Data Sources Behind TremorWatch
The public-data stack behind TremorWatch risk briefings.
Why public data matters
TremorWatch uses public and open signals because many supply-chain disruptions first appear as scattered evidence rather than a single clean headline. A road closure, a wildfire perimeter, a protest report, a disease notice, or a commodity-policy article may not look like a supply-chain story by itself. It becomes relevant when it overlaps with a supplier, logistics lane, port, agricultural region, mine, energy asset, or inventory plan.
Public data is not a replacement for supplier communication, carrier advisories, or internal planning systems. It is an early awareness layer. The value comes from combining different public sources, removing obvious noise, and presenting the remaining patterns in a way that operators can compare with their own exposure map.
Hazard and disaster signals
GDACS-style disaster signals are useful for rapid awareness of earthquakes, tropical cyclones, floods, and other hazards that can pressure infrastructure. These sources help identify where physical conditions may affect roads, ports, power systems, warehouses, farms, and local labor availability. TremorWatch does not assume that every disaster event creates a supply-chain disruption. Instead, it looks for severity, location, recency, and plausible connection to infrastructure or production regions.
Fire detection and weather-related sources add another layer of context. Wildfires, heat, storms, and floods can affect transport routes and worker safety even when facilities remain open. For supply-chain teams, the operational question is whether the signal sits near an exposed asset or critical lane, not whether the event is dramatic enough to dominate global news.
News, conflict, and policy signals
GDELT-style news monitoring provides breadth. It can surface unrest, policy shocks, industrial action, weather impacts, transport problems, and emerging narratives. Conflict/event datasets can add structure around protest, violence, and security conditions. These sources are valuable because logistics and procurement exposure often depends on repetition and proximity. A single article may be weak. A cluster of related signals near a corridor or industrial region can deserve attention.
Commodity context helps connect public risk to business exposure. A regional event may matter more if it occurs near a major production area, processing hub, export corridor, or substitute-constrained commodity. TremorWatch uses this context to frame why a signal might matter, while avoiding claims that public data alone can prove a specific commercial impact.
Quality controls
Public data can be duplicated, delayed, biased toward visible regions, or revised after publication. TremorWatch therefore treats source diversity, location quality, category fit, and persistence as important controls. The blog summarizes patterns and mechanisms rather than presenting raw signals as verified disruptions. Readers should validate high-priority findings with supplier outreach, carrier notices, government advisories, and their own operational data before taking action.