SAVIIA and ECHO: Trusted Data Infrastructures for Field Science

What are SAVIIA and ECHO?

SAVIIA (Sistema de Administración y Visualización de Información para la Investigación y Análisis) and ECHO (Edge Computing and Hardware Orchestration) form a trusted data infrastructure ecosystem for UC’s Regional Field Stations Network (RCER).

ECHO acts as the local edge orchestrator, capturing and validating data on-site. SAVIIA operates as the online platform, governing and integrating scientific (sensors, surveys, imagery) and operational data (logistics, maintenance, safety). Together, this hybrid local and cloud architecture enables reproducible pipelines, auditable analyses, and secure sharing across teams.

Why it matters

Field research suffers from fragmented sources, intermittent connectivity, and uneven practices. This ecosystem addresses this by:

• Standardizing capture, metadata, and storage so datasets are FAIR (findable, accessible, interoperable, reusable).
• Bridging local constraints through ECHO and cloud-scale analytics through SAVIIA to support continuous, trustworthy workflows.
• Connecting scientific and operational streams to improve data quality, reproducibility, and decision-making in stations and partner projects.

Architecture at a glance

• ECHO (Local Orchestrator): edge services for device and sensor ingestion, validation, caching, and scheduled exports; resilient to low or unstable connectivity.
• SAVIIA (Cloud Integration): versioned data lake and workflow engine for ETL and ELT processes, quality checks, and lineage; analytical sandboxes for teams.
• Shared Models and Views: curated datasets, dashboards, and APIs for research, station operations, and stakeholders.

Data governance

SAVIIA implements lightweight, enforceable rules centered on:

• Quality: schema checks, unit validation, completeness, timeliness SLAs.
• Traceability: dataset identifiers, provenance, code, data, and result linkage; reproducible notebooks and pipelines.
• Access and Sharing: roles, project spaces, embargo and visibility policies; clear licensing for reuse.
• Safety and Ethics: consent and acceptable use registers; minimal exposure for sensitive fields.

What we are building (deliverables)

• ECHO: deployable edge stack (ingestion, validation, scheduling, secure sync).
• SAVIIA: data lake and workflow templates; metadata registry; dataset catalogue.
• Operations Kit: runbooks, templates, QA playbooks, and hello station examples.
• Visualization and APIs: curated views and endpoints for research and station management.
• Training and Onboarding: short guides for station staff and researchers; governance checklists.

The SAVIIA and ECHO ecosystem advances the state of practice by operationalizing governance and linking edge capture with cloud analytics, so field science can move from isolated datasets to reliable, decision-ready evidence at scale.

Project Team:

• Director: Rodrigo A. Carrasco
• Students: Sol Covacich, Pedro Zavala, Catalina Ortega