Data is Power, Not Property: Moving from Ownership to Relationships
How ‘data relations’ can empower communities and shift power dynamics
Beyond Ownership: Why the Property Model Doesn’t Work
Imagine waking up one morning to find that every detail of your digital life—your personal messages, your location history, even the metadata of your daily habits—had been claimed as proprietary assets by a corporation. This has already happened - often in ways we don’t always see.
When a neighborhood's worth of Ring doorbell footage becomes Amazon's property, or when your genetic data is sold by ancestry companies to pharmaceutical firms, we're witnessing something unprecedented: the commodification of human relationships and experiences. As someone who studies how communities interact with technology, I've observed that our current framework for understanding data—as property to be owned and traded—fundamentally misses how data emerges from and shapes social relationships.
For years, discussions about data governance have been shaped by one dominant framework: data as property. Corporations extract value from user-generated content, local knowledge gets digitized and commercialized without community consent, workers' performance data intensifies surveillance rather than improving working conditions, and environmental data that could support public health becomes proprietary information. These aren't just privacy issues—they're manifestations of power imbalances that the property framework reinforces.
This model mirrors historical land enclosures—just as land privatization in the past concentrated wealth in the hands of a few, today’s digital enclosures place control of critical data resources in corporate silos, reducing individuals and communities to passive data subjects.
Consider the case of biometric data: governments and corporations collect facial recognition and DNA data under the guise of security and research, yet the individuals providing this data have little to no say in how it’s stored, sold, or used.
Or what happens when a community health center shares patient data with researchers. Under the property model, this is a simple transaction: data is transferred from one owner to another. But in reality, this data represents complex webs of relationships—between patients and healthcare providers, between communities and institutions, between present health outcomes and future research benefits.
But what if we moved away from thinking about data as property altogether? What if, instead of ownership, we focused on relationships?
Data Relations: From Ownership to Stewardship
A shift towards ‘data relations’ means seeing data not as an isolated product, but as a socially embedded resource—one that is generated through relationships, influences power structures, and should be governed accordingly. Unlike the property model, which assumes absolute control by a single entity, data relations emphasize shared responsibility, collective governance, and ethical stewardship.
Communities are already developing ‘data relations’:
In Barcelona, neighborhood health clinics are implementing collective protocols for patient data governance, ensuring research serves community needs while protecting cultural practices.
Urban farming networks in Detroit have created shared data systems for seed libraries and growing conditions, treating agricultural knowledge as a commons rather than a commodity.
In Brazil, community-led environmental monitoring networks collect and govern pollution data, using it to advocate for environmental justice while maintaining local control.
In Canada, First Nations communities are implementing OCAP® principles (Ownership, Control, Access, and Possession) to ensure data about their peoples serves their collective interests.
And in Kerala, India, fishing communities use cooperative data platforms to share market information while maintaining collective control over their knowledge systems.
Rather than asking who owns the data, we should be asking: Who has a stake in it? Who should have decision-making power? What relationships does this data emerge from and affect?
When we treat data as a relationship rather than a commodity, several transformative possibilities emerge:
1. Collective Governance: Communities develop shared protocols for data use that align with their values and needs, preventing exploitative practices and reinforcing digital rights frameworks to drive empowering opportunities
2. Contextual Integrity: Data practices respect the social contexts where information originates
3. Distributed Benefits: Value generated from data flows back to the communities that produced it
4. Dynamic models: Systems that enable ongoing negotiation of data use, rather than one-time terms-of-service agreements that strip users of agency.
The implications transform how we think about data governance. When communities manage health data collectively, they ensure research serves local needs while protecting privacy. When neighborhoods control environmental monitoring data, they strengthen their capacity for environmental advocacy. When workers cooperatively manage workplace data, they gain agency over how automation and efficiency metrics affect their lives.
Here’s what data relations governance looks like in practice:
Barcelona’s DECODE Project – This initiative allows residents to collectively determine how their data is used for public services, offering an alternative to surveillance-driven smart city models.
Open Data Commons in Agriculture – Farmers and researchers are creating shared data infrastructures to promote knowledge exchange while maintaining control over their agricultural insights, rather than handing them over to agribusiness giants.
Civic Data Trusts – Cities like Toronto and Amsterdam are exploring public data trusts where municipal data is managed as a collective asset, with oversight from citizen councils rather than tech corporations.
Patient-Led Health Data Cooperatives – The MIDATA cooperative in Switzerland enables individuals to pool their health data for research while maintaining collective governance over how it’s accessed and used.
Potential Challenges and Unintended Consequences
While data relations offer a more equitable framework, they also introduce new complexities. How do we ensure that community-led governance structures remain inclusive and democratic? What safeguards are needed to prevent governments or corporations from co-opting collective data initiatives? And how do we resolve conflicts over competing claims to data stewardship?
Another challenge is the regulatory gray area in which relational data governance operates. Many legal systems still default to property-based data frameworks, making it difficult to enforce collective governance models at scale. Additionally, well-intentioned data cooperatives or commons could struggle with sustainability, facing funding constraints or governance disputes that limit their long-term viability.
Moreover, traditional rights regimes argue that property rights provide clear rules while relational governance creates uncertainty. They suggest that existing privacy laws and individual consent are sufficient protections.
But these arguments ignore the property model’s limitations, and historical failure to prevent data exploitation or ensure equity. They also overlook the sophisticated ways communities already manage complex relationships and shared resources. Consider watershed management systems where communities have developed sophisticated frameworks acknowledging water as both a physical resource and a web of ecological and social relationships (for example, along the Hudson River in New York). These systems demonstrate how governance can prioritize relationships and collective benefit over individual ownership. However, data presents unique challenges that require new frameworks - it's simultaneously more fluid than physical resources and more deeply embedded in power structures.
Taking Stock and the Potential of Data Relations
Treating data as relationships rather than property fundamentally reshapes democratic possibilities. When communities govern their health data collectively, they can ensure research serves local needs while protecting cultural practices. When workers manage workplace data cooperatively, they gain agency over how automation and efficiency metrics affect their lives. These aren't just theoretical possibilities - they're emerging practices that show how relational approaches to data can strengthen democratic participation and collective decision-making.
The shift from data ownership to data relations isn’t just theoretical—it’s a movement with real implications for economic justice, digital rights, and community empowerment. Instead of waiting for top-down reforms, people are already reclaiming their data through grassroots initiatives and policy advocacy. By supporting cooperative data governance, pushing for policy changes that recognize collective data rights, and educating communities on digital sovereignty, we can actively shape more just and participatory futures.
The commodification of our digitally-mediated lives isn't inevitable. Just as our relationships and experiences can't be reduced to property, the data that emerges from them shouldn't be treated as merely a commodity to be owned and traded. By recognizing data as relationships - between people, communities, and institutions - we open new possibilities for collective governance and shared benefit. The frameworks for relational data governance are emerging through community innovation and practice. Our task now is to strengthen and expand them, reflecting the richness and complexity of human relationships rather than the simplistic logic of property rights.