Bitcoin is a decentralized digital currency based on an open-source,peer-to-peer Internet protocol. It was introduced in 2009 by a pseudonymous developer, Satoshi Nakamoto. It has risen to widespread media attention very quickly recently, leaving everyone to wonder what it is — and how it works. These visualizations attempt to further explain the Bitcoin phenomenon in a visual way.

This short video explains the ins and outs of how Bitcoin works and how Bitcoins are mined.

A Visualization of the exchange rate, network power consumption, estimated money sent and coins in circulation for Bitcoin

Realtime Bitcoin infographic

This infographic explains, very concisely, how the Bitcoin ecosystem operates

Bitcoin infographic infographic

Data Visualization Summit SF infographic

The theme of the conference is “Data in, Decisions out,” and the presentations so far have shown several case studies of companies doing just that. Here are three of the highlights from the talks that took place on Thursday, April 11.

Drew Linzer from Emory University gave a fantastic talk on his 2012 presidential election predictions. He covered how he built his prediction model and kept it more stable so predictions were consistent even when new polls were added. He also discussed the challenges of building aesthetically pleasing charts with no formal training.

Andy Kriebel from Facebook covered his path from visualization novice through to Tableau Zen Master and visualization guru at Facebook. He showed how his path at every level was defined by finding important information in data, and using that information to drive decisions. He also discussed running a his blog VizWiz, where he critiques visualizations, and presents new work that he has done.

Krist Wongsuphasawat from Twitter went over his research into visualizing events. His system, LifeFlow, is a great tool for visualizing aggregated event sequences for huge quantities of event series.

There were several other great talks, and the talks on Friday should be very informative as well. The full list of presenters can be found here. You can check out Visually’s presentation from yesterday here. For live coverage, follow conference updates on twitter with #DVSF.

 
Drew Skau is Visualization Architect at Visual.ly and a PhD Computer Science Visualization student at UNCC with an undergraduate degree in Architecture. You can follow him on twitter @SeeingStructure

But here, wait staff at restaurants (along with those working in the kitchen, etc.) earn minimum wages – if not less than that – and it is generally accepted that they must rely on tips to make a living.

To gauge America’s opinions on tipping at restaurants, Visually partnered with SurveyMonkey Audience to gather feedback from over 500 U.S. adults. See what they told us in the infographic below. (General information on respondents is available here).

Restaurants Run on Tips infographic by anibalinfographics.

But for those who’ve come to love running – whether they just started going ’round the block last month or have been competing in their age groups for years – the marathon distance is the ultimate goal; a bucket list type of thing.

A marathon is long enough to challenge you physically and mentally and to test your endurance, spirit and heart, not to mention your love of and commitment to the sport. Do not fool yourself, in training you will cover many, many hundreds of miles. And so it is: when it comes to long distance running, the marathon has all the glory.

But in recent years, it isn’t the marathon that’s exploding in popularity among runners — it’s the distance that was once, perhaps deprecatingly, named “half” of a marathon.

There is nothing “half” in a half marathon, mind you. To run 13.1 miles is no small feat. But because it is, after all, twice shorter than a marathon and the training is arguably easier and less time consuming, the number of people finishing a half marathon distance has been growing much faster in recent years than those running and finishing the full.

Non-profit organization Running USA and Athlinks, an online database for race results, released its latest annual Half Marathon report earlier this week and, together with the same type of data for the marathon (out just a few weeks prior), we created the infographic below to visualize some of the most interesting data.

Battle of the Long Distance Races infographic by anibalinfographics.

Aleks Todorova is the Editorial Director at Visual.ly. She recently ran her third marathon and will run her 21st half marathon this Sunday. Follow her on Twitter.

InfoVis deals with smaller datasets, typically demographic or financial data.

Visual analytics involves a cycle of rapidly creating visualizations to answer and generate new questions about a dataset.

Infographics are typically in the realm of InfoVis, and often they show the results of the visual analytics process, but SciVis is not really a part of most infographics.

SciVis is interesting because it deals with really large quantities of data that often has a spatial and/or temporal component. These are cool qualities to have in a dataset because they sometimes allow for the appropriate use of 3D visualization techniques. With the huge quantities of data involved, this often leads to extremely beautiful results that often look as if they are photographs or pieces of art.

In many cases, they actually are photographs that are taken using advanced devices to show us either a scale we could not see, the inside of an object, or something so far away that to the naked eye it looks as if it is only a single point of light.

Sometimes, scientific visualization also uses rainbow color scales, or inappropriately uses 3D techniques. This still produces beautiful images, but the usefulness of these images can be harmed by these techniques.

The people who do this kind of work are extremely intelligent, so you might ask, why are they doing something wrong? The nature of SciVis requires people who are experts at some extremely niche subjects, and they spend the majority of their time learning about and working on these problems, unaware that there are better techniques for showing their data.

Overall, these problems are minor in comparison to the issues that have been and are being solved with help from SciVis. People who work on these problems have developed the software that shows CAT scans and MRIs. They work on systems to show and predict weather patterns, both here on Earth, and on other planets. They build tools for seeing the molecular structure of substances we want to study or create. They show us what it looks like when tiny sub-atomic particles slam into matter, breaking it into other sub-atomic particles. They enable us to see inside the human body to heal people and keep them healthy.

So, a big Thank You to all the scientists out there dealing with truly “Big Data,” and here’s to hoping your results are as functional as they are beautiful.

All of the images and videos in this post are winners of the 2012 International Science & Engineering Visualization Challenge.

 
Drew Skau is Visualization Architect at Visual.ly and a PhD Computer Science Visualization student at UNCC with an undergraduate degree in Architecture. You can follow him on twitter @SeeingStructure

Super Bowl commercials try to make us laugh, move us emotionally, or move us, well, not-so emotionally. They advertise everything, from soda to beer, to cars, to laundry detergent. But how often do they feature a woman wearing more than a bikini or a minority as the primary character?

This Super Bowl Sunday, we took on the tremendously important task of watching every single commercial aired during the game — except for movie ads and local spots — and taking studious notes about who they feature, what they’re selling and how they try to sell it. Below are the results, visualized.

Super bowl Commercial breakdown infographic by anibalinfographics.

Learning New Skills

One theme that was persistent through the whole conference was education. With the advent of so much new technology, journalists are having to learn how to program in order to keep up. Programming at the level of an expert developer may not be necessary, though. It is far more realistic to learn how to think computationally, and know enough to communicate well with a developer. Understanding the process on the conceptual level goes a long way toward being able to collaborate effectively.

Mastering Social Networks

As expected, social networks, especially Twitter, were a focus of many discussions. These platforms have revolutionized reporting from every possible angle, becoming publication platforms, data sources, contact methods, and distribution methods. Journalists are really figuring out how to use Twitter and other social networks as a part of their work. Access to APIs and computational skills turn these networks into rich data sources, and journalists are employing increasingly detailed analysis to scrape insight from the mass of posts.

Telling Stories With Data

Another theme that was present in the symposium was storytelling. Traditional journalism does this all the time, and journalists have become very good at storytelling with visualization. It is clear that for presenting data, telling a story alongside or with the data is crucial. Storytelling helps the viewer gain an understanding and get insight from the data. This means that the analysis process has to be thorough and find the story that the data supports.

It’s clear that the field of journalism is rapidly evolving. Computers and the internet have dramatically changed the landscape, and mobile devices have mixed things up even further. Data visualization is certain to remain key in journalism’s future, and many journalists are rapidly building out skillsets to support it and other computational tools.

Videos of the sessions can be found here once they go live, and notes from the event can be found here.

 
Drew Skau is Visualization Architect at Visual.ly and a PhD Computer Science Visualization student at UNCC with an undergraduate degree in Architecture. You can follow him on twitter @SeeingStructure