@article { , title = {The cardboard box study: understanding collaborative data management in the connected home}, abstract = {The home is a site marked by the increasing collection and use of personal data, whether online or from connected devices. This trend is accompanied by new data protection regulation and the development of privacy enhancing technologies (PETs) that seek to enable individual control over the processing of personal data. However, a great deal of the data generated within the connected home is interpersonal in nature and cannot therefore be attributed to an individual. The cardboard box study adapts the technology probe approach to explore with potential end users the salience of a PET called the Databox and to understand the challenge of collaborative rather than individual data management in the home. The cardboard box study was designed as an ideation card game and conducted with 22 households distributed around the UK, providing us with 38 participants. Demographically, our participants were of varying ages and had a variety of occupational backgrounds and differing household situations. The study makes it perspicuous that privacy is not a ubiquitous concern within the home as a great deal of data is shared by default of people living together; that when privacy is occasioned it performs a distinct social function that is concerned with human security and the safety and integrity of people rather than devices and data; and that current ‘interdependent privacy’ solutions that seek to support collaborative data management are not well aligned with the ways access control is negotiated and managed within the home.}, doi = {10.1007/s00779-021-01655-9}, eissn = {1617-4917}, issn = {1617-4909}, issue = {1}, journal = {Personal and Ubiquitous Computing}, pages = {155-176}, publicationstatus = {Published}, publisher = {Springer Science and Business Media LLC}, url = {https://nottingham-repository.worktribe.com/output/6457354}, volume = {26}, keyword = {Management Science and Operations Research, Computer Science Applications, Hardware and Architecture}, year = {2022}, author = {Kilic, Damla and Crabtree, Andy and McGarry, Glenn and Goulden, Murray} }