Whose Data Are They? Data Ownership and Sovereignty in Oral Health Research

Abstract

In the complex and ever-evolving landscape of oral health research, community-based participatory research methods provide essential tools for meaningfully engaging with vulnerable and socially marginalized populations. These methods reflect community needs and integrate their perspectives into oral health research. However, issues of data control, equity, ownership, and sovereignty can lead to ethical and legal challenges. To discuss these concerns, a symposium was held in March 2025 in New York City at the American Association for Dental, Oral, and Craniofacial Research annual meeting. This event explored the intricate dynamics of data access, control, and sovereignty within the context of community-based participatory research, particularly involving vulnerable populations such as Two-Spirit, lesbian, gay, bisexual, transgender, queer or questioning, and other sexual orientations and gender identities (2SLGBTQ+), as well as Indigenous peoples, racial/ethnic minorities, and others. As oral health data become increasingly accessible across various platforms, it is incumbent on investigators to understand appropriate access, ownership, legitimate rights, and the ethical use and reuse of data to uphold equity, rights, and representation. The symposium examined the complex challenges surrounding data access, ownership, and control and their implications for community and individual rights, emphasizing the importance of implementing best practices in inclusive research and prioritizing the voices, rights, and meaningful integration of vulnerable populations. Speakers presented and advocated for multifaceted frameworks that integrate cultural values and traditions, aiming to promote equitable oral health outcomes. The symposium also underscored the critical role of ethical data stewardship in big data and community-based oral health research in American Indian, Hispanic, and Global East African contexts. Case studies showcased collaborative approaches that meaningfully engage community stakeholders and service users throughout the research process, ensuring that data are utilized ethically and yield genuine benefits for the populations involved.

Introduction

In their raw form, data are discrete, unorganized facts and figures, specific elements that lack inherent meaning without context. When these data are systematically collected, structured, and processed, they become information, an organized form that facilitates interpretation (McCloud et al. 2023). Further synthesis, analysis, and contextualization of information yield knowledge that embodies deeper insights and understanding derived from patterns, relationships, and relevance to specific domains or questions. In health research, knowledge generated from such processes ideally informs evidence-based actions, including clinical decision making and public health interventions, as well as development of policies, clinical guidelines, and standards of care (McCloud et al. 2023). However, in the era of precision health and big data analytics, critical questions arise: Where do these vast datasets originate? What is their provenance? Understanding these data streams’ sources and ethical underpinnings is fundamental to maintaining public trust and ensuring responsible research conduct (Hulsen et al. 2019).

Clinical research data are typically obtained directly from individuals who voluntarily participate in research studies under the guidance of rigorous ethical review processes. Participants provide informed consent, granting researchers permission to collect, analyze, and use their data for specified purposes. Ethical research principles and regulatory standards (e.g., the Declaration of Helsinki, the Common Rule) require that participants retain the right to withdraw their consent at any time through written notice, verbal communication, or even by choosing to discontinue participation without penalty.

In contrast, the data landscape in big data research is more complex and often less transparent to participants. These datasets are frequently curated and managed by data repositories or custodians who act as intermediaries between the data sources (e.g., hospitals, health systems) and the researchers requesting access (Hulsen et al. 2019). The original data are typically generated during routine clinical encounters and stored in electronic health records. While patients may authorize use of their health data for secondary purposes under frameworks such as HIPAA (Health Insurance Portability and Accountability Act), revoking that authorization is generally more formalized and limited to written documentation, rather than the broader, simpler consent revocation mechanisms available in prospective research studies.

This divergence in consent mechanisms and participant autonomy highlights key ethical considerations in big data and precision health research. As data become increasingly decoupled from the individuals who generate it, ensuring transparency, accountability, and meaningful consent becomes evermore consequential. Without clear provenance and ethical stewardship, even the most sophisticated data infrastructures risk undermining public confidence and the very validity of the knowledge that they aim to produce.

Data Sovereignty and Empowering Vulnerable Populations

Data sovereignty is essential to dismantling systemic biases in research and promoting equity in vulnerable populations. Collaborative efforts are needed to create ethical, community-driven research frameworks that empower marginalized voices and improve population health.

Data sovereignty refers to the right of communities to control the collection, ownership, access, and use of data that relate to their members, cultures, and lands. It aligns with broader movements for social justice, decolonization, and ethical research with historically marginalized populations (Carroll et al. 2019). There is a critical and growing need for data sovereignty, especially in research involving American Indian and Hispanic/Latino/a communities.

For American Indian nations, data sovereignty is deeply connected to tribal sovereignty—the recognized political and legal right of tribes to self-govern. Tribal data sovereignty asserts that tribal legal systems and cultural values must govern data originating from tribal members, lands, or resources (Carroll et al. 2019; Rhodes et al. 2024). This is not only a technical or regulatory issue but also a matter of self-determination, with tribes having the authority to define how data about them are collected, shared, interpreted, and used (Rhodes et al. 2024).

Data in these contexts often go beyond clinical or biomedical categories. They may carry cultural, historical, and spiritual meanings. Health behaviors, ancestry, environmental data, or traditional knowledge can have implications for identity, sacred practices, and communal integrity. As such, these data should be treated as cultural assets, requiring research practices that respect Indigenous knowledge systems, sovereign protocols, and community-defined priorities (Rhodes et al. 2024).

The lack of adherence to data sovereignty principles has historically led to mistrust in research within many Indigenous communities (Carroll et al. 2019). Experiences of extractive research, data misuse, and lack of benefit sharing have damaged relationships and limited research participation. In response, many tribal nations have established tribal institutional review boards, data governance protocols, and memoranda of understanding to ensure that research reflects tribal interests, values, and laws. These structures promote ethical accountability, equity, and meaningful engagement.

Similarly, Hispanic/Latino/a communities—especially those who are linguistically diverse, socioeconomically marginalized, or undocumented—require culturally responsive approaches to data use (Rodríguez-Lainz et al. 2016). These groups have often been excluded from research or involved only in ways lacking transparency and reciprocal benefit (Garza et al. 2025). Data sovereignty means building trust-based bidirectional research partnerships for these populations that prioritize community values and real-world impact.

Advancing data sovereignty is more than an ethical imperative. It is essential for scientific validity; without culturally grounded governance and community-led interpretation, research risks being irrelevant or even harmful. Incorporating data sovereignty ensures that findings are contextually accurate, locally meaningful, and equitably applied (Hudson et al. 2023).

Data Equity Approaches and Frameworks

Efforts to improve data equity span a range of tools, principles, and initiatives. Some of these constitute structured frameworks, while others represent platforms or guiding principles that contribute to the broader goals of equitable data use.

One widely recognized example is We All Count (https://weallcount.com/the-data-process), which outlines 7 key stages: funding, motivation, project design, data collection and sourcing, analysis, interpretation, and communication and distribution. Each stage is supported by practical tools. For example, in the funding stage, a “funding web” is used to map all stakeholders, such as policy makers, research funders, health care providers, community-based organizations, and patient advocacy groups. This tool helps trace the flow of funds, data, and hence influence, serving as a powerful method to make implicit dynamics explicit and to reveal hidden power structures, including their dynamic changes over time, making the heretofore hidden visible.

The FAIR guiding principles—findable, accessible, interoperable, and reusable—outline best practices in data management and accessibility (Wilkinson et al. 2016). However, FAIR does not explicitly address equity concerns, such as the potential reinforcement of systemic inequities or community representation in data use. In contrast, the CARE principles—collective benefit, authority to control, responsibility, and ethics—developed by First Nations communities in Canada, center on Indigenous data sovereignty and people-first values (Carroll et al. 2020). Researchers have proposed combining FAIR and CARE to yield a more holistic approach that incorporates data, people, and purpose foci.

Formed in 2023, the Stop Bias in Artificial Intelligence Systems Advisory Board (Stop BIAS Advisory Group; Pardo et al. 2025) is a community-based initiative aimed at improving how health data are collected, used, shared, and reused to minimize bias and prevent exacerbating health disparities. The group employs a framework that illustrates how artificial intelligence bias originates—from real-world discrimination to biased design, deployment, and application. Based on this, the Stop BIAS Advisory Group has developed preliminary recommendations to address these concerns.

In 2021, the National Institutes of Health established AIM/AHEAD—the Artificial Intelligence/Machine Learning Consortium to Advance Health Equity and Researcher Diversity initiative—which focuses on supporting equity frameworks, strengthening partnerships, advancing research, enhancing infrastructure, and providing training in data science to promote health equity.

Decolonizing Data through Community-Engaged Research

This symposium at the American Association for Dental, Oral, and Craniofacial Research annual meeting called on research institutions, funders, and investigators to fully embrace data sovereignty in their collaborations with American Indian and Hispanic/Latino/a communities. Doing so requires formal agreements and oversight, a commitment to the cocreation of knowledge, transparency across data life cycles, and shared benefits. Only by prioritizing community agency can we move from extractive data practices to collaborative justice-oriented science that advances knowledge and equity (Robinson et al. 2023).

In the global context, meaningful, community-centered research designs that empower community members in low-resource settings are uncommon. For example, Uganda continues to face entrenched structural and systemic barriers to oral health care. These obstacles disproportionately affect the most vulnerable groups in Ugandan society. In response, stakeholders at the Infectious Diseases Institute and the Rakai Health Sciences Program identified the pressing need for a comprehensive assessment to explore the burden of oral diseases and the accessibility of care across vulnerable populations, including gay, bisexual, and other men who have sex with men and transgender and gender-diverse people, as well as fishing communities around Lake Victoria and urban communities in South Central Uganda. These groups are historically marginalized partly due to social stigma, legal discrimination, and geographic isolation (Jessani et al. 2024). Oral health, often sidelined in global health agendas, is deeply interconnected with overall health, quality of life, and social well-being. Thus, addressing these populations’ oral health needs is a matter of health equity and human rights.

A core tenet of this initiative is integrating a decolonized approach to health data collection and utilization. Decolonizing data requires critically examining who generates knowledge, who controls the data, and how those data are used. This approach prioritizes shifting power back to local communities, amplifying Indigenous and local knowledge systems, and ensuring that data reflect lived experiences and local priorities rather than external agendas.

To operationalize this framework, the team employed community-engaged research as its methodological foundation. Community-engaged research is inherently collaborative, involving community members and local stakeholders as coresearchers throughout the research cycle. This includes codeveloping research questions, designing culturally sensitive tools, and implementing data collection strategies that reflect the unique sociocultural contexts of the communities involved.

Structured community engagement sessions were conducted, enabling open dialogue and iterative feedback on the research design. Community advisory boards, composed of local leaders, faith-based representatives, health care workers, and service users, provided ongoing guidance to ensure that tools were culturally appropriate and scientifically rigorous. Undergraduate trainees from Makerere University and Western University were engaged to foster learner collaboration and capacity building (Jessani et al. 2024). This participatory and context-aware approach is expected to yield critical insights into the epidemiology of oral diseases within these communities and shed light on the systemic inequities that shape access to care. The data generated through this process will inform not only evidence-based interventions but also policy development and health system–strengthening efforts that are community centered, sustainable, and ethically sound.

In sum, this initiative serves as a model for inclusive, decolonized global health research, underscoring the importance of embedding equity, community voice, and cultural competence into all stages of research. Such frameworks are essential for moving beyond extractive research practices toward a more just and collaborative future for global health.

Key Issues Addressed at This Symposium

There was a strong consensus among symposium speakers and audience members participating in the discussion regarding the need for culturally safe and community-integrated practices, including capacity building and community empowerment that advance data sovereignty and ownership. The dialogue reflected a shared commitment to addressing the intersecting issues of underrepresentation, structural inequities, and the unethical misuse of data. The following points were highlighted in the discussion.

Underrepresentation in Oral Health Research

Speakers and audience members participating in the discussion strongly agreed that Hispanic/Latino/a, LGBT+, and other minority communities are underrepresented in clinical research, as study populations and as cocreators of knowledge. One of the consensus principles that emerged was the need for culturally responsive research design, which includes community-engaged protocols, simple and elaborative consent processes, inclusion of community stakeholders, and knowledge users in all stages of research.

Structural Inequities

Discussions highlighted that systemic and structural inequalities, including financial constraints, educational disparities, racism, and homophobia, must be explicitly considered in approaches to data sovereignty. Speakers and audience members participating in the discussion emphasized the need to build community-led data capacity, establish sustainable partnerships and infrastructure (e.g., training, technology access), and promote community-integrated data interpretation that accounts for structural determinants rather than pathologizing or stigmatizing communities.

Ethical Concerns and Data Misuse

Emphasis was placed on ethics pertaining to data misuse and ownership. A clear consensus emerged that communities have the right to govern the collection, ownership, stewardship, and use of data about themselves. To operationalize this, speakers and audience members participating in the discussion emphasized the importance of community-driven data governance, transparent data-sharing agreements that clearly define how data can and cannot be used, and the development of protocols for returning findings to communities in accessible formats. The discussion highlighted the importance of transparency and accountability throughout the research processes, including clearly defined timelines and deliverables, interactive and iterative refinement of procedures, and community-based consensus for adopting principles across all stages of oral health research.

Principles of Data Sovereignty Highlighted

• Community control: Involving American Indian and Hispanic/Latino/a communities in all stages of research ensures culturally relevant and trustworthy data.

• Transparency and accountability: Open dialogue about data use builds trust and fosters participation.

• Equitable benefits: Ensuring that research outcomes serve the community prevents exploitation.

• Community-based participatory research: Such research demonstrates successful institutions through authentic community collaboration and involvement.

• Data hubs for vulnerable communities: Hubs empower community-led advocacy by hosting accessible, locally owned data.

• Local initiatives: These can address environmental justice and education issues through community-controlled data.

Call to Action

Advocate for policy:

Support laws protecting data rights for minority groups. Future goals should include strengthening tribal data governance, enhancing informed consent practices, building local research capacity, and ensuring ethical data use agreements. These steps support self-determination and lasting partnership.

Advocacy for data sovereignty:

Vulnerable communities have been excluded from decisions about how their data are collected, interpreted, and shared. This has led to exploitation and deep mistrust. Data sovereignty seeks to rectify this by restoring agency and aligning research practices with tribal values.

Center community voices:

Listen and collaborate with local organizations to design and implement research based on their needs and choices.

Educate researchers:

Foster ethical, culturally competent practices.

Use technology:

Leverage digital tools for community access and data control.

Data equity depends on community collaboration, transparency, and accountability. By embedding data sovereignty, community engagement, and shared governance into all stages of the research cycle, institutions and researchers can produce knowledge that is community grounded, ethically sound, and equitably applied. These commitments are fundamentally essential for advancing health equity and supporting a more collaborative future for research.

Knowledge Transfer Statement:

This symposium emphasized the critical role of data ownership and sovereignty in advancing oral health equity, particularly for socially marginalized groups such as 2SLGBTQ+ communities, Indigenous peoples, racial minorities, and others. It highlighted best practices for ethical data stewardship and inclusive research that centers community voices. The session offered actionable frameworks to help researchers, policy makers, and institutions build trust, integrate community values, and ensure culturally sensitive outcomes in their efforts to advance health equity.