Table 3.

Policies, processes and practices to advance ID-GOV.

Ref/Year	Title	Policies, Processes, Practices as Necessary to ID-GOV	Topic/s	Challenges and Barriers to ID-GOV	Considerations for the Advancement of ID-GOV
Canada
[45]/2001	Building Capacity in Applied Population Health Research	Develop population health that is consistent with Ownership, Control and Accessible (OCA). Shared leadership, power, and decision making from design to dissemination. Respect. Resolution (through the Assembly of Manitoba Chiefs) to build research capacity and to extend further First Nation control over the health care systems in their communities.	Health research.	Over-emphasis if pathologizing discourses in Aboriginal health research. Institutional barriers and ownership issues to effective research dissemination. Lacking technical and analytical skills to make information relevant to community health needs and interests.	Build human capital in population health research. Build social capital through the OCA principle. Research institutions, academics, and governments to develop agreements that respect First Nation determination. Build First Nation research capacity. Build partnerships.
[44]/2006	The Manitoba First Nations Centre for Aboriginal Health Research: knowledge translation with Indigenous communities	Participation in the research process from the start. Degree of control or ownership over the research process. Engagement. Trust.	Knowledge translation in research.	The need is greater than the capacity. Ownership and control of research data.	Trust and partnerships.
[30]/2014	Barriers and Levers for the Implementation of OCAP	If there are gaps in legislation, then appropriate tools should be used to apply OCAP®. Preserve ownership and other IP rights. Making OCAP® tools available for use by communities.	Data. Law. Knowledge and capacity.	Identifying applicable laws. Legislative obstacles. Lack of available information. Unreliable information. Capacity limitations. Institutional barriers. Academic culture. Administrative pressure.	Enacting legislation. Amend existing laws (Access to Information and Privacy Act (ATIP) example). Knowledge sharing. Education and training.
Australia
[57]/2016	Building better research partnerships by understanding how Aboriginal health communities perceive and use data: A semistructured interview study	Occupational engagement: Day-to-day relevance; building professional capacity; emphasise clinical relevance. Trust and assurance: Protecting ownership; confidence in local narratives (story telling); valuing local data sources. Motivation and empowerment: Community engagement; influencing morale about the reasons for data collection and use; reassure and encourage clients about the collection and use of their data. Building research capacity: Using cultural knowledge in culturally appropriate research materials resulting in more accurate data collection and dissemination; promote research aptitude; prioritization of data relevant to professional interests and the interests of the community. Optimising service provision: Data are needed to support sustainable; data are required to guide and improve services; best-practice approaches should be supported. Enhancing usability: The presentation of data should ensure ease of comprehension; improve efficiency of data management; valuing accuracy and accessibility.	Access, use and potential value of clinical and research data.	“Top-down” approaches cannot empower Aboriginal community. Aboriginal people are wary of research. There is a need more Aboriginal involvement and control, over health research practices. Lack of time identified as a major barrier to research training and data use.	Address issues of ineffective data use. Encourage health research that is “strengths-focused”. Support the development of research capacity in Aboriginal communities.
Aotearoa/New Zealand
[31]/2014	Enacting Kaitiakitanga: Challenges and Complexities in the Governance and Ownership of Rongoā Research Information	Provision of a collective voice for Indigenous rights. Stewardship could be provided by Māori for Māori. Collective control, in contrast to individual control.	Data governance. Health care services.	History of exploitation. Challenges valuing Indigenous knowledges in Western systems of Intellectual Property Rights. Funding limitations. Capacity limitations. International trade agreements that could override exiting governance. Lack of consistency in legal and ethical policies and documents.	Crown resourcing to support the management and governance of Indigenous data. Knowledge repository for traditional knowledge and contemporary research. Partnerships.
[72]/2017	Engaging Māori in biobanking and genomic research: A model for biobanks to guide culturally informed governance, operational, and community engagement activities	He Tangata Kei Tua model Kawa (principles): (i) kia tau te wairua o te tangata (level of comfort), (ii) kia pūmau te mana o te tangata (level of control), and (iii) kia hiki te mauri o te kaupapa (level of integrity). Kaitiakitanga (guardianship). Purpose. Benefit. Respect for Kawa (principles).	Genomics. Biospecimens.	The move of genomics research into clinical practice should work towards clinical benefits and not perpetuate health inequities by excluding populations from sharing in the benefits of genomic medicine advances or creating opportunities for cultural misunderstandings.	Expanding the discussions and presentations of the He Tangata Kei Tua model.
United States
[20]/2014	Identifying Useful Approaches to the Governance of Indigenous Data	Single-organization data model—outsourcing, Data partnership model—inter-agency coordination, improved efficiency, co-governance of the data asset. Jointly established executive and technical committees to develop and implement framework. Protocols and processes are jointly created. Data commons model—cultivate community of mutual discussion, exchange, and group-sourcing to ensure quality and usefulness. Shared infrastructure or platform that allows members to upload data.	Data governance.	Single-organization data model—what to do with the data belonging to anyone or anything outside of the organization that may be collected and used elsewhere. Data partnership model—Advisory bodies is not data partnership. Data commons model—Near impossible to control the use of data once released into cyberspace.	Integrate disparate, multiple First Nations data sources. Develop and use indicators and performance measures for strategic objectives, visions, and cultural or historical self-understandings of communities. Consolidate information from multiple existing sources (governments and First Nations). Ensure IT infrastructure and technical personnel required to ensure the coordination of data around nations and citizens.
[49]/2014	Exploring pathways to trust: a tribal perspective on data sharing	Partnerships. Development of guidelines that call for re-consent.	Data collection. Data management. Secondary use of research data.	Historical assimilation policies. Bioprospecting.	Partnerships to be situated within the legal framework that protects the sovereign rights of tribal governments. Acknowledgement of IP rights. Protection of Indigenous rights.
[46]/2015	Tribal Archives, Traditional Knowledge, and Local Contexts: Why the “s” Matters	Enabling relationships between Indigenous and non-Indigenous rights holders.	Archival data.	Multiple perspectives, approaches and contexts. Accessibility issues with archival cultural materials in institutions across the globe. Traditional IP system is ineffective.	Repatriation efforts. Development of the Traditional Knowledge (TK) license and label.
[50]/2016	Implementing Qualitative Data Management Plans to Ensure Ethical Standards in Multi-Partner Centres	Community engagement.	Qualitative data. Data protection. Data management.	Institutional Review Board committees cannot anticipate improper data collection, storage, and maintenance.	Invested coordination of qualitative research projects. Inclusion of personnel in Institutional Review Board
[25]/2017	Data as a strategic resource: Self-determination, governance, and the data challenge for indigenous nations in the United States	Existing processes and practices: The development of Indigenous owned and controlled data sets; community-based, nation-driven data governance; assertion of sovereignty over information about Māori; Iwis (tribes) exerting control over the data about their peoples, environments, and businesses; building technical capabilities and partnerships designed to meet tribes’ data needs and support their strategic visions. Emerging processes and practices: Strategically responding to data challenges; engaging with the community to educate leaders and citizens about data; and using data to inform policy decisions and resource allocation that strengthen Indigenous nation sovereignty. Inform internal policy decisions. Identify nation’s assets and allocate resources. Track program and department performance. Access resources. Advocate for external policy changes.	Data. Data Governance.	Inconsistent and irrelevant data. Limited access and utility. Poor quality data. Produced and used within and environment of mistrust. Controlled by those external to the Native nations. Data do not exist to inform tribal needs. Existing data cannot be aggregated in ways meaningful to tribes.	Tribal considerations: Indigenous nation development of institutions to govern data and Indigenous nation engagement of their communities and citizens in defining information needs, designing data collection tools, and interpreting the analyses. Other’s considerations: Acknowledge ID-SOV; include ID-SOV and ID-GOV in tribal, federal, and other governments and organizations’ data policies and processes; invest in capability building to govern data, not just training of individuals to collect and analyse data; and leverage government-to-government relationships between Indigenous nations and other governments to improve data relevance and consistency at federal, state, and other levels. Partnerships.
[17]/2019	Indigenous Data Sovereignty: University Institutional Review Board Policies and Guidelines and Research with American Indian and Alaska Native Communities	Inclusion of Traditional Intellectual Property. American Indian and Alaska Native (AIAN) sovereignty is recognized by the governing body of the state’s universities. Research and institutional engagement principles and best-practice recommendations for collaboration, cultural competency, data storage and sharing.	ID-SOV. Data governance. Institutional governance.	Continue to experience research abuses. Subservience. Struggle to maintain and exercise the right to assert sovereignty in research within community.	Protection and risks to traditional knowledge and intellectual knowledge requires redressing.
[22]/2019	Indigenous data governance: strategies from United States Nations	Data for governance and the governance of data: requirement for accurate, relevant, and timely data for policy and decision making. Additionally requires mechanisms to honour, protect, and control their information both internally and externally. A need to increase capability to govern their data. ➢Data for governance: Quality, relevance, and access ➢Governance of data: Ownership and control Utilisation of tribal legislation and tribal research bodies as governance mechanisms in the governance of Indigenous data. Aligning data with Tribal values and visions. Federal investment to support tribal data collection, analysis, and management; tribal authority to integrate federal program funds for comprehensive and streamlined data collection and management efforts; partnerships between federal agencies and tribes to achieve shared data aims; intertribal forums to encourage the exchange of tribal data best practices. Legal requirements including tribal law and Western legal frameworks.	Data. Data governance.	Power differentials within Western data systems continue to disenfranchise Native knowledge systems and Indigenous peoples.	➢Tribal rights holders Develop tribe-specific data governance principles; develop tribe-specific data governance policies and procedures; generate resources for Indigenous data governance by tribes. ➢Stakeholders Acknowledge ID-SOV as a global objective; build an ID-SOV framework that specifies the relationships among data processes such as collection, storage, and analysis; create intertribal institutions dedicated to data leadership and building data infrastructure and support for tribes; develop mechanisms to facilitate effective ID-GOV; establish data governance mechanisms that non-tribal governments, organizations, corporations, and researchers can use to support ID-SOV; explore the complexities of individual and collective rights in relation to ID-SOV; explore the relationships among ethics, law, data governance in relation to ID-SOV; grow financial investment in Indigenous data infrastructure and capability; identify common principles of ID-GOV; incorporate ID-SOV rights into all rightsholders’ and stakeholders’ data policies; promote adoption and implementation of common principles of ID-GOV by tribes, governments, organizations, corporations, and researchers within the United States. Recruit and invest in data warriors. Share strategies, resources, and best practices; strengthen domestic and international ID-SOV and ID-SOV connections among Native nations and Indigenous peoples.
More than one region and global
[2]/2016	Indigenous Data Sovereignty: Toward an agenda	Research should be carried out in partnership with Indigenous peoples. Internal governance and planning. External advocacy. Utilizing and implementing Indigenous governance. Indigenous leadership. Developing capabilities. Developing accountability mechanisms. Code of research ethics. Privacy impact assessments. Partnership (incorporation). Cultural framework. Certification of institutions (OCAP®). Legal frameworks (jurisdiction, privacy, repatriation). Co-governance arrangements. IP rights that include cultural and tribal IP. Ethics and resource rights. Council committees that advocate on behalf of Indigenous people. Development of protocols. Data governance is facilitated by tribal sovereignty.	ID-SOV. Data. Human rights.	Lack of reliable data and information. Biopiracy and misuse of traditional knowledge and cultural heritage. Data collection is a political exercise. Definitions and identification of Indigenous peoples. Large gaps in the data and information pertaining to Indigenous people (including environmental, cultural, and social gaps) due to inappropriate or ineffective measures. Denial of Indigenous sovereign governance. Limitation is infrastructure and people capacity.	Governance arrangements that allow for institutional oversight of research and data collections. Developing data governance and capacity with the use of Indigenous data. Exploring the implications of individual vs. collective rights for data linkage, sharing and use. Considerations for what happens with the advancement of “big data” and open data. Data are required for effective governance as well as the effective governance of data.
[38]/2009	Developing a Framework to Guide Genomic Data Sharing and Reciprocal Benefits to Developing Countries and Indigenous Peoples	Consulting with communities (to acknowledge sovereignty and human rights) Complexities of consent (individual, community, and state). Training members of local communities in science and healthcare. Training scientists in how to work with Indigenous and developing communities.	Genomics. Data.	Underdevelopment and colonial exploitation that has resulted in political and economic marginalization. Negative experiences in previous health research, resulting in rejecting genomic research. Scientific abuses.	Formalize an organization to support a long-term effort. Develop resource materials. Develop an information campaign. Launch diplomatic efforts to inform global agencies about the issues. Support internal country discussions and policy initiatives about the issues.
[26]/2017	Indigenous health data and the path to healing	Describes existing principles (Snipp 2016)—1. Indigenous peoples have the power to determine who should be counted among them; 2. Data must reflect the interests and priorities of Indigenous peoples; 3. Tribal communities must not only dictate the content of data collected about them, but also have the power to determine who has access to these data. OCAP® principles supported the governance processes for the use of routinely collected health data at the Institute for Clinical Evaluative Sciences (ICES) in Ontaria, Canada: 1. Access to use of data with Indigenous identifiers are approved by data governance committees organized and population by the relevant Indigenous organizations. 2. Specific application and approval must be sought from the relevant data governance committee before researchers or analysts can access them. 3. Researchers are required to discuss their project with Indigenous community representatives, who may collaborate in the planning, conduct and reporting of the studies. 4. Researchers and staff are to build their capabilities in Indigenous worldviews, research principles, and historical and social contexts. 5. Build the capacity of Indigenous organizations and communities to training Indigenous analysts and epidemiologists. 6. Results are co-interpreted with the communities and the representatives who will decide how the results will be disseminated.	Data. Health reporting.	Results often portray Indigenous health as only a problem and over-emphasize negative findings. There are major gaps in the availability and adequacy of data on Indigenous health.	Greater efforts are needed to track the health of Indigenous peoples. Appropriate governance processes need to be developed through governance and data-sharing agreements.
[15]/2019	Data Management in Health-Related Research Involving Indigenous Communities in the United States and Canada: A Scoping Review	OCAP® provides a valuable framework and rights-based approach to data management. Data management is inclusive of both individual and community rights. Participatory approaches to research. Community engagement.	Data management.	History of unethical and misguided research practices. Concerns have included data collection, interpretation and analysis of data, data security, confidentiality, biospecimens and other data storage, regulatory processes in specimen withdrawal and disposal, data sharing, research dissemination processes.	Community-level governance, including data management terms and practices. Indigenous communities are to participate and develop the policies and protocols guiding data management. A need to better understand the role of data management in shaping research practices to benefit and empower communities. Need for standards for reporting on data management.
[81]/2019	Strengthening the Availability of First Nations Data	Better coordination of First Nations data. Develop a First Nations statistical entity or network. Principles overarching the statistical function—First Nations led; independent; meaningful information; confidential; accessible; First Nations Governance of Data; quality/standardized; partnerships.	Data. Data governance.	Vast amount of data collected on Indigenous peoples. Limitations in accessibility by First Nations to data collected by departments and organizations. Data do not respond to the data needs of First Nations.	Development of First Nations institutions to support statistical capability. A need to address the data needs of First Nations governments and to support the planning, decision making and performance measurement. A need to develop standardized indicators that reflect First Nations and their needs.
[37]/2020	Rights, interests, and expectations: Indigenous perspectives on unrestricted access to genomic data	To support greater diversity and inclusion: 1. Building trust, whereby Indigenous communities decide whether their genomic data and associated metadata are publicly available or accessible on request. 2. Enhancing accountability, in which the provenance of Indigenous samples and genomics data must be transparent, disclosed in publications and maintained with the data. 3. Improving equity, whereby credit should be given to Indigenous communities to support future use and benefit-sharing agreements as appropriate.	Genomics. Data.	Substantial risks, few benefits of genomic research for Indigenous communities.	Agencies need to become responsive to the aspirations of Indigenous communities. Science community to become more sensitive to the concerns of Indigenous communities. Research environment to become more conducive to understanding the cultural implications of genomic research. A need for trust, accountability, and equity.
[21]/2021	Indigenous Data Sovereignty and Policy *	Processes that prioritize Indigenous participation and leadership. Contextual processes and practices. Strategic partnerships. Establishment of tribal data policies. Community engagement. Trust. Centralizing Indigenous priority setting. Accountability. Indigenous control. Disaggregated data. Data used for self-determination. Recognition of existing mechanisms (including treaty and human rights). Alignment with developed ID-SOV principles.	Data. Statistics. Secondary use of data. History. Data governance.	Policy practice lacks the integration of Indigenous worldviews. Statistics do not serve the purposes or interest of Indigenous peoples. UNDRIP is an insufficient foundation for the realization of Indigenous peoples’ rights and interests. Voluntary frameworks and principles may result in limited state commitment to ID-GOV. Limitations in ability for Indigenous peoples to contribute to the policy agenda.	Indigenous-designed legal and regulatory approaches to data founded on ID-SOV principles. Global alliance needed to advocate for and advance a shared vision for ID-SOV. Systematic processes to identify the research with Indigenous data. Access to Indigenous data by Indigenous peoples. Enacting FAIR with CARE.

OCAP = Ownership, Control, Access, Possession; IP [23] = Intellectual Property; ATIP = Access to Information and Privacy Act (Government of Canada 1985a); OCA = Owned, Controlled and Accessible; AIAN—American Indian/Alaskan Native; * Book—with information synthesized from several chapters.