Beyond Public Transport – What Happens When You Combine the Mobility Database with Fintraffic’s Open Data Ecosystem?

In the first article of this series, I introduced Fintraffic’s Mobility Database and explained how it transforms fragmented public transport information into a single, standardised data foundation. But the Mobility Database is only one part of a much larger ecosystem.

In this article, I’ll introduce Fintraffic’s most important data services, explore practical examples of how they can complement one another, and discuss what it actually takes to build services on top of them.

A broader ecosystem than many realise

The Mobility Database forms an important foundation, but it is only one component of Finland’s digital transport infrastructure.

Together, Fintraffic’s services create an exceptionally comprehensive ecosystem.

Digitraffic provides open data for road, rail and maritime transport. Road traffic data includes traffic flow, road weather, weather camera images, incident information and traffic volumes collected from hundreds of automatic monitoring stations. Rail traffic data covers timetables, real-time train locations, operational status and train compositions, while maritime data includes AIS vessel positions and port call information.

Digitransit offers Finland’s nationwide journey planning platform. Built on OpenStreetMap and the Pelias geocoding engine, it already utilises Mobility Database data to provide nationwide route planning and real-time passenger information through modern GraphQL interfaces.

FINAP, Finland’s National Access Point, acts as the national catalogue for mobility services and transport data providers. It enables organisations to publish descriptions of their transport APIs and supports the development of integrated mobility services.

PETI, the national stop and accessibility database, maintains harmonised information about public transport stops, terminals and other interchange points. Every stop receives a unique national identifier together with detailed accessibility information.

LIIPI, the park-and-ride information service, provides nationwide information about park-and-ride facilities, including locations, capacity, pricing and operators. During 2026 its data will gradually be integrated into PETI.

Taken together, these services form one of Europe’s most comprehensive open transport data ecosystems.

Four practical examples

Each individual service solves a specific problem.

Their real value emerges when they are used together.

The following examples are not official Fintraffic roadmaps. They represent practical ideas that become possible because the underlying data already exists.

1. Real-time comparison between public transport and private cars

By combining timetable and real-time information from the Mobility Database with Digitraffic’s road traffic and congestion data, a journey planner could compare different transport modes in real time.

Instead of simply recommending public transport, the service could answer a more practical question:

“Which option is actually faster right now?”

During rush hour—or in severe winter weather—the answer may surprise many travellers.

2. Smarter transfers during train delays

Train delays rarely affect only train passengers.

When rail data from Digitraffic is combined with bus and tram information from the Mobility Database, it becomes possible to predict how delays propagate through an entire journey.

Instead of discovering that a connecting bus has already departed, passengers could receive alternative travel options before arriving at the station.

This would be particularly valuable for longer multimodal journeys involving several transfers.

3. Truly accessible door-to-door journeys

Accessibility is about much more than low-floor buses.

Combining route and timetable information with PETI’s accessibility data and LIIPI’s park-and-ride information makes it possible to plan journeys that consider accessibility at every stage.

For example, a wheelchair user could receive a journey where every stop, transfer point and vehicle has been verified as accessible.

This illustrates how combining datasets can create benefits that are not merely technical, but socially significant.

4. Comparing transport services—not just travel times

Journey planners typically compare routes by travel time.

But travellers often care about much more.

How frequently does a service operate?

How reliable is the operator?

Can tickets be purchased digitally?

By combining Mobility Database information with metadata published through FINAP, future services could compare transport options based on overall service quality rather than travel time alone.

The same information would also provide transport authorities with valuable insight into network performance and service levels.

Integration still requires engineering

The opportunities are exciting.

That does not mean integration happens automatically.

Different services expose their data through different technologies. Digitraffic primarily offers REST APIs returning JSON and GeoJSON. Digitransit uses GraphQL, while the Mobility Database provides both downloadable datasets and API-based access.

Developers therefore need to understand several integration approaches and combine them into a coherent solution.

Static and real-time datasets also operate on different update cycles. Timetables change relatively infrequently, while real-time vehicle positions may update every few seconds. Synchronising these different temporal perspectives requires careful engineering.

Data quality also varies between operators. Accessibility information may be incomplete in some regions, while the accuracy of real-time predictions naturally depends on the quality of each operator’s own systems.

Even so, today’s starting point is dramatically better than it used to be.

The Mobility Database removes the largest obstacle by providing harmonised, validated transport data. Combined with Fintraffic’s well-documented APIs, developers can focus on building services instead of cleaning data.

The building blocks already exist

Perhaps the most interesting observation is this:

Most of these ideas do not require new technology.

The data already exists.

The APIs already exist.

The standards already exist.

What is still needed are organisations willing to combine these building blocks into new digital mobility services.

The Mobility Database serves as the logical starting point because it establishes a common language for public transport information. Once that foundation exists, enriching it with road traffic, accessibility, weather or maritime data becomes significantly easier.

In the final article of this series, we’ll take one step further.

What happens when artificial intelligence is added to this ecosystem? Can AI identify traffic patterns, predict disruptions and help passengers make better travel decisions?

That is where the next chapter begins.