Data visualisation

In a world we live in, a world overloaded with information and data, it’s not easy to take in important information and filter out useless junks. In fact, the amount of information we need to take in and process increased by 500% than we do in the 80s. Subconsciously we calculate the price of a product in market and compare with another product, we evaluate the need to bring umbrella based on the chance of rain in weather report, the lists goes on. It’s almost impossible to eliminate or even reduce the amount of information we take in because we voluntary take in those information, we set our phone to remind us when there is an email text and we want to have real time access to weather information. With that been said, even if we voluntary overload our senses we can still make the information we take in easier to understand, and that is where data visualisation came in, its primary purpose is not to reduce the amount of information (it can) but to represent the data into a visual form which might make it easier for us to understand.

Data visualisation can be simple as a line graph and pie graph or it can be very complicated and cool like some data art where scientist, data analysist and artist work together to visualise data. Sometime data visualisation will uncover hidden aspect of the data or connection and relation between individual numbers and stats

Aaron Koblin’s work Flight Patterns is a good example that use Federal Aviation Administration data

Air traffic is heavy in the early evening but hits a low of about 4,100 in-transit flights around 4 a.m. EST. It rockets upward again after the sun rises, peaking around 3 p.m. Take-offs flow in a wave across the country as people wake up and get to the airport. On the East Coast, flights shoot out of major hubs like New York City and Atlanta like the sparks of exploding fireworks, while solitary jets squirm around like protozoa in less-populous areas like Canada and the Gulf of Mexico. (John Metcalfe, 2012)

Mountains out of molehills is a work by David McCandless that visualise fear reported in media

David McCandless describes data as the “new soil” since it’s a fertile medium that nurtures flowers of understanding. He creates aesthetically pleasing infographics that use shapes and colors to show patterns and connections in data, such as a 3D timeline called “Mountains Out of Molehills” that shows how non-issues (such as the Y2K bug) receive excessive coverage in the media during periods when there is no major news. (Jennifer Dutcher, 2013)

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Martine Krzywinski tried to represent Pi into a visualisation to find a pattern or connection between numbers within Pi, Pi is known for its irregular, random and never-ending property, as far as we know, Pi have no repetition and completely irregular.

He connected digits of Pi together, for example 3->1->4->1->5 and link them into a graph

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Reference:

Metcalfe, J. (2012) Visualizing a full day of airplane paths in the U.S.A. Available at: http://www.citylab.com/commute/2012/05/visualizing-day-flight-paths-us/2072/ (Accessed: 14 October 2016).

Flight patterns (no date) Available at: http://www.aaronkoblin.com/work/flightpatterns/index.html (Accessed: 14 October 2016).

McCandless, D. (2010) The beauty of data visualization. Available at: https://www.ted.com/talks/david_mccandless_the_beauty_of_data_visualization (Accessed: 14 October 2016).

Dutcher, J. (2013) David McCandless: The beauty of data visualization – Blog. Available at: https://datascience.berkeley.edu/david-mccandless-the-beauty-of-data-visualization/ (Accessed: 14 October 2016).

Caridad, P. (2013) The art of pi – A colorful data visualization. Available at: https://www.visualnews.com/2013/07/09/the-art-of-pi-a-colorful-data-visualization/ (Accessed: 14 October 2016).

Aaron Koblin (2009) Flight patterns color – HD. Available at: https://www.youtube.com/watch?feature=player_embedded&v=ystkKXzt9Wk (Accessed: 14 October 2016).

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