Abstract
Our movement and sustenance in this data-saturated world is determined by state-issued legal documents that define the extent to which these identifying markers build or dismantle our sense of belonging in the spaces we occupy. The data meant to validate an individual’s identity is utilized just as effectively to segregate and characterize their existence based on gender, race and nationality. The adaptation of data to alienate the target population is applied contextually to fulfill the relevant political/ social agenda. That is how the data can turn one into a migrant in one’s home country and an immigrant in another. I seek to create a portrait in data, constructed from a composite of glitched and non-glitched versions of personal document representations, and analyze the transformation of identity proofs into marginalizing labels. The glitched version will involve manipulating the pixels of the document images based on the document weight calculated as the number of months the document has existed in the system. The degree of the glitch will communicate the estimated distortion of said data based on its systemic use or misuse. The final image will be stitched together as a grid of gifs alternating between original and glitched versions. The objective is to inquire what the collection of data conveys about the self. Does the data rich image represent the self or an identity constructed to “other” the subject?
Presenters
Lini RadhakrishnanStudent, Masters, City University of New York, Graduate Center, New York, United States
Details
Presentation Type
Paper Presentation in a Themed Session
Theme
Civic, Political, and Community Studies
KEYWORDS
DIGITAL HUMANITIES, DATA VISUALIZATION, IMMIGRATION, MIGRANT, ALIENATION, OTHERING, DATAFICATION
