Data vs. Information

What are they 

Data are raw observations (or data points) captured by monitoring systems. Information is data that has been processed, contextualised and presented so that engineers and operators can act on it.

Data in detail

In a rail context, data are uninterpreted observations. They might include thousands of accelerometer readings per second from an onboard sensor, or temperature values from a hot axle-box detector. Each value is precise but, on its own, tells you little about asset condition or risk.

Modern systems generate billions of data points every day from sensors mounted on trains and infrastructure, covering parameters such as longitudinal level, alignment, twist, and wheel-rail forces (e.g. AIVR Geometry). This scale makes manual interpretation impossible and demands automated processing.

Refined data: information

Converting data into information typically involves filtering noise, aggregating over distance or time, applying thresholds and comparing against standards such as EN 13848 geometry limits, which defines acceptable track geometry quality on European railways.

For example, millions of track geometry samples may be reduced to an exception list highlighting locations where twist exceeds an intervention limit, each with a GPS position, severity index and trend over successive runs.

Similarly, real‑time vibration data from distributed sensing can be transformed into alarms indicating a likely rail break or ballast voiding at a specific chainage, with confidence levels and recommended actions.

Intelligent infrastructure programmes integrate multiple monitoring feeds (fixed detectors, embedded sensors or train‑borne systems) into dashboards that show asset health, predicted failure dates and the operational impact of different intervention strategies. Information supports condition‑based and predictive maintenance, reduces manual site inspections and improves safety and availability by enabling targeted, timely interventions.