How data mined information is recorded and presented is leading to a new movement of data visualization.
But for the data to be useful, the raw data must be synthesized into information: As Tien reports, “today, retailers complain, we are awash in data but starved for information. Thus, in order to overcome the somewhat embarrassing data rich, information poor (DRIP) conundrum it is critical to synthesize this data in to meaningful and understandable information.”
But the synthesis of information does not need to be boring, ugly, stifling. Artists, graphic designers and statisticians have banded together to create methods for making sense of data in beautiful ways. Edward Tufte, a statistician and professor emeritus at Yale, pioneered the early data visualization movement. Through “pictures of numbers” Tufte asserts that statistics can be beautifully presented and that data can be clearly derived from pictorial infographics and the newest wave of data visualization trailblazers take infographics into even more creative territory.
Infographics transform complex information into simple pictorial and graphical visuals. After all, now a days, we eat with our eyes. We struggle with sizing and fit in the apparel industry, but as the infographic below by isegoria.net starts to synthesize some of the complex data on fit across many brands.
Through all this data, we are looking for: 1) Stories that isolate a question from the information; 2) A way to improve connections and relevant data; and 3) a way to visually communicate the story.
However there is criticism about the use and collection of all the data through data mining. Data mining is a computer software process that can analyze billions of sources of information for patterns, but data mining also implies the more sinister activities of surveillance or subject-based information gathering. The artist Amy Balkin provides commentary on the data mining by asking: Who Hearts Data mining: She provides two answers:
Who (hearts) data mining? Most everyone, since the ramifications of new knowledge patterns found in masses of previously uncollectible or un-parsable data allow for new insights and new types of social connectedness.
Who (hearts) data mining? Anyone who profits off of it, or uses it to political ends, such as Facebook, Investigative Data Warehouse, Apple Computer, The Department of Homeland Security, Narus, Target, Twitter, Project Narwhal, or now-shut programs like ADVISE, which in 2006 “was capable of analyzing one billion pieces per hour of ‘structured’ information, such as databases, and one million pieces per hour of ‘unstructured’ information, such as intelligence reports, emails or news articles.”
But people have taking data mining into their own hands at the individual level and started processing their own personal statistics. In 2005, Nicholas Felton decided to compile a statistical and graphical look at his year to tell “his story" to his friends and family with "content I could call my own”. Felton has been compiling The Feltron Annual Reports for each year hence. In 2009 Felton sent out “meaningful encounter card” with an invitation to complete a quick online survey to anyone: from people he met for the first time, to friends, parents and even his dentist. Of 1700 encounters, 200 surveys were completed and 51,00 words submitted.
Felton processed this data with the help of amazonmechanicalturk workforce and was able to synthesize out ‘meaningful information.’ Felton has also created daytum.com a free app for counting and communicating personal statistics so users can create their own annual reports. With this data a better understanding of specific consumers is possible. Through advanced segmentation of the markets we can curate specific marketing information to specific people or small groups. From this information at the individual level, we can make decision down to advanced details like where to buy marketing space: For Feltron we should target subways not taxies, for example.
To reiterate, through all this data, we are looking for: 1) Stories that isolate a question from the information; 2) A way to improve connections and relevant data; and 3) a way to visually communicate the story.
As the introductory image says: Infographic thinking is the future, not a fad. The underlying story is that the value of the raw data-based narratives has to be processed into valuable information that is communicated is easy to manage ways - which is possible through the trend of infographics. I am going to leave on an infographic about infographics, which sums up the arguments pretty well!