core principles for mitigating these biases when formulating strategy
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