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 .

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.

Rock and Roll has undoubtedly been one of the most powerful and influential musical genres throughout last hundred years. Various artists and bands have created music which liberated and energized millions around the globe. Silicon Valley Data Science dedicated an interactive data visualization to 100 years of Rock history which focuses on musical influences among Rock artists.

Viewers can visualize data on singers and bands as circles. Musical influences are charted as lines drawn between the circles. Red circles correspond to an artist or a brand of interest. Golden circles represent influencers and the blue ones correspond to the artists who were influenced. By highlighting a red circle the data visualization displays basic artist information along song stats. Interestingly songs are rated on sad to happy and low to high energy bar charted continuum. On this screenshot you can see a data visualization example of The Doors musical influence. It seems this band drew its inspiration from The Rolling Stones and Bob Dylan. In its turn Jim Morrison&co talent influenced Pearl Jam and Alice in Chains. The right section of this data viz represents a temporal component of this interactive graphic. It shows when the bands started and how long they have been together. This part of the viz is a bit convoluted, but overall it is a creative example of how music history data can be visualized.

This is a sophisticated data visualization which is based on the analysis of 100 years of movie influences by Culturegraphy . According to the creator of this cool website, Kim Albrecht, his endeavor focuses on the investigation of  cultural information exchange done via “memes”. This visualization is an

innovative way to study the complex interconnectedness of cultural development. Below you can see movie reference analysis screen when visualized from genre perspective. There are several views which can be displayed on the website and provide interesting insights into complex cultural interrelationships. Although seemingly complicated, this visualization likely mimics actual cultural interconnectedness closer than standard aggregation tools or rankings.