High-quality data for a seamless passenger experience
From real-time journey updates to smarter transport policy, Ito ensures the data behind public transit systems is accurate, timely, and trusted.
The backbone of modern mobility
Data increasingly underpins every aspect of public and shared transportation—from journey planning and ticketing to operational analysis and national policy.
But poor data = poor experience. Whether it’s misleading arrival times or flawed performance analysis, the consequences can be widespread and damaging.
High-quality data isn’t just beneficial-it’s essential.
Ito’s forensic approach to data quality
We run 130+ checks on every dataset — because every detail matters.
At Ito, we’ve spent years supporting global journey planners, MaaS providers, and custom transit apps. Our testing framework is informed by the needs of both planners and passengers.
We focus on five critical dimensions:
The five data quality dimensions:
Availability
Is the data easy to find and access?
Accuracy
Does the data reflect real-world conditions?
Responsiveness
Is the data delivered at the right time?
Completeness
Is the data whole and within expected standards?
Consistency
Does the data align across formats and sources?
Beyond automation: Human-informed quality control
While many tests focus on technical integrity, the majority are passenger-centric—aimed at ensuring a seamless, reliable experience. For example, a single bus stop needs over 10 unique data points to function correctly.
Our in-house data team:
Runs prioritised quality tests based on user impact
Collaborates with data providers to implement improvements
Can intervene directly in our systems while source fixes are in progress
Automatically reverts to source data when fixes are confirmed
This agile model ensures the best data is always downstream—without compromise.
Shaping global
standards in transit
data
Ito contributes to the evolution of both GTFS (North America) and CEN (Europe) transit standards. This positions us at the forefront of transport data quality and fuels our continuous innovation—especially as new datasets and AI applications emerge.