Notions like ‘Big Data’ and the ‘Internet of Things’ turn upon anticipated harvesting of personal data through ubiquitous computing and networked sensing systems. It is largely presumed that understandings of people’s everyday interactions will be relatively easy to ‘read off’ of such data and that this, in turn, poses a privacy threat. An ethnographic study of how people account for sensed data to third parties uncovers serious challenges to such ideas. The study reveals that the legibility of sensor data turns upon various orders of situated reasoning involved in articulating the data and making it accountable. Articulation work is indispensable to personal data sharing and raises real requirements for networked sensing systems premised on the harvesting of personal data
