Mimi Onuoha is an artist and researcher using data and code to explore new forms of storytelling, social critique, and interaction. She is an Adjunct Professor at NYU, and her work focuses on the overlap of digital and geographic spaces. Mimi is a 2015-1016 Fellow at the Data & Society Research Institute. Her particular focus is on the creation of datasets that represent social structures and experiences that are rarely quantified (e.g., discrimination, harassment), with the aim of empowering users and supporting data journalism efforts. Currently she is combining ethnographic research methods with emerging data practices to investigate missing datasets as opportunities for grassroots data collection.
How We Became Machine Readable

What if the structure of information reveals more than the information itself? What if the most crucial aspect of a dataset is the moment before it becomes one? This talk is about the messy spaces between categorization and collection, as explored through a series of projects that aim to reveal the ways in which we are being and have always been abstracted, represented, classified, and forgotten.