Preserving Location Privacy for Mobile Phones with Homomorphic Encryption: The False Position Protocol

In the data economy, data sovereignty is often conceptualized as data providers’ ability to control their shared data. While control is essential, the current literature overlooks how this facet interrelates with other sovereignty facets and contextual conditions. Drawing from social contract theory and insights from 31 expert interviews, we propose a data sovereignty conceptual framework encompassing protection, participation, and provision facets. The protection facets establish data sharing foundations by emphasizing baseline rights, such as data ownership. Building on this foundation, the participation facet, through responsibility divisions, steers the provision facets. Provision comprises facets such as control, security, and compliance mechanisms, thus ensuring that foundational rights are preserved during and after data sharing. Contextual conditions (data type, organizational size, and business data sharing setting) determine the level of difficulty in realizing sovereignty facets. For instance, if personal data is shared, privacy becomes a relevant protection facet, leading to challenges of ownership between data providers and data subjects, compliance demands, and control enforcement. Our novel conceptualization paves the way for coherent and comprehensive theory development concerning data sovereignty as a complex, multi-faceted construct.

Beyond control over data: Conceptualizing data sovereignty from a social contract perspective

Abbas,

van Velzen,

Ofe

et al. 2024

Industrial data ecosystems and data spaces

Möller,

Jussen,

Springer

et al. 2024

Industrial data ecosystems are inter-organizational forms of cooperation emerging around sharing data. They arise from a digital infrastructure, giving data providers and data users a platform to share and (re-)use data. Data spaces are among the digital infrastructures frequently associated with data ecosystems, as they supply a shared digital space for its participants to share data in a sovereign way. Data spaces aim to close a gap in the digital infrastructure landscape, addressing concerns of organizations when sharing data, such as data misappropriation or a lack of control of shared data. They do this by implementing data sovereignty—typically through Usage Control Policies—that give data providers the means to formalize semantically and technically how data users are allowed to use their data. In this fundamentals article, we address the following issues: (1) contextualizing and demarcating data spaces and data ecosystems, (2) systematizing data spaces in the research and policy landscape, and (3) elaborating on a research agenda for Information Systems (IS) research.

Stuck in the middle with you: Conceptualizing data intermediaries and data intermediation services

Schweihoff,

Lipovetskaja,

Jussen-Lengersdorf

et al. 2024

Data intermediation services are a novel class of services mitigating various aspects of inter-organizational data sharing. Facilitating data intermediation services is a pivotal activity that leverages the benefits of the data economy. These services are usually provided by so-called data intermediaries, who organize data sharing between one or multiple data provider(s) and data consumer(s). Against the background of prominent legislation, these data intermediaries (e.g., data marketplaces or data trusts) receive increasing attention in research, practice, and politics. For instance, the Data Governance Act regulates data intermediation services, prompting organizations sharing data to comply with various regulations, including registration with government bodies or acquiring a trusted label. However, to date, little research has been done about the nature of data intermediation services, motivating us to tackle this issue in a two-fold strategy. First, we derive a visualization of a data intermediary and concept subsuming its potential functions. Second, we explore archetypical configurations of co-existing services of data intermediaries. With this, we contribute to understanding the data intermediaries as a concept and enrich this understanding with more detailed service configurations.