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Observations & Indicators

The spatial backbone provides structure, but two external pathways add data that authoritative agency datasets alone cannot provide: field observations from community researchers, and sub-county statistical indicators that refine federal baselines.

Observations: Research Commons

Geocoded environmental samples — water quality, soil tests, species surveys — are contributed through the Research Commons, a public GitHub repository with an open review workflow.

How it works:

  1. A contributor forks the research repository and adds their dataset (CSV or GeoJSON) with a metadata file describing the contribution type, topic, and spatial extent.
  2. A pull request triggers automated validation — schema checks, coordinate verification, and metadata completeness.
  3. On merge, the ingestion pipeline adds the contribution and its records to the platform, links them to the appropriate SDG goals, and resolves each record to the backbone through spatial indexing.

This is the only SDG measurement pathway backed by structured relationships rather than editorial labels. When a research record says it measures SDG 6 (Clean Water), that claim is grounded in a provenance chain: the contribution, the records it contains, the environment sites those records observed, and the moku districts those sites belong to.

Contribution types:

| Type | Purpose | Example | |------------------|--------------------------------------------------|--------------------------------| | Observation | Field-collected environmental samples | Water quality at Keehi Lagoon | | Indicator | Statistical measures at sub-county resolution | Food access by moku district | | Spatial overlay | Boundary or classification layers | Monitoring site network |

Topic areas: Land & environment, water, biodiversity, agriculture, coastal, climate, forestry, food safety, infrastructure, demographics, community wellbeing.

Indicators: Refining Federal Baselines

The Island Baselines page shows county-level statistics sourced from federal data — demographics, employment, food access, energy, and other measures organized by SDG pillar. These federal baselines provide useful context but are limited to county resolution, which in Hawaii means island-level at best.

Indicator contributions through the Research Commons link community-collected sub-county data to the corresponding federal variables. This bridges the gap between county resolution and moku district resolution, giving subscribers a more granular picture of conditions in their area.

How Both Pathways Resolve to the Backbone

Neither observations nor indicators modify the backbone. Both follow the same spatial resolution process:

  1. Each record's coordinates are converted to a grid cell index.
  2. The grid cell is matched to a backbone cell.
  3. The backbone cell links the record to its containing moku district and all overlapping zones.

This means a water quality sample taken at a specific GPS coordinate automatically inherits the full spatial context — which moku it belongs to, whether it falls within a conservation reserve or agricultural land, and which schools or infrastructure are nearby. The researcher provides coordinates; the backbone provides context.

Environment Monitoring Sites

Observation records link to environment sites — specific monitoring locations such as water sampling points, soil test stations, and air quality monitors. These sites are grouped into monitoring networks, which aggregate multiple locations into community-managed clusters.

The SDG measurement chain runs through these sites:

SDG Goal ← measured by ← Research Contribution → contains → Research Record → observed at → Environment Site → located in → Grid Cell → within → Moku

From any SDG goal, you can trace which contributions measure it, which records they contain, where those records were observed, and which moku district contains those observation sites.