The rise of the nature data economy
Part 1: Foundations of data exchange
Welcome to the Nature Data Newsletter. Each month, we share insights with data providers, spatial data enthusiasts, and investors learning about nature data.
“$30,000 for soil baseline data.”
We recently brought together a group of nature professionals, where a regenerative agriculture project developer mentioned they had sold soil sample data from a baselining assessment to two remote sensing companies for $30,000 each, covering the cost of the initial baselining work. This anecdote signals a greater trend: robust in situ measurements of nature are valuable, and this value is increasingly recognised by the nature sector.
A nature data economy – i.e. the trade of nature data among willing participants – is here. This brings both exciting opportunities for the nature tech and data sector and raises questions about the readiness of the industry to deliver on the rigour, scale, ethics, and governance required.
This newsletter is the first in a new series focusing on the opportunities and challenges of the emerging nature data economy. In this first edition, we cover the foundations of data exchange. We explore why a nature data economy is needed, introduce the roles that exist within it, and touch on considerations for responsible data sharing. We then provide examples of successful data sharing as a foundation for a responsible and effective nature data economy.
This newsletter expands on previous newsletters covering specific aspects of sharing nature data, including nature data licensing and the Nature Data Sharing Initiative.
Why is a nature data economy needed?
Representing the natural world through data requires combining a mosaic of digitised information collected using different technologies and delivered in a spatially explicit, temporally explicit, and accurate way. Although large amounts of environmental data exist today, most of it is collected to order, remains siloed in private repositories, and is in technical formats unfamiliar to even advanced data scientists. Teams frequently tell us they struggle to find, access, and use the data they need.
The nature data economy bridges this gap. By incentivising the exchange of data and providing the mechanisms to do so, the nature data economy facilitates the seamless sharing of nature data between organisations in a rigorous, equitable, and useful manner.
But the sharing of nature data is still in its infancy, and multiple technical, scientific, and ethical challenges prevent it from reaching scale. At Cecil, we believe an equitable data sharing culture is the foundation for enabling the exchange of data because it standardises the language, roles, responsibilities, and practices among participants.
Roles in the nature data economy
There are three basic roles involved in the exchange of nature data:
Nature Practitioners: groups that collect nature data through their work managing and conserving natural environments (e.g. land stewards, Indigenous Peoples and Local Communities, not-for-profit organisations, researchers, and private sector entities).
Data Providers: organisations that generate and transform field observations and other measurements into meaningful variables and datasets (e.g. see our documentation).
End Users: groups that use nature data (e.g. forest managers, farmers, insurance providers, and companies preparing for like EUDR and TNFD reporting). This group also includes service providers that translate data products into insights for other End Users.
A single organisation can play all three roles: a nature conservation charity may collect in situ observations for their own use (Nature Practitioner), sell this data for use by others (Data Provider), and use additional data generated by third parties (End User).
Yet these personas typically lack the resources and incentives to fully explore their data sharing options. In situ observations collected to baseline a nature conservation project are used once then archived, while organisations building global datasets struggle to find sufficient in situ observations to train and validate models. With no common vocabulary or framework for sharing data, it is hard for different groups to align on interests, price, and mutual motivations. So data is simply not shared.
Responsible data sharing
Much like privacy concerns surrounding online personal data, the exchange of nature data raises ethical and governance considerations that the sector has yet to resolve. At the highest level, responsible nature data sharing must consider1:
Sovereignty: the rights of individuals, groups, and organisations to exercise ownership and control over data related to them, their communities, and their lands.
Permanence: the ability to control, govern, and provide access to data, knowledge, and resources in perpetuity.
Provenance: an audit trail of the data supply chain going back to the origins of the data.
Licensing: the terms for data sharing, ranging from Public to Open to bespoke options.
Sensitive Data: data with greater risk of intended or unintended harm and misuse. Examples include: Personally Identifiable Information (e.g., addresses); bioculture knowledge (e.g., traditional ecological knowledge); species location data (e.g., the location of endangered black rhinos); and commercial and competitive data.
Similar to the challenge above, the lack of a common understanding hinders this process.
Data sharing initiatives in practice
Despite the challenges ahead, initiatives are now emerging to align language and standards across the ecosystem, showcase what successful nature data sharing looks like, and call the sector to action in the pursuit of a mature nature data economy. Some examples are:
The CARE Principles for Indigenous Data Governance (Collective Benefit, Authority to Control, Responsibility, and Ethics) support Indigenous Peoples’ self-determination, right to resiliency development, and the right to control access to, use of, and benefit from research data.
The Enhanced Rock Weathering (ERW) Data Quarry is one of the first systems of its kind to proactively share commercial data for the benefit of scientific learning in the Carbon Dioxide Removal (CDR) space.
The FAIR data principles (Findable, Accessible, Interoperable, and Reusable) provide a framework for making research data more discoverable and usable by ensuring data can be easily located, accessed, and reused across different systems and contexts.
Finally, Cecil, alongside a group of 16 cross-sector organisations, recently launched the Nature Data Sharing Initiative (NDSI). The NDSI provides guidance notes, a data sharing worksheet, and a template agreement to enable effective and equitable sharing of Nature Practitioners' field data.
The rise of the nature data economy
At Cecil, we believe that a responsible, equitable, and effective nature data economy is here – and is essential for the planet. The sharing of existing siloed data would help fill critical gaps, like tracking the one in six IUCN-listed species that lack sufficient data. New pathways to finance data generation by Indigenous Peoples and Local Communities would create best-in-class data and well-paying jobs that require their intimate knowledge of the land. Innovations in science and tech would bloom alongside Nature Practitioners, being fed by both the new data and the economy.
Perhaps most importantly, the rise of a mature nature data economy could be just in time to give us the depth of information we need to act – to work alongside nature effectively to mitigate the worst effects of the global polycrisis.
This newsletter is created by Cecil. We have some exciting announcements coming soon about our data infrastructure platform, stay tuned!
Here are our recent updates:
We announced our destination partnership with Felt
We announced data partnerships with Impact Observatory and Space Intelligence
Two Joint Research Council (JRC) datasets are now available on Cecil: Global Forest Cover 2020 (v2) and Global Forest Type 2020 (v0).
These principles are discussed in more detail in the Nature Data Sharing Initiative