Unclear data licences are stalling the world’s first global ecosystem map

A quarter of the way through the twenty-first century, humanity still lacks a comprehensive, authoritative, and scientifically sound map of the world’s ecosystems. That may sound surprising in an age of ubiquitous satellite imagery and increasingly powerful machine-learning classification algorithms, but the bottleneck is not technology. It is law. According to a new opinion article published in PLOS Ecosystems, the greatest obstacle to building a truly global picture of Earth’s ecosystems is something as mundane as ambiguous data licensing—and the scale of the problem is now quantified for the first time.

The article, written by Falko Buschke, David Patterson, and colleagues at the Global Ecosystems Atlas initiative, convened by the Group on Earth Observations (GEO) Secretariat in Geneva, together with collaborators at James Cook University in Australia, draws on an extensive audit of candidate datasets for the Atlas. As of January 2026, the team had compiled a catalogue of 343 ecosystem datasets that could, in principle, be combined—with full attribution to their owners—into the first comprehensive, standardised, and open global map of ecosystems. Yet nearly one-third of those datasets, 29.7 percent, provide no explicit guidance whatsoever on how the data may be reused.

That figure matters because of a legal default that most people never think about. Like all creative works, ecosystem maps remain under exclusive copyright unless clearly stated otherwise. In practical terms, this means that even when a dataset is freely downloadable from a public website, users must assume it is protected and cannot be reused without prior permission. Permission takes the form of either an explicit data licence or direct authorisation from the provider. A dataset that sits openly on the internet but carries no licence statement is, legally speaking, locked.

The consequences ripple far beyond academic inconvenience. The Global Ecosystems Atlas is designed to bring together existing ecosystem information from trusted sources—national authorities, nongovernmental organisations, and the peer-reviewed scientific literature—and to fill remaining gaps using classification models trained on expert-evaluated, point-based data. Local expertise remains fundamental to this approach: field surveys of species composition, annotations of ecosystem-class records, and manual refinements of historical maps all feed into the final product. Top-down global approaches, however sophisticated, have repeatedly proven resistant to producing accurate maps without this local validation. When a third of the underlying information cannot legally be integrated, decades of preceding investment in local knowledge are effectively stranded.

The audit revealed a licensing landscape that is fragmented in ways that impose real technical and legal costs. Beyond the unlicensed third of the catalogue, a further 20.4 percent of datasets are governed by custom licences—legal terms tailored to a specific dataset or institution. These range from institutional policies of national governments and large research organisations to personalised modifications of standard licences. Some data owners even offer different conditions to different users, permitting free use by individuals and small businesses while restricting large corporations above a certain size. For nonexperts, navigating such bespoke terms is daunting, and for project managers, custom licences introduce legal overheads to verify compliance. Worse, when custom licences embed copyleft conditions—requiring that any derivative work be shared under identical terms—they severely limit uptake in composite products.

Only 47.8 percent of the datasets in the catalogue are shared under Creative Commons licences, the standardised public instruments designed precisely to make reuse conditions clear. Within that open minority, the majority—39.6 percent of all datasets—require simple attribution (CC-BY), while just 4 percent restrict reuse to noncommercial purposes (CC-BY-NC). On the surface, that seems like a healthy majority of usable data. But the mathematics of aggregation is unforgiving: any derived product assembled from multiple datasets must be licensed according to the most stringent conditions of its constituent parts.

This ‘weakest link’ principle means that even a single restrictive dataset can contaminate an entire global product. Include one dataset carrying a noncommercial condition, and the whole composite is barred from commercial applications such as corporate biodiversity reporting—a rapidly growing use case as companies come under pressure to disclose nature-related risks. Add a no-derivatives condition, and the product cannot be combined with any other dataset at all. A share-alike condition constrains the licence of everything downstream and can conflict with datasets that carry slightly different terms. In a synthesis that might draw on hundreds of sources, a handful of ambiguous or restrictive licences can quietly determine what the final map is legally allowed to do.

It is tempting to conclude that all ecosystem data should simply be released under maximally open licences. The authors resist that blanket prescription, and for good reason. Biodiversity data can be regarded as social infrastructure, and respecting data sovereignty—particularly that of Indigenous peoples and marginalised communities—is essential for equitable and effective conservation outcomes. Selling commercial access to biodiversity information is also a legitimate way for custodians to recoup the costs of producing and maintaining it, which is only possible when commercial rights are protected. Open data advocacy that ignores these realities risks repeating the extractive patterns that conservation is trying to move beyond.

In their discussions with data owners—scientists, government officials, and NGO researchers—the team found that licensing is often an afterthought, with stakeholders receiving little guidance on how to select and apply licences that support their intended uses. Their response is a set of three practical recommendations. First, license ecosystem data explicitly: choosing an appropriate Creative Commons licence with a user-friendly selection tool and copying the licence information alongside the data—on the access website, or in a ReadMe or metadata file accompanying GIS files—can take minutes. Second, use standardised licences wherever possible, since Creative Commons terms are translated into many languages and widely understood, whereas custom licences often impose the same restrictions in inaccessible legal jargon. Third, when restrictions are genuinely necessary, build in mechanisms to navigate them legally. The World Database on Protected Areas offers a prominent model: it maintains a public version for noncommercial use alongside a licensed version, accessible through the Integrated Biodiversity Assessment Tool, for commercial purposes.

The authors emphasise that initiatives like the Global Ecosystems Atlas are not intended to replace existing ecosystem information but to build on it, adding value by bringing datasets together under consistent standards. That vision depends on recognising the effort and investment behind every existing map, and on making the legal terms of reuse as clear as the data themselves. Clear data licences, the article argues, are an essential though often overlooked requirement for bottom-up global ecosystem mapping. The alternative is a world where the raw material for understanding Earth’s ecosystems exists in abundance—yet remains legally invisible to the very efforts trying to assemble it.

Subject of Research: Data licensing barriers to integrating local ecosystem datasets into global ecosystem maps

Article Title: Ambiguous data licences undermine global ecosystem mapping efforts

Article References: Buschke, F., Patterson, D., Cresswell, B. J., Gros-Dubois, N., Lloyd, T. J., Gomersall, L., Young, A. R., Gevorgyan, Y., & Murray, N. J. (2026). Ambiguous data licences undermine global ecosystem mapping efforts. PLOS Ecosystems, 1(1), e0000017. https://doi.org/10.1371/journal.pesy.0000017

Image Credits: AI Generated

DOI: 10.1371/journal.pesy.0000017

Keywords: ecosystem mapping, data licensing, Global Ecosystems Atlas, Creative Commons, open data, biodiversity, data sovereignty, copyright, Group on Earth Observations, conservation, geospatial data, PLOS Ecosystems