Leanne Fischler

• Year: 2025
• Skills: Design, Research, Futures Thinking, Data Analysis

Exploring Community Data Trusts in Small Places

This dissertation project formed the central component of my MSc in Data, Inequality and Society at the University of Edinburgh’s Edinburgh Futures Institute. It investigated the feasibility and desirability of community data trusts as a model for collective governance of household energy data, focusing on the islands of Hoy and Walls in Orkney.

Data trusts have been proposed as a way for communities to govern and benefit from their data collectively. Yet, their application in small, self‑governed, place‑based groups remains largely unexplored. My research sought to address this gap by prototyping a community data trust and using it as a provocation to spark dialogue about local data use, governance, and trust.

The project was motivated by a broader concern: how can digital technologies be designed and governed in ways that resist extractive logics and instead cultivate fairness, care, and resilience? By situating the work in a small island context, the research highlighted both the promise and the limits of collective data governance in communities where social relations are close‑knit and vulnerabilities are heightened.

Research Focus

This dissertation centred on the idea of a community data trust as a model for collective governance of household energy data. The research did not aim to deliver a fully functioning technical system, but rather to use the prototyping of a data trust as a provocation to explore how such a model might operate in practice within small, self‑governed communities.

Community Engagement in Hoy and Walls
The prototype was used to facilitate conversations with islanders about data, trust, and governance. These discussions revealed how data was perceived not as a neutral resource, but as something that could expose individuals to risk in the context of small communities.

Analytical Framework of Convivial Tools
The convivial tools framework (Illich, 1973; Vetter, 2018; Pansera & Fressoli, 2021) was applied to assess both the prototype and its interactions with the community. This lens emphasised the importance of care, trust, and relational understandings of data, situating the project within wider social and political dynamics.

By combining prototyping, situated community dialogue, and critical analysis, the research explored the possibilities and limits of community data governance in small places, and considered what is required for data tools to be genuinely empowering.

Methodology

The methodology unfolded in two main phases:

1. Prototype Development

   • A working model of a community data trust was designed to demonstrate how household energy data might be aggregated and governed collectively.
   • The prototype embodied both technical and conceptual elements, serving as a tangible artefact through which questions of governance, trust, and care could be explored.
   • Building the prototype itself generated insights into the dependencies of community-built digital tools on wider infrastructures, often shaped by extractive logics.

2. Community Engagement

   • The prototype was used as a discussion tool with islanders, enabling conversations about local data use, governance, and trust.
   • These engagements highlighted how data was perceived not as a neutral resource, but as something that could make people vulnerable in the context of small communities.
   • Islanders’ responses revealed tensions between empowerment and risk, and provided grounded perspectives on the desirability of collective data governance.

The analysis was guided by the framework of convivial tools (Illich, 1973; Vetter, 2018; Pansera & Fressoli, 2021). This lens allowed the prototype and its interactions with the community to be examined in relation to broader social and political dynamics of trust, care, and power. By situating the prototype within this framework, the research was able to assess not only its technical feasibility but also its capacity to embody relationships of care and mutual responsibility.

This methodological choice — combining prototyping with situated community dialogue — ensured that the research remained attentive to both the material realities of digital infrastructures and the lived experiences of islanders. It provided a way to surface tensions, test assumptions, and explore how relational understandings of data might be cultivated in practice.

Findings

The research surfaced three central tensions that shape the feasibility and desirability of community data governance in small, place-based settings:

1. Dependence on Extractive Infrastructures
   The prototype revealed how even community-built digital tools remain reliant on wider infrastructures that are often designed around extractive logics. Hosting, connectivity, and technical dependencies tied the project back into systems that communities cannot fully control. This dependence raised questions about whether genuinely autonomous data governance is possible without rethinking the infrastructures themselves.

2. Data as Empowerment and Vulnerability
   Household energy data was seen as both a potential resource for collective empowerment and a source of risk. Islanders recognised that data could support local decision-making and strengthen community energy initiatives. At the same time, they expressed concern that sharing data in a small community could expose individuals to unwanted scrutiny or compromise social safety. This dual role of data underscored the complexity of building trust around collective governance.

3. Constraints on Relational Governance
   While the idea of relational data governance—treating data as a shared social medium—was appealing in theory, its implementation was constrained by local dynamics. Community processes, existing tensions, and varying levels of digital literacy limited enthusiasm for a formalised data trust. Islanders’ cautious responses highlighted that governance models must be sensitive to the everyday politics of trust and care, rather than assuming that collective ownership alone will deliver equity.

Together, these findings demonstrate that the promise of community data trusts cannot be separated from the realities of infrastructure, vulnerability, and local social relations. For data tools to be genuinely empowering, they must cultivate new relational understandings of data—attentive to risk, power, and care—while acknowledging the wisdom of communities who resist simplistic solutions.

Contribution

This dissertation contributes to the growing field of community data governance by offering a grounded, practice-based exploration of how collective models might operate in small, place-based contexts. Rather than treating the community data trust as a purely technical or legal mechanism, the research demonstrates how its feasibility is shaped by infrastructures, social relations, and lived experiences of risk and vulnerability.

By prototyping a data trust and engaging directly with islanders in Hoy and Walls, the project highlights the importance of situating governance models within everyday community dynamics. It shows that empowerment cannot be assumed simply by shifting ownership structures or aggregating data locally. Instead, genuinely beneficial governance requires cultivating relational understandings of data as a shared social medium — attentive to trust, care, and the politics of small places.

The work also advances methodological innovation by using prototyping as provocation, combined with the convivial tools framework, to surface tensions and possibilities. This approach demonstrates how speculative and participatory methods can enrich social research, bridging critical theory with practical experimentation.

Ultimately, the dissertation adds nuance to debates about digital justice and sustainability. It cautions against simplistic narratives of community empowerment, while also pointing towards principles and practices that could support more equitable futures. In doing so, it provides both academic insight and practical guidance for communities, policymakers, and designers seeking to reimagine data governance in ways that resist extractive logics and foster care.

Reflections

This project began with the hopeful idea that a community data trust could challenge extractive data practices by transferring the benefits of data aggregation to local organisations. What emerged was a more nuanced exploration of power, vulnerability, and the everyday politics of trust in small communities.

Working with islanders in Hoy and Walls revealed that data is not experienced as a neutral resource, but as something that can expose individuals to risk. This insight was invaluable: it showed that reluctance to embrace collective governance was not apathy, but a form of wisdom grounded in lived experience.

The process of prototyping and engaging with the community reinforced the importance of humility and attentiveness in research. It highlighted that technical possibility alone is insufficient; social dynamics, histories of extractive practices, and relational understandings of care must be central to any attempt at community data governance. For me, the project was both intellectually challenging and personally instructive, underscoring the need to listen deeply and to value caution as much as enthusiasm.

Looking Ahead

This dissertation is not an endpoint but a foundation for future work. The findings suggest that socially beneficial data governance will require more than shifting ownership structures or building new technical tools. It demands cultivating relational practices that treat data as a shared social medium, attentive to risk, power, and care.

For communities considering similar initiatives, curiosity should be balanced with caution. Tools must be evaluated not only for their functionality but for how they embody relationships of trust and conviviality. The conviviality matrix offers one way to assess whether technologies align with local needs and values, rather than reproducing extractive dynamics.

In my ongoing professional and creative practice, I continue to explore how digital and energy technologies can support fairer, more resilient communities. The questions raised in Hoy and Walls remain urgent: how can we design data systems that resist surveillance logics, foster care, and empower communities without exposing them to harm?

Listening to the wisdom of communities is essential. Their cautious stance reminds us that empowerment is not simply about control or opportunity, but about navigating risk and responsibility. Building truly empowering data futures will require sustained collaboration, reflexivity, and a commitment to relational governance.