The goal of the Computing Community Consortium (CCC) is to catalyze the computing research community to debate longer range, more audacious research challenges; to build consensus around research visions; to evolve the most promising visions toward clearly defined initiatives; and to work with the funding organizations to move challenges and visions toward funding initiatives. The purpose of this blog is to provide a more immediate, online mechanism for dissemination of visioning concepts and community discussion/debate about them.
NSF Data Science Seminar- Making Sense of Found Data
December 7th, 2015 /
in NSF, Research News /
The AAAS Science and Technology Policy Fellows at the National Science Foundation (NSF) have organized another talk in their Data Science Seminar Series from danah boyd on Making Sense of Found Data. The talk will be on Thursday, December 10th from 1:30-2:30PM at NSF Stafford I, Room 110.
is the founder and president of Data & Society
, a research institute focused on understanding the role of data-driven technologies in society. She is also a Principal Researcher at Microsoft Research
, and a Visiting Professor at New York University
. Her research is focused on addressing inequities in society. Currently, she’s focused on research questions related to “big data”, privacy and publicity, and the civil rights implications of data. Her recent book on youth practices – “It’s Complicated: The Social Lives of Networked Teens”
– has received widespread praise from scholars, parents, and journalists.
People have more access to more information than ever before. And those in power have more access to data about people than ever before. The ecosystem of networked information, colloquially referred to as “big data”, introduces a myriad of questions and challenges as the public grapples with privacy, networked sociality, and the politics of algorithms. In this talk, danah will weave together her research on young people¹s practices of social media and the practices of “big data” to highlight challenges and opportunities in making sense of found data.
No RSVP is required if you are coming in person. If you are interested in attending but can’t come in person, the talk will be webcast here. Please register for the webcast beforehand.