Designing for the Privacy Commons

Mir, Darakhshan

doi:10.1017/9781108749978.011

Cited by 2 publications

(1 citation statement)

References 42 publications

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“…However, the contextual integrity theory does not elaborate on how the contextual informational norms can be established in a social context. To this end, the Governing Knowledge Commons framework can provide a way to derive these contextual informational norms [36].…”

Section: Privacy Governancementioning

confidence: 99%

Data governance in smart cities: Challenges and solution directions

Choenni

Bargh

Busker³

et al. 2022

SCS

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Today, our environment and the objects therein are equipped with an increasing number of devices such as cameras, sensors, and actuators, which all together produce a huge amount of data. Furthermore, we observe that citizens generate data via social media applications running on their personal devices. Smart cities and societies are seeking for ways to exploit these vast amounts of data. In this paper, we argue that to take full advantage of these data, it is necessary to set up data governance properly, which includes defining, assigning, and allocating responsibilities. A proper setting up of data governance appears to be a challenging task since the data may be used irresponsibly, thoughtlessly and maliciously, resulting in many (un)wanted side effects such as violation of rules and regulations, human rights, ethical principles as well as privacy and security requirements. We elaborate on the key functionalities that should be included in the governance of a data ecosystem within smart cites, namely provisioning the required data quality and establishing trust, as well as a few organizational aspects that are necessary to support such a data governance. Realizing these data governance functionalities, among others, asks for making trade-offs among contending values. We provide a few solution directions for realizing these data governance functionalities and making trade-offs among them.

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Section: Privacy Governancementioning

confidence: 99%

Data governance in smart cities: Challenges and solution directions

Choenni

Bargh

Busker³

et al. 2022

SCS

View full text Add to dashboard Cite

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A Roadmap for Applying the Contextual Integrity Framework in Qualitative Privacy Research

Kumar,

Zimmer,

Vitak

2024

Proc. ACM Hum.-Comput. Interact.

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Privacy is an important topic in HCI and social computing research, and the theory of contextual integrity (CI) is increasingly used to understand how sociotechnical systems-and the new kinds of information flows they introduce-can violate privacy. In empirical research, CI can serve as a conceptual framework for explaining the contextual nature of privacy as well as an analytical framework for evaluating privacy attitudes and behaviors. Analytical applications of CI in HCI primarily employ quantitative methods to identify appropriate information flows but rarely engage with the full CI framework to evaluate such flows. In this paper, we present a roadmap to guide HCI and social computing researchers on how to apply the full CI framework to qualitative projects. To help researchers envision what such an analysis can look like, each step includes an example analysis using interview data from projects on privacy and fitness tracking. We conclude by discussing how harnessing the full CI framework can address critiques of CI and identify opportunities for further theory development.

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Designing for the Privacy Commons

Cited by 2 publications

References 42 publications

Data governance in smart cities: Challenges and solution directions

Data governance in smart cities: Challenges and solution directions

A Roadmap for Applying the Contextual Integrity Framework in Qualitative Privacy Research

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