Our last few blogs have focused on how to design surveys, maximise response rates and the analysis of the data. All of this is wasted if you are unable to communicate your findings. Traditionally this done in the form of a report made up of several pages of dry text and tables however with the introduction of infographics advances in technology data visualisation has become more than a simple chart of results. Vitality Friedman states that there are much better, creative and fascinating ways to visualise data including the awesome TedTalk below by Hans Rosling using scatterplots.
Data visuals also referred to as infographics are visual representations of information, data or knowledge used to communicate information clearly and effectively.
Development of Data Visuals
The use of graphics to represent information is not a recent innovation, its roots stem from early map-making and visual depiction of events like this visual of planetary movements below from the 10th century.
Source: http://www.datavis.ca/papers/hbook.pdf
By the 16th century techniques and instruments for the observation and measurement of physical quantities, geographical and celestial positioning were well developed. According to Michael Friendly this along with the recording of mathematical functions in tables and the first modern cartographic atlas form the beginning of data visualisation.
The 19th Century is considered to be the golden era of data visualisation and the beginning of modern data visuals. Advances in the technology used for drawing and reproducing images, developments in mathematics and statistics including how data was collected including empirical observation and recording coupled with the rise of statistical thinking and widespread data collection for commerce and planning all contributed to the use of data visualisation today.1800 – 1850 is considered the beginning of modern graphics. During this period all the modern forms of data presentation we have come to take for granted were established.
This includes but is not limited to:
- bar charts
- pie charts
- histographs
- line graphs
- time-series plots
- scatterplots
While the 1800s are viewed as the goldern era for data visuals the 1900s, in particular, the period 1900 – 1950 have been described as the modern dark ages. This is due to few innovations during this period and the waning of enthusiasm for visuals with the rise of social sciences which focused on quantification and formal statistical models focusing on numbers, estimates, and precise standard error rates.
“Pictures were— well, just pictures: pretty or evocative, perhaps, but incapable of stating a “fact” to three or more decimals”
Michael Friendly
An alternative view of this period is that instead of innovation it was a period of application and popularization. During this period statistical graphics became mainstream appearing in textbooks, educational curriculum and became accepted in the fields of government, commerce, and science. Data visuals became so mainstream that in 1914 a Joint Committee on Standards for Graphic Presentation was established and a set of standards and rules for graphic presentations was adopted.
With the advancement in technology in particular widespread access to computers at universities in the 1960s data visuals entered a period of rebirth from 1950 – 1970. While the skills required to hand draw visuals withered during the dark ages technology in particular computer programs opened up the opportunity to reconstruct old graphics and create new forms of visuals including interactive statistics. John Turkey in his paper The Future of Data Analysis published in 1962 called for data analysis to be recognised as a distinct branch of statistics separate from mathematical statistics.
As technology and software advances we will be able to do increasingly more with modern approaches data visuals, we just have to look back at the TedTalk from Hans Rosling at the start of this blog. By taking colourful, moving scatterplots and turning global trend data into an animations Rosling turned “global trends – life expectancy, child mortality, poverty rates – become clear, intuitive and even playful ” according to Friedman.
While we have hit the peak of the rebirth period of data visuals access to big data, technological developments including high-definition and virtual reality who knows what the next development and milestone will be.