Data, Governance, and Cooperatives

Introduction

This document provides a literature survey of resources published by DCI network members and others on the issues of data governance and cooperative governance. Here, we share our reflections on the intersection of these issues along with a set of guiding questions about the ways in which cooperative methods (i.e. those driven by worker/stakeholder ownership and the Cooperative Principles) may influence the discussion around data systems and how they can be governed more equitably.

Perspective

Much recent attention has been paid to the idea of data cooperatives—organizations that are formed to cooperatively govern a shared collection of data gathered from or about a group of individuals. The focus of data cooperatives is on the technical material as constituted (data), and how to care for a particular kind of data collectively. This is in some ways a distinct situation to cooperatives and other existing communities who may have goals and do work not specifically focused on data management, yet are increasingly required to conceptualize, model, and collect data for and about their work—and as a result must confront the transformations that technologies of measurement and prediction impose on their social practices and ways of self-organizing.

Our interest is in how data and artificial intelligence systems can be more justly governed when the platforms, tools, and working practices are designed, sustained, and fully owned by those who are most impacted by how data is collected and used. How do successful cooperatives and other grassroots communities understand and treat their own data, and share it with others? How can contributors retain ownership of data in a way that would allow autonomy over the movement and use of one’s data, or the ability to retract data in the future? How are individual choices about data balanced with those of the community? 

With this project we are researching and developing new ideas toward data governance models that support communities in taking collective ownership of data that relates to them. The following is a growing collection of resources that we have found useful in developing and refining our ideas and vision. Please contact us if you have a resource you would like to add to this list.

Resources

Pluralistic Data Infrastructure 

Article by Antranig Basman for Project We Count, Inclusive Design Research Centre 

The pluralistic data infrastructure supports communities in taking collective ownership of data that relates to them and curating its relationships with data from other sources. Our current architecture focuses on helping communities working with simply-structured tabular data, although the concepts and some of the implementation are applicable to more complex and loosely-structured data. 

Last Mile Model: Decentralized Governance by Women Community Leaders 

Report by SEWA Bharat

How can communities become more participatory in their own governance and thereby bridge the gap between the State and market on one hand and vulnerable populations on the other? Drawing on the examples set by SEWA’s (Self Employed Women’s Association) cadre of grassroots leaders called aagewans, this paper proposes a Last Mile Model rooted in equitable power-sharing through processes of decentralisation. 

CARE Principles for Indigenous Data Governance 

Principles created by Global Indigenous Data Alliance

The CARE Principles for Indigenous Data Governance are people and purpose-oriented, reflecting the crucial role of data in advancing Indigenous innovation and self-determination. These principles complement the existing FAIR principles that emphasize greater data sharing without consideration of Indigenous Peoples’ right to greater control over the application and use of Indigenous data and Indigenous Knowledge for collective benefit.

Understanding Data Stewardship: taxonomy and use cases. 

Report by Aapti Institute in collaboration with the Omidyar Network.

How can we build systems and processes that allow for easy and safe data sharing in ways that enable innovation without compromising individual rights and security and to derive public good? This report describes how in this context, a data steward, an intermediary who facilitates or holds consent and decision-making on behalf of users, is a viable solution that can balance individuals’ data rights and the use of data for societal good. Stewards are also responsible for ensuring data is unlocked to generate societal value and maintain the security standards and quality of the data sets.

Data for Empowerment 

Collaborative research series by Mozilla Insights 

Ideas about new forms of data governance are on the rise, suggesting alternatives to big tech monopolies. Could this help us reimagine, reconstitute, and rebalance skewed power dynamics? The research presented here is an open study by Mozilla Insights that examines approaches to data stewardship and alternative data governance (in theory and in practice).

Shifting Power through Data Governance. 

Mozilla Insights with Jonathan van Geuns and Ana Brandusescu

The Data Futures research presented here is an open study by Mozilla Insights that examines approaches to data stewardship and alternative data governance (in theory and in practice). This research will help inform decisions to support new technologies and infrastructure,as well as support further cross-disciplinary thinking as part of Mozilla’s new Data Futures Lab.

Learning to speak to an elephant and other stories of decentralised futures

Book by Decentralizing Digital

This book is about accentuating the positives among rural communities in Karnataka, India. It explores the possible roles that mesh networks, the Internet of Things, voice-enabled Internet, machine learning, and artificial intelligence might play in enhancing daily life practices that are already successful: ecological agriculture, forest conservation, water management, and place-based education.

Emerging models of data governance

Article by the Joint Research Centre, European Commission

The article examines four models of data governance emerging from the practices of small businesses, public bodies and civic society: data sharing pools, data cooperatives, public data trusts and personal data sovereignty. 

Digital Farmer Profiles: Reimagining Smallholder Agriculture. 

Report by Feed the Future – The US Government’s Global Hunger & Food Security Initiative. 

This report documents experiences in managing digital farmer data by describing how smallholder farmers are defined, the types of service providers that collect farmer profile data, how data is collected, analyzed, and used to support smallholders with products and services, and how this data is shared and managed. It highlights innovative models of smallholder farmer data management and sharing to inspire new thinking among actors in this space and outlines key considerations when assessing existing or investing in new efforts to develop and leverage farmer profile data.