SAVIIA: Trusted Data Infrastructures for Field Science

What is SAVIIA?

SAVIIA (Sistema de Administración y Visualización de Información para la Investigación y Análisis) is a trusted data infrastructure for UC’s Regional Field Stations Network (RCER). It integrates scientific (sensors, surveys, imagery) and operational data (logistics, maintenance, safety) through a common governance model and hybrid local–cloud architecture, enabling reproducible pipelines, auditable analyses, and secure sharing across teams.

Why it matters

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

• Standardizing capture, metadata, and storage so datasets are FAIR (findable, accessible, interoperable, reusable).
• Bridging local constraints and cloud-scale analytics 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

• Local Orchestrator: edge services for device/sensor ingestion, validation, caching, and scheduled exports; resilient to low/unstable connectivity.
• Cloud Integration: versioned data lake + workflow engine for ETL/ELT, quality checks, and lineage; analytical sandboxes for teams.
• Shared Models & 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–result linkage; reproducible notebooks/pipelines.
• Access & Sharing: roles, project spaces, embargo/visibility policies; clear licensing for reuse.
• Safety & Ethics: consent/acceptable-use registers; minimal exposure for sensitive fields.

What we’re building (deliverables)

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

SAVIIA 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