Unlike Ireland’s traditional owner-occupier structure, renting in Germany’s post-Communist debt contributed to a dominance of private real estate seen today.

What are the best data visualizations ever created?

Our Top 12 of The Best Data Visualizations

1) Transparency International

The first of our interactive data visualization examples will be this clean, simple interactive diagram that displays the results of Transparency International’s Corruption Survey data. Bold red makes the results pop out immediately. The visualization uses icons instead of words to communicate the different sectors included in the survey, making the presentation very visually appealing. Transparency International shows the viewer the relationships between the geographic location of the country and the type of corruption, leaving the audience to draw their own conclusions.

2) Largest Vocabulary in Hip Hop

We had a hard time rounding out our list. Instead of going for the super useful, we picked the most interesting: Matt Daniel’s Largest Vocabulary in Hip Hop. Matt explains, “Literary elites love to rep Shakespeare’s vocabulary: across his entire corpus, he uses 28,829 words, suggesting he knew over 100,000 words and arguably had the largest vocabulary, ever. I decided to compare this data point against the most famous artists in hip hop. I used each artist’s first 35,000 lyrics. That way, prolific artists, such as Jay-Z, could be compared to newer artists, such as Drake.” While the result may surprise you, it is a reminder that good data visualization does more than present information – it tells a story.

3) Selfiecity – The Science of Selfies

This project is studying the way people take self-portraits in different parts of the world – over 120,000 selfies from Berlin, New York, Bangkok, Sao Paolo or Moscow have been analyzed. Are women more likely to take selfies than men? In which proportion? Do people smile, tilt their head, crop the picture? All these questions have been answered and the results are displayed in very well-made interactive data visualization examples. The complexity of the study and the insights found made it a real challenge to expose the results, which they addressed very well, creating one of the best data visualization of the past years.

4) Pinellas County’s Public School Inequalities For Black Pupils

Another good data visualization pictures the link between increasing segregation of schools in Pinellas County in Florida and poor performance of students. The visualization displays the results of an investigation carried out by Tampa Bay Times on the basis of data gathered by Florida Department of Education and Pinellas County School District. The results are strikingly accurate and clear. They reveal five out of 150 elementary schools in Pinellas County where students’ performance is exceptionally low. The underperforming schools are located in black communities’ areas with highest levels of social segregation. These insights can move local decision-makers and social activists to take better care of the troubled institutions and introduce improvements. Users scroll, not click, to see charts change and follow the investigation step by step. The scroll action is the new users’ favorite which is particularly fit for the mobile use. On Facebook, Instagram or Twitter we scroll through streams and streams of content. Scrolling engages users for longer and makes it difficult to look away. The view transitions easily from chart to chart, making the story easy to follow, and making the data itself central to the view on the screen. The data and results collected are complex and prolific, which made this data viz a real challenge, but they managed it so well and easy to understand, that we deem it to be one of the best interactive data visualization that we came across.

5) The First Data Visualization to Solve a Deadly Threat

Cholera is a bacterial infection of the small intestine that causes its victims to suffer from such severity of the diarrhea and vomiting that they can die in two hours. It’s fatal in half of untreated cases. When the disease arrived in London, in 1832, it was thought to be spread by a “miasma” or bad smell in the atmosphere. There were four major cholera outbreaks in London over the next twenty-two years.

It was during the 4th epidemic that the Doctor John Snow began to think that the air contamination argument seemed flimsy. Londoners were getting their drinking water from the disgustingly polluted Thames, which also served as the city’s sewage line. Dr. Snow hypothesized that cholera was spread through the ingestion of polluted water. On August 31st, 1854, “what Dr. Snow later called ‘the most terrible outbreak of cholera which ever occurred in the kingdom’ broke out. It was as violent as it was sudden. During the next three days, 127 people living in or around Broad Street died.”

Dr. Snow set out to track where people died and the nearby water sources. His map not only solved the source of cholera, but is one of the first (and most well-known) data visualizations. Dr. Snow simply put a dot on a map to indicate where people died of cholera. He found that almost all deaths had taken place a short distance from the Broad Street water pump. It was discovered that, “houses much nearer another pump, there had only been 10 deaths — and of those, five victims had always drunk the water from the Broad Street pump, and three were schoolchildren who had probably drunk from the pump on their way to school.” There were several other anomalies that helped prove his theory. There was a pump nearby where only five out of 530 residents came down with cholera – it turned out they had their own well. The seventy employees at a nearby brewery made it through the epidemic unscathed; they were provided free beer and didn’t bother drinking water. The final piece of the puzzle arrived when Dr. Snow was alerted to the death of a woman who had not been in the SoHo area. When the deceased woman’s son informed him that his mother liked the taste of the Broad Street well water so much that she had a servant fetch it each day, he knew his hypothesis was proven. It would take years for the rest of London to believe him.

Exclusive Bonus Content: Need to create your own data visualizations?
Read here the 10 different data visualization types you should know!

6) Worldshapin

Worldshapin is a truly unique data presentation. This visualization takes several development factors for different countries and compares them in an odd, yet interesting way. The color coded shapes on screen can be manipulated by dragging your cursor across a timeline, visually representing the changes different countries or geographic regions experienced over time. This easy-to-use graph is insightful and presents data in a fresh way, letting the user visualize the disparity between countries through interaction.

7) Where the Population of Europe is Growing And Declining

Among the various interactive data visualization examples that we picked, this one is interesting when it comes to the huge amount of data it deals with. The Berliner Morgenpost’s EuropaKarte is a detailed map which provides viewers with detailed insights into the population growth and decline in Europe. Countries are divided into fields corresponding to geographical locations like cities, or even villages with less than 5.000 inhabitants. The fields vary in colors and their intensity, with vibrant orange symbolizing the biggest growth and dark blue the biggest decline. White means no change. When you move the cursor over a selected geographical field, you will see a pop-up with data including the name of the unit, the number of inhabitants and the growth/decline rate. You can also type the name of the location that interests you into the search box and find it easily. Moreover you can use one of the filters to see which municipalities are growing/declining at the fastest pace in Europe or Germany or to view the list of countries with fastest growing/declining populations in total. Last filter will display birth rates of every country listed in descending order. This interactive infographics fits squarely into the current trend of geographical map data visualizations, offered by datapine and some other visualization software providers.

8) Newsmap

Are you a news junkie? This application organizes Google News’s top stories into color-coded category blocks. The size of each story depends on the number of related articles that exist inside each news cluster, so users can quickly identify the stories that receive the most coverage. Users can also filter their news by country and category, making it easy to find the stories that are important to you.

9) Interactive Real-Time Map of Berlin Traffic

Another good real-time data visualization example that shows the location and movement of trains, trams, buses and even ferries in real time. If you want to take a look on the whole city, from a longer distance, the map won’t be of much use. You will just see dozens of signs swarming around like angry ants. To fully appreciate this map’s usefulness you should use one of the filters – you can drill down to a street address, means of communication, lines, stops or stations to get a clearer picture. Moreover, if you zoom in, the map can also display taxis, car sharing, bike sharing and parking lots. If you are still not impressed, click on the icons. If you click P of the parking lot, the pop-up will appear with more detailed information like the number of vacant places or the price. On the other hand, if you click, say a taxi, you will see the car make, and accordingly: a bus – the whole timetable, same for a bus stop – the timetable of every single bus line that stops there. According to VBB (Verkehrsverbund Berlin-Brandenburg), the public transport authority covering the federal states of Berlin and Brandenburg, the visualization doesn’t reflect the bus location with 100% precision, because the data doesn’t come from GPS, but is calculated according to the timetables. So it can happen that a user will wait freezing on a train station expecting the train to arrive, but it won’t appear. However, if it happens that the train is cancelled or it has a serious delay, then it will be taken out of the system. The added value of this kind of timetable is that it can show multiple information at a glance, so that you can decide which transportation will suit you most. The only drawback: the mobile application is so far available only for Android systems.

10) The Dawn Wall

The Dawn Wall is The New York Times’ best interactive data visualization on the astonishing 19-day free climb in Yosemite National Park in California. Tommy Caldwell and Kevin Jorgeson were the first daredevils ever who completed a breathtaking climb up the mostly smooth granite face of El Capitain, widely considered to be the most difficult free-climb in the world. A free-climb means that ropes are used only to catch a climber’s fall — not to aid the ascent. Data visualization complements the story, weaving organically into the narrative and helping the user to picture the scale of this venture.

Exclusive Bonus Content: Need to create your own data visualizations?
Read here the 10 different data visualization types you should know!

11) General Electric

While at first glance, this health infoscape seems overwhelming, a second look will show that it is worth the bounty of information it presents. By gathering data from over 7.2 million electronic medical records, General Electric created an entertaining presentation about the prevalence of health symptoms and the symptoms commonly associated with each other. With pleasing colors and multiple ways to view the relationships, this makes looking at unpleasant symptoms quite enjoyable.

12) The Big Mac Index

Big Mac Index, popularized by The Economist, compares the prices of a Big Mac burger in McDonald’s restaurants in different countries. Why this particular product? Big Mac burger represents a standardized product that includes input costs from various areas, such as agricultural commodities (beef, bread, lettuce, cheese), labor (blue and white collar workers), advertising, rent and real estate costs, transportation etc., and therefore is representative of the general state of the local economy.

The Big Mac Index is a real-time data visualization example that shows whether currencies are at their “correct” level. It is based on the theory of purchasing-power parity (PPP), the notion that in the long run exchange rates should move towards the rate that would equalize the prices of an identical basket of goods and services (in this case, a burger) in any two countries. For example, the average price of a Big Mac in Euro area in July 2015 was $4.05 at market exchange rate, while in the United States it was $4.79. It means that Big Mac in Europe was undervalued by 4.4%.

Scatter chart at the bottom displays the local price of a Big Mac (expressed in the current base currency) against GDP per person in that country. When you move the cursor over individual data points for details, you will see information like GDP per person and Big Mac price in a chosen currency. When you click on the particular country on the map, the scatter chart will be replaced by a line chart displaying the selected country’s under- or over-valuation against the current base currency over time.

Source: The Best Data Visualizations of All Time – Including Interactive Examples

Effective Data Visualization