The STRATA Substrate

@techreport{hamilton2026strata, author = {Hamilton, Michael P., Ph.D.}, title = {The STRATA Substrate}, institution = {Canemah Nature Laboratory}, year = {2026}, number = {CNL-TN-2026-046}, month = {april}, url = {https://canemah.org/archive/document.php?id=CNL-TN-2026-046}, abstract = {STRATA 2.0's Observatory and Intelligence dashboards currently generate all sensor summaries, narrative text, and ecological context on demand -- executing 30-50 database queries per page load, discarding the results when the page closes, and rebuilding everything from scratch on the next request. The Chat interface compounds this by dumping the entire sensor state into an LLM system prompt as unstructured text. This pull-on-demand architecture works at development scale but cannot sustain real-time ecological awareness, efficient AI conversations, or the always-on pattern detection required by SOMA. This technical note specifies the **Substrate** -- a continuously maintained ecological context layer that keeps a current, structured, curated picture of the world ready to serve. Modeled on the same launchd collector pattern that already gathers raw sensor data on Galatea, the Substrate operates as a second-tier process: collectors deposit raw readings into the `macroscope` database; the Substrate reads those readings and maintains derived intelligence state. Observatory, Intelligence, Chat, and SOMA become consumers of maintained state rather than independent query engines. The Substrate maintains three layers of context: Place Identity (from MNG's ecological address model), Sensor State (per-platform summaries refreshed on natural data rhythms), and Ecological Frame (species detection states, phenological context, seasonal norms). Together these layers provide the structured, curated context that STRATA IQ requires for place-based ecological intelligence. The architecture positions the Substrate as the foundation for convergence between MNG's spatial identity framework and STRATA's temporal intelligence framework, and as the sensory input layer for SOMA's pattern detection meshes.} }