by Jae Kyung Kim

Autocomplete by Jae Kyung Kim

Jae Kyung explored notions of data transparency in this project: “The ability to easily access and work with data no matter where they are located or what application created them….The assurance that data being reported are accurate and are coming from the official source.” Her research question was thus about how to engage viewers with data visualisation while making them  aware of issues of data transparency.

Autocomplete by Jae Kyung Kim

She explored this through the autocomplete function built into contemporary text-entry systems. In Google, she says, autocomplete is similar to the old Google Suggest – a collection of suggested phrases/words based on what other people have entered previously. “They are trying to anticipate your search query before you have finished typing,” she says.

Research by Jae Kyung Kim


Research by Jae Kyung KimShe collected the words most frequently listed by Google for each letter of the alphabet, from the 20 countries with the highest proportion of internet users.


She then used this data to distort each letter, in a new data-driven typeface created in Nodebox.

The project reminded tutor Jon Wozencroft of Oulipo, Pereç’s book without the letter ‘e’, Burroughs’ cut-ups, and The Third Mind.


Kellogg, R., Knoll, M. and Kugler, J., 1965. Form-similarity between phosphenes of adults and pre-school children’s scribblings. Nature, 208(5015), pp.1129-30.

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