Data Feeds

This section describes the numerous data feeds that acumen consumes.

POINTA CIF

A train service database (TSDB) is maintained within acumen; the TSDB is created from a full extract CIF file at initialisation, and kept up to date by consumption of an incremental update which takes place each morning at 01:00 Hrs.

Both the full CIF and incremental update CIF files are obtained via SFTP directly from Network Rail PPTE (Pre-production Test Environment).

As published by ITPS, the CIF contains limited train association data (AA records) however, prior to publication to PPTE for consumption, the CIF is parsed by a service known as POINTA.

POINTA (Platform Occupancy INference of Train Associations) is a service which infers associations and enriches the CIF file prior to publication. POINTA is considered to be an enhancement on the association parsing and inference undertaken by WACI (or similar) components common at many locations.

VSTP

To complement the TSDB described above, acumen subscribes to and consumes VSTP schedules which are published over the Network Rail TD.net feed; acumen receives these messages regardless of the VSTP source (i.e. TRUST, TDA or Integrale).

Train Journey Modification (TJM) Messages

There are a sub-set of messages that acumen consumes from TD.net that maintain the planned intent of activated services - informed by transactions commited within TRUST:

• Full cancellation;
• Start Forward (change of origin);
• Terminate Short;
• Cancellation reinstatement;
• Change of Location;
• Change of identity.

Each message is received and processed by acumen and where a service is subject to forecasting, the forecast reflects the modification.

Train Movement Reports

As a train service proceeds on its journey, train movement reports are published via TD.net; acumen subscribes to and consumes this feed; the train movement report is primarily used to inform the forecast - allowing acumen to update the forecast to reflect actual (known) train running.

TD: C-Class Data

Where configured to do so, berth level TD (train describer) data is published via TD.net; acumen currently consumes this data for various reasons:

• Inform the approach berth notification service;
• Feed the TD map service.

TD: S-Class Data

As with C-Class Data described above, acumen consumes the counterpart S-Class data. This data feed relates to Signalling Equipment state; acumen consumes this data and extrapolates:

• Signal state - on or off;
• Route state - set or not set;
• Train Ready To Start (TRTS) - operated or clear.

This data is utilised primarily to feed the TD maps available within acumen.

Darwin

Darwin is the GB rail industry’s official train running information engine, providing real-time arrival and departure predictions, platform numbers, delay estimates, schedule changes and cancellations.

There are numerous available public feeds that National Rail Enquiries make available; acumen subscribes to and consumes the following:

• Station Messages;
• Knowledge Base - Real Time Incident feed;
• Darwin TS (Train Status).

Currently, acumen extrapolates train length and platform changes from the Darwin TS feed - this data is used to inform service forecasting.

PPM - Public Performance Measure

Twice a minute, TD.net publishes PPM data; acumen consumes this data and provides the current PPM statistics in the Home > PPM tab.

TSR - Temporary Speed Restriction Data

Each Friday at 07:00 Hrs, TD.net publishes the current TSR data as published in the Weekly Operating Notice. Users can view this information in the Home > Temporary Speed Restriction (TSR) tab.

Reference Data

Other sources of static data are utilised by acumen - these are available from various sources and are updated periodically:

• B-plan - a representation of railway data in a structured file format, used mainly to create a location directory, parse timing and route links and to provide full textual references to railway data within the application.
• SMART database - an xml file that details the mapping between signal berths, SMART and TIPLOC.