JNCTION Archive

Helping to understand historic train movements and performance through data

Analytics challenges

The analytics landscape faces significant hurdles due to the limitations of many industry-standard historic data sources. These data sets are often incomplete, biased, or prone to human-input errors, undermining their reliability. Additionally, historic data are frequently pre-aggregated, restricting the depth of analysis analysts can perform. Many standard data feeds lack precise time specificity, recording events only to the nearest minute, and geographical accuracy is often insufficient. Data availability is further constrained by limited windows and restricted historic data access, particularly for certain industry players, such as operators.

The tool addresses these challenges by:

High-Quality, Unbiased Data

Complete train movements data with no human input, ensuring high data quality and no bias. Can be used to build AI and ML solutions.

Granular Train Movement Data

Data available for each train movement event, with multiple between each station stop.

Precise Timing

Events specified at to-the-second timing.

Detailed Geographic Data

Events specified at berth step level geography.

Historical Data Access

Multiple years of historic data available.

Streamlined Data Access

Circumvent endless data requests by getting data directly.

Benefits

Data-driven insights 

More specific time and geography allows analysts to look ‘under the hood’ and understand root causes of sub-threshold delay  

Better performance 

Railway planners and operators can identify opportunities in their timetables and station operations. 

Unlock AI  

With complete and unbiased data you can train your own predictive machine learning models to learn accurately from historic events 

More in Control 

Railway operators can directly access large volumes of data without needing data requests to partner organisations 

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