google-transit-jjkavanagh — Source Data Validation Report

This report was generated by the Canonical GTFS Schedule validator, version 8.0.1 at 2026-06-19T11:40:56Z,
for the dataset file:///shared/google-transit-jjkavanagh_ca42b2fe.zip. No country code was provided.

Use this report alongside our documentation.

Summary

Agencies included


Feed Info


Publisher Name:
National Transport Authority
Feed Email:
apisupport@nationaltransport.ie
Feed Language:
English
Feed Start Date:
2026-06-17
Feed End Date:
2027-06-17

Files included


  1. agency.txt
  2. calendar.txt
  3. calendar_dates.txt
  4. feed_info.txt
  5. routes.txt
  6. shapes.txt
  7. stop_times.txt
  8. stops.txt
  9. translations.txt
  10. trips.txt

Counts


  • Agencies: 1
  • Blocks: 716
  • Routes: 16
  • Shapes: 143
  • Stops: 291
  • Trips: 720

Specification Compliance report

144 notices reported (0 errors, 72 warnings, 72 infos)

Notice Code Severity Total
fast_travel_between_consecutive_stops WARNING 6

fast_travel_between_consecutive_stops

A transit vehicle moves too fast between two consecutive stops.

The speed threshold depends on route type:

Route type Description Threshold, km/h
0 Light rail 100
1 Subway 150
2 Rail 500
3 Bus 150
4 Ferry 80
5 Cable tram 30
6 Aerial lift 50
7 Funicular 50
11 Trolleybus 150
12 Monorail 150
- Unknown 200

You can see more about this notice here.

tripCsvRowNumber (?) The row number of the problematic trip. tripId (?) `trip_id` of the problematic trip. routeId (?) `route_id` of the problematic trip. speedKph (?) Travel speed (km/h). distanceKm (?) Distance between stops (km). csvRowNumber1 (?) The row number of the first stop time. stopSequence1 (?) `stop_sequence` of the first stop. stopId1 (?) `stop_id` of the first stop. stopName1 (?) `stop_name` of the first stop. departureTime1 (?) `departure_time` of the first stop. csvRowNumber2 (?) The row number of the second stop time. stopSequence2 (?) `stop_sequence` of the second stop. stopId2 (?) `stop_id` of the second stop. stopName2 (?) `stop_name` of the second stop. arrivalTime2 (?) `arrival_time` of the second stop.
201 "5637_279" "293 717 m" 499.1157749987355 8.318596249978926 6452 7 "8270B3510501" "Callan" "16:40:00" 6453 8 "843000031" "Killamery" "16:40:00"
574 "5721_279" "293 717 m" 499.1157749987355 8.318596249978926 6452 7 "8270B3510501" "Callan" "16:40:00" 6453 8 "843000031" "Killamery" "16:40:00"
203 "5637_280" "293 717 m" 499.1157749987355 8.318596249978926 6512 7 "8270B3510501" "Callan" "18:40:00" 6513 8 "843000031" "Killamery" "18:40:00"
576 "5721_280" "293 717 m" 499.1157749987355 8.318596249978926 6512 7 "8270B3510501" "Callan" "18:40:00" 6513 8 "843000031" "Killamery" "18:40:00"
241 "5637_316" "293 736 m" 199.22758308591975 16.602298590493312 7557 8 "8210WB11910" "Tyndall College" "16:31:00" 7558 9 "827000010" "Paulstown M9" "16:35:00"
587 "5721_290" "293 735 m" 285.229641340397 28.522964134039697 14106 3 "8420B155481" "Nenagh" "09:45:00" 14107 4 "842000025" "Roscrea Aby St" "09:50:00"
fast_travel_between_far_stops WARNING 2

fast_travel_between_far_stops

A transit vehicle moves too fast between two far stops.

Two stops are considered "far" if they are more than 10 km apart. This normally indicates a more serious problem than too fast travel between consecutive stops.

The speed threshold depends on route type and are the same as fast_travel_between_consecutive_stops.

You can see more about this notice here.

tripCsvRowNumber (?) The row number of the problematic trip. tripId (?) `trip_id` of the problematic trip. routeId (?) `route_id` of the problematic trip. speedKph (?) Travel speed (km/h). distanceKm (?) Distance between stops (km). csvRowNumber1 (?) The row number of the first stop time. stopSequence1 (?) `stop_sequence` of the first stop. stopId1 (?) `stop_id` of the first stop. stopName1 (?) `stop_name` of the first stop. departureTime1 (?) `departure_time` of the first stop. csvRowNumber2 (?) The row number of the second stop time. stopSequence2 (?) `stop_sequence` of the second stop. stopId2 (?) `stop_id` of the second stop. stopName2 (?) `stop_name` of the second stop. arrivalTime2 (?) `arrival_time` of the second stop.
241 "5637_316" "293 736 m" 199.22758308591975 16.602298590493312 7557 8 "8210WB11910" "Tyndall College" "16:31:00" 7558 9 "827000010" "Paulstown M9" "16:35:00"
587 "5721_290" "293 735 m" 285.229641340397 28.522964134039697 14106 3 "8420B155481" "Nenagh" "09:45:00" 14107 4 "842000025" "Roscrea Aby St" "09:50:00"
mixed_case_recommended_field WARNING 64

mixed_case_recommended_field

This field has customer-facing text and should use Mixed Case (should contain upper and lower case letters).

This field contains customer-facing text and should use Mixed Case (upper and lower case letters) to ensure good readability when displayed to riders. Avoid the use of abbreviations throughout the feed (e.g. St. for Street) unless a location is called by its abbreviated name (e.g. “JFK Airport”). Abbreviations may be problematic for accessibility by screen reader software and voice user interfaces.

Good examples:
Field Text Dataset
"Schwerin, Hauptbahnhof" Verkehrsverbund Berlin-Brandenburg
"Red Hook/Atlantic Basin" NYC Ferry
"Campo Grande Norte" Carris
Bad examples:
Field Text
"GALLERIA MALL"
"3427 GG 17"
"21 Clark Rd Est"

You can see more about this notice here.

Only the first 50 of 64 affected records are displayed below.

filename (?) Name of the faulty file. fieldName (?) Name of the faulty field. fieldValue (?) Faulty value. csvRowNumber (?) The row number of the faulty record.
"trips.txt" "trip_short_name" "1.daily.12-735-y11-6" 208
"trips.txt" "trip_short_name" "2.daily.12-735-y11-6" 209
"trips.txt" "trip_short_name" "3.daily.12-735-y11-6" 210
"trips.txt" "trip_short_name" "4.daily.12-735-y11-6" 211
"trips.txt" "trip_short_name" "5.daily.12-735-y11-6" 212
"trips.txt" "trip_short_name" "14.daily.12-735-y11-" 214
"trips.txt" "trip_short_name" "7.daily.12-735-y11-6" 215
"trips.txt" "trip_short_name" "9.daily.12-735-y11-6" 216
"trips.txt" "trip_short_name" "10.daily.12-735-y11-" 217
"trips.txt" "trip_short_name" "11.daily.12-735-y11-" 218
"trips.txt" "trip_short_name" "12.daily.12-735-y11-" 219
"trips.txt" "trip_short_name" "13.daily.12-735-y11-" 220
"trips.txt" "trip_short_name" "15.daily.12-735-y11-" 221
"trips.txt" "trip_short_name" "16.daily.12-735-y11-" 222
"trips.txt" "trip_short_name" "19.daily.12-735-y11-" 225
"trips.txt" "trip_short_name" "18.daily.12-735-y11-" 226
"trips.txt" "trip_short_name" "20.daily.12-735-y11-" 227
"trips.txt" "trip_short_name" "21.daily.12-735-y11-" 228
"trips.txt" "trip_short_name" "22.daily.12-735-y11-" 229
"trips.txt" "trip_short_name" "23.daily.12-735-y11-" 230
"trips.txt" "trip_short_name" "24.daily.12-735-y11-" 231
"trips.txt" "trip_short_name" "25.daily.12-735-y11-" 232
"trips.txt" "trip_short_name" "6.MF-BH.38-874-y11-6" 264
"trips.txt" "trip_short_name" "2.MF-BH.38-874-y11-6" 265
"trips.txt" "trip_short_name" "3.MF-BH.38-874-y11-6" 266
"trips.txt" "trip_short_name" "5.MF-BH.38-874-y11-6" 268
"trips.txt" "trip_short_name" "4.MF-BH.38-874-y11-6" 269
"trips.txt" "trip_short_name" "1.M-T.43-NUM-6-y11-4" 350
"trips.txt" "trip_short_name" "2.M-T.43-NUM-6-y11-4" 353
"trips.txt" "trip_short_name" "2.M-T.43-MU1-4-y11-3" 361
"trips.txt" "trip_short_name" "3.M-T.43-MU1-4-y11-3" 362
"trips.txt" "trip_short_name" "4.M-T.43-MU1-4-y11-3" 364
"trips.txt" "trip_short_name" "5.M-T.43-MU1-4-y11-3" 365
"trips.txt" "trip_short_name" "7.M-T.43-MU1-4-y11-3" 366
"trips.txt" "trip_short_name" "6.M-T.43-MU1-4-y11-3" 368
"trips.txt" "trip_short_name" "1.daily.12-735-y11-6" 581
"trips.txt" "trip_short_name" "2.daily.12-735-y11-6" 582
"trips.txt" "trip_short_name" "3.daily.12-735-y11-6" 583
"trips.txt" "trip_short_name" "4.daily.12-735-y11-6" 584
"trips.txt" "trip_short_name" "5.daily.12-735-y11-6" 585
"trips.txt" "trip_short_name" "14.daily.12-735-y11-" 587
"trips.txt" "trip_short_name" "14.daily.12-735-y11-" 588
"trips.txt" "trip_short_name" "7.daily.12-735-y11-6" 589
"trips.txt" "trip_short_name" "9.daily.12-735-y11-6" 590
"trips.txt" "trip_short_name" "10.daily.12-735-y11-" 591
"trips.txt" "trip_short_name" "11.daily.12-735-y11-" 592
"trips.txt" "trip_short_name" "12.daily.12-735-y11-" 593
"trips.txt" "trip_short_name" "13.daily.12-735-y11-" 594
"trips.txt" "trip_short_name" "15.daily.12-735-y11-" 595
"trips.txt" "trip_short_name" "16.daily.12-735-y11-" 596
big_gap_in_service INFO 1

big_gap_in_service

A service has a gap of more than 13 days between active service dates.

You can see more about this notice here.

serviceId (?) The service_id that has the gap. gapStartDate (?) The first day of the gap. gapEndDate (?) The last day of the gap. gapDurationDays (?) The number of days in the gap.
"347" "2026-12-18" "2027-01-08" 20
service_window_outside_feed_period INFO 4

service_window_outside_feed_period

A service window is not covered by the feed's validity period.

You can see more about this notice here.

serviceId (?) The service_id whose active window extends outside the feed validity period. serviceWindowStartDate (?) The first active date of the service window. serviceWindowEndDate (?) The last active date of the service window. daysBeforeFeedStart (?) Number of days the service window extends before feed_start_date (0 if none). daysAfterFeedEnd (?) Number of days the service window extends after feed_end_date (0 if none).
"134" "2026-06-16" "2026-06-19" 1 0
"136" "2026-06-16" "2026-06-21" 1 0
"4" "2026-06-16" "2027-06-17" 1 0
"7" "2026-06-16" "2027-06-17" 1 0
unsorted_stop_times INFO 67

unsorted_stop_times

Stop times are not sorted by trip_id and stop_sequence.

'stop_times.txt' entries for a given trip are not sorted by stop_sequence, or are not contiguous in the file.

You can see more about this notice here.

Only the first 50 of 67 affected records are displayed below.

tripId (?) The faulty record's trip_id. startCsvRowNumber (?) CSV row number of the first stop_times entry for this trip. endCsvRowNumber (?) CSV row number of the last stop_times entry for this trip.
"5637_179" 3318 3430
"5637_171" 2966 3078
"5637_175" 3142 3254
"5637_297" 6817 7006
"5637_164" 2588 2698
"5637_20" 4052 4192
"5721_181" 8081 8192
"5721_186" 8277 8389
"5721_195" 9480 9599
"5721_191" 8628 9398
"5721_198" 9654 9773
"5721_125" 4140 4256
"5721_121" 3411 4079
"5721_129" 4332 4448
"5637_77" 11215 11355
"5637_79" 11405 11545
"5637_73" 10927 11067
"5721_131" 4523 4633
"5721_138" 4707 5452
"5721_101" 1559 1699
"5721_103" 1749 1889
"5721_221" 12353 12558
"5721_109" 2687 2797
"5721_226" 12639 12751
"5721_107" 2037 2637
"5637_90" 12226 12366
"5637_94" 12514 12654
"5637_96" 12704 12844
"5721_115" 3046 3162
"5721_111" 2872 2988
"5721_119" 3220 3336
"5721_20" 9838 10072
"5721_23" 12812 13027
"5721_160" 6725 6835
"5721_19" 8459 8600
"5637_34" 8160 8300
"5637_36" 8366 8506
"5637_38" 8556 8696
"5721_171" 7187 7298
"5637_30" 7079 7219
"5721_175" 7362 7926
"5637_29" 6606 6746
"5721_148" 5721 5822
"5721_142" 5538 5638
"5721_10" 639 1509
"5637_53" 9573 9713
"5637_55" 9763 9903
"5637_58" 10002 10142
"5637_51" 9383 9523
"5721_158" 6089 6654