While lessons about data governance, collective organizing, and personal data rights have existed for years in research across disciplines, technologists tasked with data stewardship still express an uncertainty about what data governance principles should look like in practice.

We define supporting entities as those who help the field move forward by defining the parameters of what data stewardship work is and is not. They fund new projects, convene thinkers, produce recommendations for policymakers, and help guide responsible experimentation. Individuals and entities alike are pushing new conversations into the spotlight about what alternative data governance should be for and how to assess the potential harms of rolling out experimental technologies in the public marketplace.

Key questions for this section include:

• An overview of the supporting entities database
• Who’s providing support for builders?
• What do learning pathways look like?
• How are builders affecting change?
• What are the field’s open questions?

Database overview

We’ve created a library of over 110 supporting entities that we found supporting the ecosystem around builders and data stewards.

Supporting entities are organizations that support or inform builders as Funders, Learning Communities, or Researchers. In some cases, builders are both building and supporting the ecosystem — we call these Hybrids.

Supporting entities can act as conveners, distribute funds, produce policy research, provide legal support, or create data standards or principles among other capacity building functions across the field. While the range of activities supporting entities can undertake is broad, it encapsulates the breadth of activity in this emerging field, and the variety of ways in which the ecosystem requires support to thrive.

Most supporting entities in the field are Researchers producing research or writing about data stewardship or Hybrids building tech infrastructure and sharing lessons or best practices with their peers.

Who’s providing support for builders?

Funders provide financial resources, knowledge resources, and other in-kind support directly to builders who are experimenting in the data stewardship space. Funders’ primary activities involve distributing funds and convening their networks. Some also produce policy research or insights to shape the field.

A majority of builders are able to take on data stewardship projects with support from venture capitalists or philanthropists in their country of origin. Countries in the Global South are also largely influenced by the political priorities of the international aid community.

Both private investors and philanthropists are funding projects on the cutting edge of experimental technologies, but supporting open learning is a priority to varying degrees.

Most funders are not specifically focused on data stewardship initiatives. Later in this section, we will discuss how builders connect to different types of funders depending on how they market their products and based on the learning pathway through which they arrived at working on data stewardship.

Learning Communities are the home base for many builders where issues of sovereignty, governance, digital rights, design justice, and other subjects that are important to the field of data stewardship are discussed. Across industries, learning communities integrate learning about data stewardship across their memberships, and their primary activities involve convening spaces for discourse and producing policy opinions or practice-based learning from the field.

Some learning communities focus on distributing open source technology that peers can build on. For example, Ethereum Swarm is a system of peer-to-peer networked nodes that create open source decentralised storage. They work with the emerging Fair Data Society to distribute grants to builders who use their technologies and align around a set of collectively generated principles.

Many builders attach to a community that convenes people in similar learning pathways and provides small grant funding for experimentation or learning. Theories behind data governance models are diverse and varied. Builders do not gather information about how to govern data from any single knowledge source. Some communities are open to individuals and others primarily convene organizations.

Researchers conduct practice-based or academic research, compile recommendations, and spread resources across the field. They produce knowledge to help builders effectively communicate data governance projects to stakeholders on the ground and remain in step with the field’s recent innovations.

Thought leadership in the form of policy research or open standards documentation can serve builders and practitioners to create more informed data stewardship projects. As stewards of a growing field, many researchers expressed a desire to keep up with experimentation by synthesizing lessons and publishing open documentation in real time.

These are key players in building the sandbox of experimentation that will insulate vulnerable communities from failures of emerging technologies and allow builders to push the boundaries of technology-enabled data ownership.

Specialized researchers can provide necessary culture-informed guidance about technology use to address specific issues related to justice and community empowerment. Groups like Local Contexts, based in New Zealand and working globally, specialize in supporting Indigenous communities and ensuring that data sovereignty efforts remain grounded in Indigenous governance frameworks for determining ownership.

Most builders rely on personal relationships or individual legal experts to advise on the step-by-step processes of managing data. Some researchers pointed out that legal and regulatory definitions for data stewardship are not always clear or actionable, but groups like the Ada Lovelace Institute or the Data Trust Initiative are participating in research exploring legal definitions of governance mechanisms like data trusts.

Hybrid organizations are both building data stewardship technologies and supporting others to replicate or proliferate open source technologies and best practices across the field. They lift up peers in the ecosystem, create collective resistance to monopolistic or exploitative forces in the market, and learn from the open exchange of information. Many hybrids are also leaders in developing actionable data standards and principles for data use or writing about practice-based insights that feed back into the field.

Because of the early stage maturity of the field of data stewardship, real-life examples, tech implementations, and other concrete case studies from hybrid organizations are a first learning resource for many.

What do learning pathways look like?

Many builders enter the field through what we call “learning pathways” which affect how they frame data stewardship issues, how they seek funding, and which audiences or industries their work gravitates toward. We examined how builders come to work on data stewardship technologies after emerging from open data, decentralized tech, social justice, or medical research learning pathways.

Many builders and supporting entities arrived at data stewardship as a means to other social, political, or scientific ends. The goal of most data stewardship projects is to XXX. [Couple of sentences about why they turn to data governance and link to later sections on issue areas and social contracts.]

Throughout this research, we found it helpful to categorize builders and supporting entities by the “pathway” from which they emerged. These pathways form a shorthand for the types of language, goals, and technologies that various builders bring to data stewardship based on the field in which they “learned.” Some pathways include:

Open data. Builders and supporting entities with experience producing open data or advising on open data policies tend to work with non-sensitive data and prioritize maximizing access to information for collective benefit.

Decentralized tech. Expertise with decentralized technologies like distributed ledgers tends to orient builders and funders toward market-based solutions and technologies that enable individual data ownership.

Social justice. Those with experience in social governance through Indigenous governance communities, labor organizing communities, or cooperative structures bring an orientation toward justice and a slight tech-agnosticism that prioritizes sovereignty and responsible data use.

Medical research. The medical research, health, and open science communities have already informed much of the thought leadership around ethics and consent in data stewardship. Builders from these fields tend to bring research-informed tech infrastructures for ethical consent frameworks or personal health data ownership.

These are common pathways by which builders and supporting entities in our limited research process arrived at data stewardship work. These pathways informed our analysis on consumer views, based on the varying language and funding sources that builders use to generate technologies for public use.

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Visual based on this table:

https://docs.google.com/spreadsheets/d/1CZBdqU_oDWnk_bjChJG-u4LqQiwsjskwpFfl2zcHAg8/edit?usp=sharing

[Explain the pathway example below.]

How are builders affecting change?

The uses for data stewardship and alternative models of data governance are extremely varied across industries.

Open Science
Giving research subjects and individuals ownership over biodata; opening scientific practice to prioritize collective learning and knowledge management.

Labor & Platform Work
Organizing platform workers to reclaim ownership of data on outputs and wages; leveraging trade union infrastructures and cooperatives to modernize governance of collective assets and information.

Consumer Rights
Giving individuals the ability to self-monitor browsing and consumption data and participate in the data economy through data unions or collective bargaining; crowdsourcing insights on consumer or social behavior.

Environmental Justice
Improving communities’ abilities to monitor governments and major industries by building collectively governed data commons that maximize transparency and accountability.

Urban & Community Development
Using democratic governance or civic participation to collectivize location, neighborhood, or services data that improve communities’ and governments’ abilities to make decisions around mobility, development, and other elements of urban or communal life.

Indigenous Rights
Ending control or discrimination through dominant technology or data systems by reinstating digital sovereignty in marginalized communities; shifting from oppression through data and technology to empowerment.

Health
Giving individuals ownership of mobile health data and personal health records to ensure that providers and institutions are not the only entities with access to personal data and maximize interoperability across providers.

Banking
Giving individuals control over their banking information through interoperability standards and emerging technologies like account aggregators.

Arts & Culture
Sharing collections data and other art catalogs through open standards; Collectivizing information about art and culture consumption for behavioral insights; sharing data for creativity.

Philanthropy
Opening records on philanthropic giving through data standards and transparency measures to publish open data.

Agriculture
Empowering agricultural cooperatives to monitor weather, markets, or other collectively impactful data that informs production and sales prices; Connecting farmers or fishers to markets through technology platforms that benefit the collective.

Mobility
Tracking location and movement through GPS-enabled smartphones and crowdsourced information, either through data commons or more complex data-sharing models to generate insights.

In each of these industries, power players are shaping the field and affecting builders’ abilities to shift data stewardship practices. In industries with strong monopolistic forces, power players may be overtly adversarial to builders attempting to subvert exploitation through data. In others where power players are more adaptable, it is harder to assess the likelihood that data stewardship technologies will take hold.

Building collective power is a central challenge for many builders who seek to capture a larger share of the market, which means dealing with power players in the space. Some power players, like trade unions, have shown a desire to collaborate with data stewardship builders in the long-term, and others - like tech platforms hoarding data - are openly adversarial toward builders in the near term.

Government, specifically in its role as a regulator, is seen as a possible ally but not the primary vehicle for progress around data stewardship. Builders and supporting entities generally hope that governments will pass regulations that enables data stewardship, but users are often skeptical about trusting governments enough to share data, especially people who have been colonized or disenfranchised by lack of government support in the past. Governments can choose to fund or support organizations that leverage collective data governance measures, and are already shifting the consumer rights space through personal data regulations in countries around the world.

As the most publicly visible hoarders of users’ data and most visible technologies in the sociopolitical domain, many builders and supporting entities see regulation of social media platforms as a vanguard for putting data stewardship protections into law. Builders working with or competing against social media platforms recognize the immediate need for regulation and antitrust action to level the playing field and open space for fair competition. While some believe there is room for more responsible data use among social media platforms, many recognize the political barriers that stand in the way of that shift.

Builders and supporting entities working with trade unions have generally positive relationships but acknowledge that there is significant room for education and capacity-building to help unions effectively use technology. Because trade unions have social and legal infrastructure for collective governance and ownership of assets, technologists are able to build responsibly and innovate on top of existing infrastructure. The success of relationships with trade unions relies on the members’ trust of their unions as responsible intermediaries.

What are the field’s open questions?

The following open questions shaped our conversations with supporting entities and builders, and might provide a roadmap for framework building and further investigations into data stewardship.

Protecting personal data is a necessary framing for gauging the harm and effects of the current data economy. However, interviewees in our research pointed out that if we frame every conversation about data stewardship through the lens of “personal data”, we are adopting a deeply Western worldview that orients the field around individuals rather than exploring the relational and collective qualities of data. They note that our power is not just in owning our own data but in gathering with others to use collective data. Our research found that while these principles are often framed in opposition to one another, they are deeply intertwined.

People may demand control over personal data if builders frame individual control as the best option; but people may demand collective change if builders show them other people with aligned incentives and offer to organize that alternative. Both personal data and collective data governance models, as exclusive frameworks, have drawbacks. Individuals can have differing understanding of benefits and harms, and communal self-monitoring processes can become new ways to exert power.

Generally, though, many felt that the harms of over-reliance on self-sovereignty haven’t fully been explored yet, and that a balance is necessary for society to maximize benefits from data stewardship technologies.

The commodification of personal data is both being debated and actively tested through a number of new technologies that aim to help individuals receive dividends or even establish basic income from selling their data.

While some supporting entities we spoke to were wary of establishing money as an ultimate good in exchange for personal data, early research from groups experimenting in this space (like Streamr and Swash) has shown that money helps consumers understand that their personal data has value, while the actual amount of money that consumers want for their data is still a subject of research.

Paying users for their data could simply be a tool to build trust. One builder noted that “GDPR and other regulations are tightening control. [Advertisers] are interested in any technology that can open up their audience access… And they know that they can’t keep doing business as they are now.”

Monopolistic technologies pose a real challenge for builders and supporting entities alike. Many fear that even if new solutions are introduced to the market, they may not be able to crack big tech’s market share. The Mozilla Foundation has previously written in support of antitrust legislation and support for interoperability standards to improve competition in tech.

Researchers in the field noted that until antitrust and other data protections take hold, builders and innovators will need to work around big tech and instead might have to build an alternate ecosystem. Builders may do this by devaluing work that preaches “AI supremacy” or other hegemonic ideas from which today’s major platforms draw their power. Builders have the power to construct alternative narratives of the future based on principles of openness and learning that could prevent the creation of the next Google or Facebook.

Collective organizing was raised as a necessary precursor to tech implementation by many builders attempting to draw connections between data stewardship and social progress in the world. Many builders see trade unions and the fight to organize platform workers as the current frontier of impactful applications of alternative data governance models.

Even builders not working directly with trade unions or labor organizing shared curiosity about areas where social governance models can act as the foundation for technology solutions that allow for empowerment through data. This issue warrants further inquiry.

Differing uses of new language complicate the question of what is or isn’t “data stewardship” which can lead to confusion for users and co-option by products that are not “data stewardship” projects.

But where should researchers draw the line about standardizing definitions for data governance tools and frameworks? How can supporting entities ensure that misuses of the language of data stewardship don’t damage trust or progress and alienate beneficiaries in the process?

Interviewees mentioned that words like “data trusts,” which are used to describe various types of collective data projects despite the legal definitions, can disenchant people who are counting on these projects to create meaningful change.

Most recently, the EU added infamous digital tech company Palantir Technologies to its GAIA-X project for European “data sovereignty.” But companies like Palantir represent exactly the kind of exploitative practice in data collection and use that true data sovereignty is intended to protect against. Any buzzword can be co-opted by powerful entities if those guiding discourse fail to attach definitions to specific technical, legal, or otherwise concrete mechanisms that separate new methods from the status quo.

Business models. "how can we reconcile data stewardship and collective data governance with traditional business ownership models? We need to think about incentives, the value of data and the consequences. Coops seem to be part of the answer as they solve for the business ownership part of it." I made a suggestion here in key take-aways but you would need to build it in below.