Meghan Quinn, MFA ’22
thesis abstract
Name: Meghan Quinn, MFA ’22
Thesis cover
Data is analytical, impersonal and intimidating making it hard to decode. Alberto Cairo stated, “ we’ve all heard a picture is worth a thousand words, but what if we don’t understand what we’re looking at? ” Data is our real world behaviors translated into bar charts or spreadsheets—visualizations some struggle to make sense of. Behind these digital representations are people. A text exchange between strangers or friends has a hidden collection of data. Behind this lies people, emotions, connection and stories. My work creates something that is naturally l uid to overpower the
rigidness of data. My work seeks to explore what the input of data looks like as an output. Through the use of visualizations and input/output systems, I am abstracting data and reinterpreting it into a valuable artifact as opposed to a mere statistic. Through this process I am re—i ltering data to create a new more nuanced meaning and a new representation that leaves room for interpretation within the space between data and humans.
Download “DATA ARTIFACTS” (PDF, 55 MB).