Spacetime

Nature doesn’t stand still. Spacetime is Lemu’s nature data protocol that organises environmental observations, models, and indicators so they stay consistent, comparable, and decision-ready—no matter the source or scale.

Spacetime defines how complex, linked, interdependent nature data is represented, related, and versioned over space and time. It lets organisations combine field data, remote sensing, models, and records into one coherent fabric—ready for analysis, governance, and sharing.

A data protocol for ecological intelligence

There is a place in southern Chile where the arrayán trees grow so close to the river that their roots drink from two worlds at once — the soil and the current. The Mapuche call the arrayán quetri and consider it a guardian. A botanist calls it Luma apiculata and measures its leaf area index. A satellite 500 kilometers above sees neither the name nor the sacredness — it sees a reflectance signature at 842 nanometers that says: something is alive here, and it is changing.

Three ways of knowing the same tree. Three systems of notation. Three levels of trust. And until now, no common language to hold all three in the same sentence without losing any of them.

Spacetime is that language.

It is a protocol for recording what happens on Earth — where, when, and how certain we are. A single bee counted on a Tuesday morning and a continent's carbon flux measured across a decade are both valid Spacetime records. They share the same grammar. They differ in scale, in confidence, in what they claim to know — and that difference is explicit, not hidden.

The architecture is simple enough to state in one breath: every observation carries a space (where, at what resolution, how precisely), a time (when, how precisely), a payload (what was observed, in what units, by what method), and a provenance (how it was produced, from what sources, through what process). Raw field data, derived indicators, and institutional claims all use the same envelope — but they declare their epistemic level honestly. A camera trap photograph and a TNFD disclosure metric are never confused, because they never pretend to be the same kind of knowledge.

This matters because the planet's next decade will be shaped by decisions that depend on ecological data — and most of that data does not yet exist in a form that machines can reason about, that regulators can audit, or that indigenous communities can recognize their knowledge within. SpaceTime is built so that all three can happen simultaneously, without any of them compromising the others.

The protocol is fractal: a single tree nests inside a forest stand, inside a watershed, inside an ecoregion — and the lineage is traversable all the way down. It is event-sourced: corrections are new records, not overwrites, because the history of what we thought we knew is as valuable as what we know now. It wraps Darwin Core, Humboldt Extension, CF Standard Names, and IUCN vocabularies inside a unified spatiotemporal envelope — not replacing them, but giving them a shared coordinate system.

Spacetime is how we begin to describe it.

Key Highlights

• 4D by design: every record is anchored in location (x, y, z) and timestamp/period (t).
• Typed & linked: observations, features, events, habitats, and indicators are first-class, linked objects.
• Versioned & auditable: provenance, lineage, and change history are preserved end-to-end.
• Interoperable: aligns with open geospatial and temporal data conventions for smooth exchange.

{x, y, z, t}

4D NATURE DATA PROTOCOL

Why it matters

• Comparability: like-for-like across sites, projects, and years—turns scattered datasets into a continuous story.
• Scientific integrity: explicit units, methods, and uncertainty keep insights honest and reproducible.
• Operational speed: one schema across teams, tools, and vendors reduces friction and rework.
• Governance & trust: traceable data builds confidence with regulators, investors, and communities.
• Actionable insight: makes complex ecology legible to business systems—so decisions include nature.

Key capabilities

• Spatiotemporal primitives – points, lines, polygons, rasters, volumes; instants and intervals.
• Event & state modelling – distinguish conditions (state) from changes (events) and link causes.
• Provenance & lineage – source, method, model version, and processing steps carried with data.
• Quality & uncertainty – confidence scores, detection limits, gaps clearly encoded.
• Indicators as first-class – pre-defined structures for nature metrics so results are portable.
• Permissions & sharing – fine-grained access so teams can publish openly or keep private.
• Standards friendly – plays well with established geospatial/temporal conventions and APIs.

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