Week 12 - Data Visualisation
Data - noun 1 facts and statistics used for reference or analysis. 2 the quantities, characters, or symbols on which operations are performed by a computer. (Ask Oxford)
Visualising data is one of the most common methods used to graphically convey a logical argument or point in modern day society. Most commonly, the idea of graphs, depicting data is seen to prove and back up statements made and also to demonstrate trends in movements in many circumstances, such as shares, stock, employment figures and public opinion.
As mentioned in the previous entry, Census data is an example of a data visualisation, although a very bland and boring one at that. Due to the increased usability and content available in ‘Web 2.0’, data visualisations have come a long way. We are now able to manipulate and search for data in such a way that we can view data that interests and applies to the individual. Narrowing the search criteria allows the user to find single pieces of data that apply or have meaning to them. We are now able to interact and learn with the world through many ‘social’ data visualisations such as ‘We Feel Fine’ and ‘Tweet Volume’.
‘We Feel Fine”
http://www.wefeelfine.org/index.html
‘We Feel Fine’ is a data visualisation that searches the web for the phrase ‘i feel……’, it then collects that sentence and uploads it to a website called ‘We Feel Fine’, which matches the overall ‘feeling’ of the sentence to a colour depending on what words correspond to various colours. For example, ‘i feel fantastic, just try and stop me!’ could be matched to a bright colour such as yellow, to convey the feeling of joy and happiness. Although set out in a very user friendly applet, the process in which the data is collected and analysed is tedious and complex as seen in the ‘methodology’ section of the website - http://www.wefeelfine.org/methodology.html
“Tweet Volume’
‘Tweet Volume’ is another data visualisation that collects data from one source, ‘Twitter’. The user enters a word in a text box and the applet searches the ‘Twitter’ database for the number of times the ‘word’ appears in users ‘Tweets’. The information is then collated onto a easy to read bar graph that displays the number of times the ‘word’ was used. For example, I created my own data visualisation and I collated the following results using the following words:
Swine Flu - 143,000
Influenza - 42,600
H1N1 - 27,700
Flu - 7,120,000
Mexican Flu - 35,500
During my research, I have discovered the many data visualisation on the ‘www’ and the relationshp they have with ‘social media’ such as ‘Twitter’, ‘Facebook’ and ‘Youtube’. The purpose of these data visualisations is to be able to sift through data, based on user input and present a represenation of data that interests the user. ’Data visualisations’ are now more user friendly and provide a way for people to interact and learn about each other through various mediums that would be otherwise unavailable if ‘Web 2.0’ didn’t exist.
