There were a few important points made throughout this first lecture. First was that there is more data now that at any point throughout history. 23 exabytes (1 exabyte = 1 billion gigabytes) of data was recorded and replicated in 2002 (UC Berkeley’s School of Information Management and Systems, 2003). We now do that in seven days . Richard Saul Wurman (1997) said “There is a tsunami of data that is crashing onto the beaches of the civilised world. This is a tidal wave or unrelated, growing data formed in bits and bytes, coming in an unorganised, uncontrolled, incoherent cacophony of foam. None of it is easily related, none of it comes with any organisation methodology…”. Another important point made is that data itself has no meaning. It does not become information until someone interprets it.
But out of all these I think the most important point was the first one made. Data Visualisation is a mass medium. It has millions of viewers, award shows and even celebrities. It is an essential part of the communication medium, a data driven story without some form of visualisation is like a fashion story without a photo. The reason I think this is the most important point is because it made me realise just how big data visualisation is. There is so much data around today that it now blends into the background and this point made me realise just how much data we consume every day without even registering it.
The featured image here is a data visualisation of the most popular running routes in major cities, this one is New York (Yu, 2014). The data was pulled from the workout app Runkeeper. Darker means there is more traffic, lighter is less travelled.
UC Berkeley’s School of Information Management and Systems,. (2003). How much Information?. University of California, USA. Retrieved from http://www2.sims.berkeley.edu/research/projects/how-much-info-2003/execsum.htm
Waterson, S. (2016). DataVis POD01- What is Data Vis?. Retrieved from https://vimeo.com/175177926
Wurman, R.S (1997) Information Architects, Graphis Inc; USA
Yu, N. (2014). 10 Cool Big Data Visualizations | MastersinDataScience.org. Master’s in Data Science. Retrieved 25 July 2016, from http://www.mastersindatascience.org/blog/10-cool-big-data-visualizations/