Veltman started creating this interactive data visualization by outlining the area teams may claim if fans were decided by proximity. Using Facebook likes, the actual popularity is mapped out for viewers. By hovering over a region, the fan base becomes highlighted according to color. Clicking on the region keeps the space highlighted but can be erased by clicking once more on the interactive data visualization. Veltman admits Facebook likes are not the most accurate way of measuring fans and some counties may have had a close runner up. Yet, it has some interesting results. The NBA, NHL, MLB, and MLS territory maps can be found on this site and are based on the nearest stadium.

Veltman started creating this interactive data visualization by outlining the area teams may claim if fans were decided by proximity. Using Facebook likes, the actual popularity is mapped out for viewers. By hovering over a region, the fan base becomes highlighted according to color. Clicking on the region keeps the space highlighted but can be erased by clicking once more on the interactive data visualization. Veltman admits Facebook likes are not the most accurate way of measuring fans and some counties may have had a close runner up. Yet, it has some interesting results. The NBA, NHL, MLB, and MLS territory maps can be found on this site and are based on the nearest stadium.

Teams with more territory than expected include the Cowboys, Steelers, Packers, Bears, Saints, Dolphins and Giants. Those with less territory include Texans, Panthers, Jaguars, Bills, Rams, Jets, Cardinals, and Chargers.

Although most people know Broadway is the place to see the best live performances in the country, the majority may have never seen the actual street. Yet, the 13 miles of Broadway are now visible through the assembling of images and data from social network sites in a project entitled On Broadway . The project was created by Daniel Goodemeyer, Moritz Stefaner, Dominikus Baur, and Lev Manovich.

The project was inspired by the book, Every Building on the Sunset Strip , which unfolds to 25 feet wide, exposing photographs of both sides of a 1.5 mile section of the Sunset Strip.  Data for On Broadway was collected for a spine-like shape created from 30 meter intervals that were 100 meters wide.

The data visualisation project took data from 660,000 Instagram photos from 158 days in 2014, Twitter posts with photos, Foursquare check-ins beginning in 2009, taxi destinations and pick ups in 2013, Google street views and economic information from the U. S. Census Bureau’s 2013 data. The data was not transformed into a map or chart but a “vertical stack of image and data layers.” The layers include (top to bottom) landmarks and anecdotes, Google Street view, façade colors, taxi statistics, Google Street view from above, social media statistics, income information, colors from Instagram pics, and a listing of the neighborhoods.

The data visualisation showed correlations across the field for certain areas, highlighting some tourist landmarks along the street. The New York Public Library’s Public Eye exhibition has the data visualisation on display until January 3, 2016 or the application can be opened online .

For many, using their first name is impractical because so many share the same first name. Babyname Wizard provides Name Voyager: Baby Name Wizard Graph of Most Popular Baby Names so you can see just how popular certain names are in this datavisualization. Names can be scrolled through with each represented by a line (boys are blue and girls pink) with their thickness representing their popularity. Readers who cannot find their name by hovering over the graph can search for their name specifically and indicate whether they are looking for boys or girls by that name. The datavisualization covers the 1880s until 2014, by decade. Names are listed in the 100,000s per million births.

Hovering over a name in the datavisualization tells the viewer the name as well as its rank at that point in time. Names like “John” show a decline since the 1880s when it was number 1 to number 2 starting in the 1920s. It stayed in the top 10 until 1990s when it moved to number 15. Clicking on the name in the chart takes the reader to a view of only that name. Clicking on the second chart opens a new tab which provides information about the name such as the origin, other name lists featuring the same name, comments from readers, famous people with that name as well as its use in songs, stories and movies.

The New York Times created an interactive data visualization, Connecting the Dots Behind the 2016 Presidential Candidates , to help readers understand the people behind the candidates in the 2016 presidential election. The introduction explains that although the candidates change, often the people behind the campaigns do not. Visualizing data in this way, allows the reader to get a comprehensive look at who is where and where they have been in the past. The visualization begins with Hillary Rodham Clinton who by far has the most connections. Her network is broken into Clinton loyalists, Obama operative, pro-Clinton super PAC, and other key strategists.

Viewers can hover over circles to highlight the connections or see who belongs to which group by selecting a box at the top of her visualization.

The caption explains that the size of the circle is proportional to the number of people in each group. Campaigns are darker and administrations along with other organizations are lighter.

The interactive’s way of visualizing data allows the reader to make connections, literally, that they may not have made otherwise. Besides Hillary Clinton, candidates include Jeb Bush, Ted Cruz, Rand Paul, Marco Rubio, and Scott Walker. The New York Times has several other ways of visualizing data regarding the election including information on candidates’ backgrounds, who is running verse who is not, and who has the campaign money.

Presenting data in a visual form such as a chart, graph or picture is SAS Institute’s definition of data visualization. The analytics software and service company’s What is data visualization web page explains that human brains process charts and graphs faster than spreadsheets or reports. Yet, many still find charts and graphs boring. Enter interactive data visualization offering more details and changing the ways data is viewed. Users can click on parts of the visual to find more information and remain interested.

Data visualization is important because it often allows people to see things which were not apparent before they viewed the data in a visual presentation. Patterns emerge that are not as visible on a spreadsheet and the data can be consolidated regardless of the amount.

SAS does offer advice for generating the best data visualization possible. One tip is to know your audience and how your audience processes information. Second, understand the data and what you want to communicate. Third, choose the best but simplest form to convey your visual information.

All that is great for a business but what is data visualization for the average Joe? If the data exists, it can be made visual whether for use or entertainment. WebdesignerDepot .com offers 50 Great Examples of Data Visualization , including some of the data visualization tools that create them. For example, Narratives 2.0 creates music visualization.

Tag Galaxy allows the user to search Flickr tags and view all images via a globe graphic. Viewers can see a larger version by clicking on a picture.

Visualizing the Bible provide a visual representation of 63,000 textual cross-references in the Bible. It is more for its attractive appearance and is not interactive.

Finally, Visual Complexity is a collection of visualizations categorized and ready for viewing. For example, one contributor created a summary of his son, daughter, cat and his own movements through their living room over one hour in 2008.

Tired of experiencing cold and soggy weather conditions while travel around the United States, designer and software engineer, Kelly Norton, decided to use data analysis in order to find where the beautiful weather was hiding. Using NOAA Global Summary of the Day data archive , he created a data visualizations tool illustrating The Pleasant Places to Live . Defining “pleasant” as areas with temperatures between 45°F and 85°F with little to no snow or rain, Norton literally mapped out the past 23 years of the weather in the U. S.

Data analytics, the process of examining raw data to find conclusions, were used to decipher the data into an interactive identifying the five most pleasant and five least pleasant places in the country. Incorporating cities in a series of circles, the reader can hover over any circle to find the location identified, the number of pleasant days per year, and in which months those days fell.  Users may also enter a zip code to find a location.

Southern California swept the five most pleasant places with Los Angeles, San Diego, Oxnard, Simi Valley, and San Francisco respectively. The least pleasant places are more scatter, located in Montana (twice), Nevada, Wyoming and California.

Breaking down the 2013 Federal Budget is no easy task but Brightpoint , a boutique consulting firm for data visualisation, has done so with an HTML5 data visulisation using D3.js. The interactive allows readers to select an area of spending on the federal, state, or local levels to examine how spending is broken down. By clicking on a circle, the viewer sees the budget broken down even farther up to four levels.

When the cursor hovers over a circle, the federal, state and local budget totals are displayed. The data was collected from public records available from the Congressional Budget Office . Readers can view more than one area of spending at a time for a comparison.

D3.js is a javascript library that allows data driven documents to be effectively manipulation which allows for some remarkable data visualisations. The library, the first that works well on the internet, allows flexibility and manipulations of any of the document object model (DOM). Essentially, D3 makes any data visualisation possible in order to more effectively illustrate data.

Periscopic , a data visualization tool firm, created A World of Terror to explore the extent of terrorism around the world. Data was compiled from the National Consortium for the Study of Terrorism and Responses to Terrorism (START) and Global Terrorism Database (GTD) records ranging from 1970 to 2013. The interactive data visualization tool allows users to view 25 terrorist groups’ actions by five categories including longest active, recent activity, most victims, geographic spread and by the name of the group. The reader can also choose incidents that have been verified for the 25 groups or see all the incidents credited to a group even if not verified by authorities.

By hovering over a group, the reader will see the numbers of incidents that group has been involved with as well as the total number wounded or killed as a result of those incidents. The data visualization tool also includes a chart which represents the number of incidents and when they occurred as well as how many were killed or wounded. A map located above the chart allows the viewer to see which countries the acts of terrorism took place. By clicking on the map, readers can review a brief background of the group.

Al-Qa’ida and Taliban are two of twenty five groups listed in A World of Terror interactive data visualization tool.

The data analytics are summarized in a Sources and Methods link in the bottom left of the page. A brief analysis of the data is broken into the geography, years, wounded, and killed on the bottom right. Basically, the analysis states that the 25 groups selected out of 3,065 listed in the GTD are responsible for 48 % of the wounded and 56% of those killed in terrorist attacks in 73 countries.

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To help fans understand gold medal winning snowboarder Iouri Padladtchikov’s YOLO flip during the 2014 Winter Olympics Games in Sochi an interactive data visualization was created in a collaborative effort between the Neue Zürcher Zeitung , a Swiss newspaper, and +Datavisualization.ch. The finished data visualization was used in the E-book You Only Fly Once published by the paper but its creation is broken down in the article, Interactively Explore the YOLO Flip .

The data visualization tool starts by helping the reader understanding the halfpipe itself using a Swiss train to present an idea of the size and length of the platform, essentially a 22 foot high, 66 foot wide and 591 foot long snow and iced covered ramp.

The reader then can see three aspects of the YOLO flip broken into tricks known as the Backside Air (style), a Frontside 900 (twist), and a Frontside Double Cork 1080 (flip).

Next, the reader sees ghosted key frame overview of the jump. By hovering the cursor over an image, the reader is shown movements taking place as well as the real-time video image. The real time data visualization gives the reader a feel for the jump as they move from image to image or by viewing the original video.

The creators started with a mix of three separately designed screens including an introduction for the visualization tool, a video and an interactive. Yet, the three did not seem right separately so they were combined into one full interactive. Using the SensorLog iPhone app to send information to their computer, they discovered the pitch, roll and yaw by collecting gyroscope data through holding their iPhones to mimic the Russian born Swiss snowboarder’s position. The data had to be adjusted slightly to provide a better visual match so it is close but not perfect.

This is certainly one of the best data viz examples on the block. Tweetping is a real time data visualization of tweets worldwide. Shining dots on the world map show where social media activity is taking place. A panel placed at the bottom of the screen displays various counter widgets providing real time data on total tweet, chart, word, hashtag counts. There are widgets for the whole world as well as separate counters dedicated to South America, North America Europe, Africa and Asia. On the following screenshot which was taken around noon Eastern Time, you can see that most active social media interaction is happening in North America (US and Canada), coastal areas of South America (Brazil, Argentina etc), Europe and South East Asia. It seems that either Australia is asleep or has no interest in tweeting. This real time data visualization is an instance of the data visualization techniques application which is truly capable to wow a viewer.

You can also go to another interesting real time data visualization screen focused on tweets in California . In addition to showing an activity map, this interactive data analytics piece displays an ever changing list of most recent tweets.  They can be clicked taking you to an actual tweet.