Category: Ideas & Perspectives
Abstract / Executive Summary
Environmental data is becoming an increasingly important resource for governments, researchers, development organisations and businesses. Satellite imagery, forest inventories, biodiversity records, carbon accounting data and community-based environmental observations are now used to inform decisions about natural resources, climate policies and sustainable development. Yet, as these datasets become more interconnected and widely accessible, a fundamental question remains: who has the authority to collect, manage, access, share and benefit from them?
This article examines environmental data ownership as a question of governance rather than simply a matter of technology or database management. It explores the distinction between data ownership, stewardship and access rights, drawing on established frameworks such as the FAIR and CARE Principles, international biodiversity agreements and the Paris Agreement’s Enhanced Transparency Framework.
We argue that effective environmental data systems require clearly defined institutional responsibilities, legitimate access arrangements, transparent data-sharing rules and meaningful participation from communities that contribute to or are affected by the data. Open data and interoperability are essential for scientific collaboration and environmental accountability, but unrestricted access is not always appropriate, particularly where sensitive ecological information or Indigenous knowledge is concerned.
Drawing on our experience in developing national environmental and climate information systems, we also examine how governance considerations translate into practical system design. The central argument is straightforward: technology can organise and connect environmental information, but governance determines who has authority over it, how it can be used and whether its benefits are shared fairly.
Keywords
Environmental data governance; data ownership; data sovereignty; environmental information systems; FAIR Principles; CARE Principles; biodiversity data; digital environmental infrastructure.
Main article
1. Introduction: The Growing Value of Environmental Data
Environmental decisions increasingly depend on information collected across different geographical areas, institutions and time periods.
Governments use forest monitoring data to assess deforestation and prepare climate reports. Conservation organisations rely on biodiversity records to identify ecological changes and prioritise protection activities. Climate programmes require emissions data, monitoring results and financial information to demonstrate progress. Communities collect observations about environmental changes affecting their livelihoods and natural resources.
These activities generate substantial volumes of information, often held by different organisations and managed through separate databases, platforms and reporting systems.
The challenge is not simply whether this information can be collected or stored. It is whether the institutions and people involved have a clear understanding of who controls it, who can access it, under what conditions it can be shared and who is accountable for its use.
Consider a national forest monitoring programme. Satellite imagery may be processed by a technical agency, forest inventory data collected by government departments, and local observations contributed by communities living near forest areas. International organisations may provide financial or technical assistance, while external consultants develop the digital infrastructure.
Once these datasets are combined, who has the authority to determine how the information is used?
The answer is rarely as simple as identifying the organisation that operates the database.
Environmental data governance must therefore be addressed before decisions about platforms, cloud infrastructure or data integration are finalised. Without it, even technically advanced systems can create uncertainty over institutional responsibilities, access rights and the long-term management of valuable information.
In this article, we examine three connected questions: what ownership means in environmental data systems, how governance frameworks can balance accessibility with legitimate control, and what these principles mean for the design and implementation of national digital environmental infrastructure.
2. Understanding Environmental Data Ownership
2.1 Ownership is not the same as custody or access
One of the most common sources of confusion in digital environmental systems is the assumption that the organisation holding data automatically owns it.
In practice, several distinct roles may exist within the same data ecosystem.
- Data ownership concerns the legal rights and authority associated with a dataset or its underlying information. These rights depend on applicable law, intellectual property arrangements, contracts and the nature of the data.
- Data stewardship refers to responsibility for maintaining data quality, integrity, documentation, security and appropriate use over time.
- Data custody concerns the organisation or institution responsible for holding and managing the data.
- Data access determines who is permitted to retrieve or use information and under which conditions.
- Data control concerns the authority to establish rules governing collection, processing, sharing, retention and subsequent use.
These responsibilities do not necessarily belong to the same organisation.
For example, a government agency may commission an environmental monitoring platform and retain responsibility for the underlying national dataset. A technology provider may develop and maintain the platform, while researchers and development partners receive access to selected information.
The technology provider’s responsibility for operating the platform does not automatically give it ownership of the information stored within it.
The Global Biodiversity Information Facility (GBIF) illustrates this distinction in practice. Its data infrastructure facilitates the publication and discovery of biodiversity information, but GBIF does not claim ownership or custodianship of the datasets supplied by individual data publishers. Those publishers retain responsibility for the information and its licensing conditions (GBIF, 2017).
This distinction has important implications for national environmental systems. An institution should be able to identify not only where information is stored, but also who has the authority to make decisions about it.
2.2 Environmental data has multiple sources and interests
Unlike many conventional business datasets, environmental information often reflects shared natural resources, public interests and knowledge contributed by multiple stakeholders.
A single environmental dataset may combine:
- Government-generated monitoring and administrative records.
- Scientific research and academic observations.
- Satellite imagery and remotely sensed information.
- Information collected by international development programmes.
- Private-sector environmental assessments.
- Community-generated observations and traditional ecological knowledge.
Each source may have different legal conditions, sensitivities and expectations regarding access and reuse.
For this reason, it is misleading to assume that all information relating to a particular forest, river or ecosystem should automatically belong to one organisation.
The governance question must be considered at the level of individual datasets and their relationships, rather than treating an entire environmental platform as a single ownership category.
3. Governance Frameworks: Balancing Accessibility and Control
Several established frameworks provide useful guidance for addressing environmental data governance.
3.1 FAIR Principles: Making data usable and reusable
The FAIR Principles, introduced by Wilkinson et al. (2016), provide a widely recognised framework for improving scientific data management and stewardship.
FAIR stands for:
| Principle | Meaning | Practical application |
| Findable | Data can be discovered by humans and machines. | Searchable datasets with unique identifiers and descriptive metadata. |
| Accessible | Data can be retrieved through clearly defined protocols. | Documented access procedures, including authentication where necessary. |
| Interoperable | Data can be integrated with other datasets and systems. | Shared formats, standards and vocabularies. |
| Reusable | Data can be used again for future research and applications. | Clear licences, provenance and documentation. |
The significance of FAIR is that it treats data management as a foundation for scientific discovery and collaboration.
For environmental institutions, these principles can help address a familiar problem: valuable information exists, but different agencies collect and store it using incompatible structures.
A biodiversity dataset, for example, may contain species observations without consistent location references or standardised descriptions. Integrating it with forest monitoring or geospatial information then becomes difficult.
Applying FAIR principles can improve the discoverability, interpretation and reuse of such information.
However, FAIR does not establish who owns a dataset or determine who should have permission to use it. Accessibility does not mean unrestricted access.
3.2 CARE Principles: Recognising people and collective rights
The CARE Principles for Indigenous Data Governance were developed to address an important limitation in conventional open-data approaches.
CARE stands for Collective Benefit, Authority to Control, Responsibility and Ethics.
Carroll et al. (2020) argue that data governance must consider the rights, interests and priorities of Indigenous Peoples, rather than focusing exclusively on making datasets technically accessible.
The distinction between FAIR and CARE is particularly relevant to environmental information.
FAIR focuses on the characteristics that make data discoverable and reusable. CARE introduces a people- and purpose-oriented perspective, asking whether data practices respect the authority and interests of the communities to whom the information relates.
For example, a community may contribute knowledge about medicinal plants, wildlife habitats or traditional forest management practices. Making this information publicly available could support conservation research, but it could also expose knowledge that the community considers sensitive or facilitate commercial use without appropriate recognition or benefit-sharing.
The CARE framework encourages institutions to consider these issues throughout the data lifecycle, including collection, storage, analysis, publication and reuse.
The two frameworks should therefore be considered complementary rather than competing approaches. Data can be technically accessible and reusable while remaining subject to legitimate governance arrangements.
3.3 International frameworks and environmental accountability
Environmental data governance is also closely connected to international environmental agreements.
Under the Kunming-Montreal Global Biodiversity Framework, Target 21 calls for the best available biodiversity data, information and knowledge to be accessible to decision-makers, practitioners and the public.
Crucially, it also states that traditional knowledge, innovations, practices and technologies of Indigenous Peoples and local communities should only be accessed with their free, prior and informed consent, in accordance with national legislation (Convention on Biological Diversity [CBD], 2022).
This establishes an important balance: environmental information should support effective and equitable biodiversity governance, but accessibility must not disregard the rights of those who contribute or hold that knowledge.
The Nagoya Protocol provides another relevant example. It establishes an international framework for access to genetic resources and the fair and equitable sharing of benefits arising from their utilisation, including relevant traditional knowledge associated with genetic resources (CBD, 2011).
In climate governance, the Paris Agreement’s Enhanced Transparency Framework requires countries to report on progress towards their climate commitments, including national greenhouse gas inventories and information on climate policies and support. These reports undergo technical expert review (United Nations Framework Convention on Climate Change [UNFCCC], n.d.).
Together, these frameworks demonstrate that environmental data governance involves more than the technical exchange of information. It also concerns accountability, national responsibilities, legitimate access and the conditions under which information can be used.
4. The Central Governance Questions Every Environmental Data System Must Address
Before developing an environmental information platform, we believe institutions should establish clear answers to several fundamental questions.
4.1 Who has authority over the data?
The first question concerns decision-making authority.
A national environmental database may contain information from multiple government agencies, research institutions and external programmes. Each organisation may have different responsibilities and legal mandates.
Without clearly defined authority, disputes can emerge over who is permitted to approve data publication, modify records, grant external access or authorise reuse.
A governance framework should identify the responsible data owners or rights holders, custodians, approving authorities and operational administrators.
These roles should be documented rather than left to informal institutional arrangements.
4.2 Who can access the information?
Not all environmental data should necessarily be treated equally.
A public emissions dashboard may be designed for unrestricted access, while detailed records concerning endangered species locations, protected habitats or sensitive community information may require restrictions.
A practical approach is to establish data access categories.
| Access category | Typical information | Governance approach |
| Public | Published environmental indicators, approved reports and general monitoring results. | Open access with appropriate attribution and licensing. |
| Institutional | Internal monitoring records, operational datasets and administrative information. | Access restricted to authorised institutions or personnel. |
| Restricted | Sensitive ecological locations, confidential research or protected information. | Controlled access subject to approval and defined conditions. |
| Community-governed | Traditional knowledge and community-generated information subject to collective rights or agreed protocols. | Access determined through legitimate community governance and applicable consent requirements. |
The categories should be adapted to national legislation and institutional mandates.
Importantly, access restrictions should not become a general excuse for withholding information that ought to be publicly available. The objective is proportionate access, not unnecessary secrecy.
4.3 Who is responsible for data quality?
Data availability does not automatically guarantee data reliability.
Environmental datasets may contain incomplete observations, inconsistent measurement methods, outdated records or differences in geographical resolution.
If information from several institutions is integrated into a national platform, the system must preserve its origin and provide enough context for users to interpret it correctly.
This requires clear responsibility for:
- Data collection and validation.
- Quality assurance and correction procedures.
- Metadata and documentation.
- Version control and update frequency.
- Identification of the organisation responsible for each dataset.
- Recording changes and maintaining audit trails.
These arrangements are particularly important when environmental information supports national reporting, carbon accounting or policy decisions.
4.4 Who benefits from the information?
Environmental data can generate considerable public, scientific and commercial value.
It can support conservation planning, climate finance, investment decisions, research and environmental assessments. However, the organisations that generate or contribute information do not necessarily receive the benefits arising from its use.
This is particularly relevant where local communities provide environmental observations or traditional knowledge.
A responsible governance framework should consider attribution, access to resulting information, capacity development and fair benefit-sharing where applicable.
The question should not simply be whether information can be extracted from a community or institution. It should also be whether the resulting data ecosystem creates value for those who contributed to it.
5. From Governance to Technology: What Should Be Designed First?
Once institutional responsibilities and data-sharing principles are established, technology can provide the infrastructure needed to implement them.
In our work developing digital systems for environmental and government programmes, we approach technology as part of a wider institutional process. The system must reflect the client’s requirements, operational responsibilities and long-term capacity to manage it.
This is particularly relevant when multiple agencies need to work with information held across different institutional environments.
5.1 Establishing institutional responsibilities before integration
An integrated platform can bring together information from several departments, but integration should not automatically remove the responsibilities of the institutions that generate and maintain the data.
A national environmental information system, for example, may consolidate forest monitoring, biodiversity indicators, geospatial information and climate-related datasets.
Before these sources are connected, institutions should agree on:
- Which organisation is responsible for each dataset.
- Who validates and approves updates.
- Which information can be shared across agencies.
- Which datasets can be published publicly.
- Who is responsible for responding to data-quality issues.
These decisions should inform the system architecture and integration requirements.
5.2 Embedding governance into system architecture
Governance should be reflected in the technical design rather than treated as a separate policy document.
Several capabilities can support this:
Role-based access control: Different users receive permissions appropriate to their institutional responsibilities.
Audit trails: System activities and changes can be recorded to support accountability and traceability.
Data documentation: Metadata, sources, update histories and responsible institutions should be identifiable.
Interoperability: APIs and standardised data structures allow authorised information exchange between systems.
Security and data protection: Appropriate safeguards help protect sensitive information against unauthorised access or disclosure.
Data portability and handover: Documentation, databases and source code should be managed according to the agreed contractual arrangements, enabling institutions to maintain their systems over time.
These are practical mechanisms, but they do not independently establish ownership. Their effectiveness depends on the policies, agreements and institutional responsibilities governing their use.
5.3 Designing for institutional continuity
Environmental data systems are often intended to operate for many years, beyond the duration of individual projects or funding arrangements.
This creates a significant governance challenge: what happens when an external implementation partner leaves, a funding programme ends or institutional responsibilities change?
We consider documentation, administrator training and structured handover essential elements of sustainable digital delivery.
A system should not become dependent on the continued presence of the original developer simply because the institution lacks the knowledge or technical access to operate it.
Where agreed within the engagement, transferring source code, databases and documentation to the client helps establish a foundation for institutional continuity.
The objective is to enable the responsible institution to retain operational control of its digital infrastructure, subject to the relevant data rights, licences and contractual arrangements.
6. What We Learn from Implementing Environmental Information Systems
Our experience in national digital infrastructure highlights the practical relationship between institutional governance and technology.
In Papua New Guinea, our work includes the development of the National Carbon Registry and the REDD+ Safeguards Information System, alongside national environmental and geospatial platforms.
These systems address different operational requirements, but they share an underlying challenge: environmental information must be organised in ways that support institutional responsibilities, reporting and decision-making.
The National Carbon Registry provides infrastructure for managing national carbon-related information. The REDD+ Safeguards Information System supports the tracking and presentation of safeguards information. National forest monitoring and geospatial platforms bring together information relevant to environmental management and monitoring.
These examples illustrate why a database alone is insufficient.
A carbon registry must support reliable records and appropriate institutional controls. A safeguards information system must make relevant information available while respecting the sensitivity of particular records. A forest monitoring platform must organise information in a way that supports meaningful interpretation and ongoing institutional use.
In each case, system design needs to reflect the operational and governance requirements of the institution responsible for the information.
We also recognise that national environmental systems frequently involve multiple agencies and technical partners. Their successful operation depends on more than software integration. Responsibilities, documentation, access arrangements and institutional capacity must be addressed throughout implementation.
For us, this means that governance considerations belong in the initial assessment and requirements-design stages, not merely in the final security review.
7. Challenges, Limitations and Counterarguments
7.1 National sovereignty does not resolve every ownership question
Governments have legitimate responsibilities concerning national environmental resources and information. However, the principle of national sovereignty does not automatically resolve every question about data ownership.
Datasets may contain third-party intellectual property, personal information, community knowledge or information governed by specific contractual arrangements.
National institutions must therefore consider the legal status and origin of individual datasets rather than assuming that all information held within a government platform has identical ownership conditions.
7.2 Open data can conflict with legitimate protection
Open environmental data can improve transparency, scientific collaboration and public accountability.
However, unrestricted publication can create risks where datasets contain sensitive ecological information or knowledge that communities have not agreed to share.
The appropriate response is not to abandon open data, but to establish clear and proportionate rules for access and reuse.
FAIR principles provide guidance on accessibility and reuse, while CARE principles help address the rights and interests that may be overlooked by purely data-centred approaches.
7.3 Governance is difficult to implement across institutions
Even where policies exist, institutions may lack the resources, technical skills or coordination mechanisms required to implement them consistently.
Different agencies may use incompatible data standards, have overlapping mandates or operate under different reporting requirements.
In some contexts, the organisation responsible for maintaining a dataset may not have the authority to approve its publication or commercial reuse.
These challenges cannot be solved through technology alone. They require institutional agreements, clear responsibilities, capacity development and sustained coordination.
7.4 Ownership is not always the most useful starting point
There is also a legitimate argument that focusing too heavily on ownership can create unnecessary barriers to collaboration.
Some environmental information is generated through public funding and is intended to serve broad public interests. In these cases, making information openly accessible may be more valuable than establishing restrictive proprietary claims.
The objective should therefore not be to maximise ownership claims or centralise control. It should be to establish legitimate authority, clear responsibilities and appropriate access arrangements.
Good governance enables information to be shared where sharing creates public value, while protecting rights and interests where restrictions are justified.
8. Implications for Governments, Development Partners and Technology Providers
The question of environmental data ownership has practical consequences for every organisation involved in environmental programmes.
For governments, data governance should form part of national digital and environmental strategies. Institutions need clear mandates, documented data-sharing arrangements and mechanisms for maintaining information beyond individual projects. National environmental platforms should strengthen institutional capacity rather than create new dependencies.
For development partners and donors, data ownership, access and handover arrangements should be addressed during programme design. Agreements should clarify what happens to datasets, documentation and digital infrastructure when funding ends. Community participation and benefit-sharing considerations should also be incorporated where relevant.
For research institutions, data-sharing policies should distinguish between information that can be openly published and information requiring additional permissions or safeguards. Researchers should preserve provenance, provide appropriate attribution and respect the conditions attached to datasets.
For local communities, participation should extend beyond contributing observations. Communities should have meaningful opportunities to influence how their knowledge is represented, accessed and reused, particularly when information concerns their territories, livelihoods and traditional practices.
For technology providers, the responsibility is to translate agreed governance requirements into workable technical solutions. This includes implementing access controls, documentation, auditability, interoperability and secure data management. Technology providers should not independently determine the legal ownership or legitimate use of information on behalf of their clients.
At Eywa Systems, we see this as part of a broader approach to digital transformation: understanding institutional needs, translating them into functional requirements, developing appropriate infrastructure and ensuring that the responsible institutions can operate and maintain the resulting systems.
Ultimately, a well-designed environmental information system should make institutional responsibilities clearer, not obscure them behind technical complexity.
9. Conclusion
Who owns environmental data? There is no universal answer, because environmental information is generated through different activities, legal arrangements and relationships between institutions, researchers and communities.
The more useful question is who has the legitimate authority and responsibility to govern each dataset throughout its lifecycle.
The FAIR Principles demonstrate why environmental information should be findable, accessible, interoperable and reusable. The CARE Principles show why these objectives must be balanced with collective benefit, authority to control, responsibility and ethical considerations. International environmental frameworks further reinforce the importance of accessibility, accountability, consent and fair benefit-sharing.
These principles have direct implications for digital environmental infrastructure. Ownership, access rights, stewardship responsibilities and data-sharing arrangements should be established before information is integrated into national platforms. They should then be translated into technical requirements, institutional procedures and long-term operational arrangements.
Technology can make environmental information easier to collect, connect, analyse and share. But it cannot independently determine who has the right to use that information or who should benefit from it.
Before building a system to manage environmental data, we must first establish the rules governing that data. Governance comes before technology because the value of an environmental information system ultimately depends on whether the information within it is managed legitimately, responsibly and in the public interest.
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