Data Justice and Governance in Digital Societies

Data justice and governance have emerged as central concerns in an era defined by pervasive digitalisation and datafication. Data justice encompasses a range of ethical, legal and social considerations that seek to ensure fair treatment of individuals and communities in the collection, processing and distribution of data. At its core, it interrogates issues of power, equity and accountability in data-driven systems, addressing procedural dimensions (transparency, participation and contestability), distributive dimensions (equitable access to data benefits) and structural dimensions (long-term patterns of inclusion or exclusion). Effective data governance frameworks must balance innovation with protection of rights, embedding principles of privacy, non-discrimination and democratic oversight into technical architectures and policy regimes. Globally, jurisdictions are experimenting with novel models—from public data commons and platform cooperatives to regulatory sandboxes and impact assessments—to foster data stewardship and digital sovereignty. These approaches aim to cultivate trust, enhance data literacy and empower marginalised groups, while also grappling with cross-border data flows, environmental sustainability of digital infrastructures and the implications of algorithmic decision-making. The interplay of civil society advocacy, industry self-regulation and state intervention underscores the need for multi-stakeholder collaboration, robust standards and adaptive governance mechanisms to realise socially just and inclusive digital futures.

Research from Nature Portfolio

Recent studies have undertaken a large-scale audit of text datasets used in machine learning, revealing substantial gaps in licence transparency and accuracy. By tracing the provenance of over 1,800 datasets, researchers have identified high rates of licence miscategorisation and omission, particularly affecting low-resource languages and creative tasks. To address these shortcomings, an interactive Data Provenance Explorer was developed, enabling practitioners to filter and trace dataset origins, licence conditions and lineage. This work highlights the critical role of data provenance tools in fostering responsible AI development and informs emerging guidelines for dataset documentation, attribution and ethical reuse.

Data Justice and Governance in Digital Societies publication trend

The graph below shows the total number of articles in data justice and governance in digital societies across all publications each year (not limited to Nature Index journals).

Technical terms

Data justice: A normative framework concerned with fairness, equity and accountability in the entire data lifecycle, encompassing rights, procedures and structural impacts.

Data governance: The ensemble of policies, standards, practices and institutional arrangements that guide the collection, management, sharing and use of data.

Datafication: The transformation of social actions, processes and phenomena into quantifiable data amenable to analysis and computational use.

Data provenance: Information tracing the origin, ownership, licensing and processing history of a dataset, crucial for transparency and ethical reuse.

Data solidarity: Practices of mutual support and collective stewardship among stakeholders to promote equitable data sharing and collaborative governance.

References

1. A large-scale audit of dataset licensing and attribution in AI. Nature Machine Intelligence (2024).
2. Health data justice: building new norms for health data governance. npj Digital Medicine (2023).
3. Transforming towards inclusion-by-design: Information system design principles shaping data-driven financial inclusiveness. Government Information Quarterly (2024).
4. Data justice and data solidarity. Patterns (2022).
5. Data justice. Internet Policy Review (2022).
6. Embedding European values in data governance: a case for public data commons. Internet Policy Review (2021).
7. Towards Rawlsian ‘property-owning democracy’ through personal data platform cooperatives. Critical Review of International Social and Political Philosophy (2020).
8. Big Data, Big Waste? A Reflection on the Environmental Sustainability of Big Data Initiatives. Science and Engineering Ethics (2019).