indianrailways — Source Data Validation Report

This report was generated by the Canonical GTFS Schedule validator, version 7.1.0 at 2026-06-06T06:46:17Z,
for the dataset file:///shared/indianrailways_d2f553a6.zip. No country code was provided.

Use this report alongside our documentation.

A new version of the Canonical GTFS Schedule validator is available! Please update to get the latest/best validation results.

Summary

Agencies included


Feed Info


Publisher Name:
P. Radha Krishna
Feed Email:
pradha.krishna.cse17@itbhu.ac.in
Feed Language:
English
Feed Start Date:
2026-05-30
Feed End Date:
2026-06-30

Files included


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

Counts


  • Agencies: 1
  • Blocks: 0
  • Routes: 10074
  • Shapes: 10074
  • Stops: 8565
  • Trips: 10074

Specification Compliance report

18340 notices reported (2 errors, 18334 warnings, 4 infos)

Notice Code Severity Total
start_and_end_range_out_of_order ERROR 2

start_and_end_range_out_of_order

Two date or time fields are out of order.

Date or time fields have been found out of order in calendar.txt, feed_info.txt and stop_times.txt.

You can see more about this notice here.

filename (?) The name of the faulty file. csvRowNumber (?) The row number of the faulty record. entityId (?) The faulty service id. startFieldName (?) The start value's field name. startValue (?) The start value. endFieldName (?) The end value's field name. endValue (?) The end value.
"calendar.txt" 986 "Fri_20991231-20270530" "start_date" "20991231" "end_date" "20270530"
"calendar.txt" 1111 "Sun_20991201-20270530" "start_date" "20991201" "end_date" "20270530"
expired_calendar WARNING 314

expired_calendar

Dataset should not contain date ranges for services that have already expired.

This warning takes into account the calendar_dates.txt file as well as the calendar.txt file.

You can see more about this notice here.

Only the first 50 of 314 affected records are displayed below.

csvRowNumber (?) The row of the faulty record. serviceId (?) The service id of the faulty record.
2 "Mon-Tue-Wed-Thu-Fri-Sat-Sun_20260323-20260331"
5 "Mon-Tue-Wed-Thu-Fri-Sat-Sun_20260126-20260519"
7 "Mon-Tue-Wed-Thu-Fri-Sat-Sun_20260228-20260531"
8 "Mon-Tue-Wed-Thu-Fri-Sat-Sun_20260307-20260402"
15 "Mon-Tue-Wed-Thu-Fri-Sat-Sun_20260319-20260402"
18 "Mon-Tue-Wed-Thu-Fri-Sat-Sun_20260415-20260507"
23 "Mon-Tue-Wed-Thu-Fri-Sat-Sun_20260225-20260430"
28 "Mon-Tue-Wed-Thu-Fri-Sat-Sun_20260301-20260331"
29 "Mon-Tue-Wed-Thu-Fri-Sat-Sun_20260101-20260519"
32 "Mon-Tue-Wed-Thu-Fri-Sat-Sun_20260514-20260531"
35 "Mon-Tue-Wed-Thu-Fri-Sat-Sun_20260101-20260502"
36 "Mon-Tue-Wed-Thu-Fri-Sat-Sun_20260104-20260413"
37 "Mon-Tue-Wed-Thu-Fri-Sat-Sun_20260312-20260331"
38 "Mon-Tue-Wed-Thu-Fri-Sat-Sun_20260306-20260406"
44 "Mon-Tue-Wed-Thu-Fri-Sat-Sun_20260216-20260516"
47 "Mon-Tue-Wed-Thu-Fri-Sat-Sun_20260316-20260331"
49 "Mon-Tue-Wed-Thu-Fri-Sat-Sun_20260311-20260331"
50 "Mon-Tue-Wed-Thu-Fri-Sat-Sun_20260101-20260331"
53 "Mon-Tue-Wed-Thu-Fri-Sat-Sun_20260312-20260515"
55 "Mon-Tue-Wed-Thu-Fri-Sat-Sun_20260101-20260405"
60 "Mon-Tue-Wed-Thu-Fri-Sat-Sun_20260101-20260520"
65 "Mon-Tue-Wed-Thu-Fri-Sat-Sun_20260326-20260413"
72 "Mon-Tue-Wed-Thu-Fri-Sat-Sun_20260320-20260331"
73 "Mon-Tue-Wed-Thu-Fri-Sat-Sun_20260226-20260428"
80 "Mon-Tue-Wed-Thu-Fri-Sat-Sun_20260203-20260519"
85 "Mon-Tue-Wed-Thu-Fri-Sat-Sun_20260320-20260503"
92 "Mon-Tue-Wed-Thu-Fri-Sat-Sun_20260302-20260401"
94 "Mon-Tue-Wed-Thu-Fri-Sat-Sun_20260207-20260405"
97 "Mon-Tue-Wed-Thu-Fri-Sat-Sun_20260317-20260330"
101 "Mon-Tue-Wed-Thu-Fri-Sat-Sun_20260126-20260331"
103 "Mon-Tue-Wed-Thu-Fri-Sat-Sun_20260305-20260331"
105 "Mon-Tue-Wed-Thu-Fri-Sat-Sun_20260328-20260331"
110 "Mon-Tue-Wed-Thu-Fri-Sat-Sun_20260310-20260331"
113 "Mon-Tue-Wed-Thu-Fri-Sat-Sun_20260306-20260331"
118 "Mon-Tue-Wed-Thu-Fri-Sat-Sun_20260101-20260412"
121 "Mon-Tue-Wed-Thu-Fri-Sat-Sun_20260324-20260331"
125 "Mon-Tue-Wed-Thu-Fri-Sat-Sun_20260316-20260330"
126 "Mon-Tue-Wed-Thu-Fri-Sat-Sun_20260101-20260503"
129 "Mon-Tue-Wed-Thu-Fri-Sat-Sun_20260318-20260331"
131 "Mon-Tue-Wed-Thu-Fri-Sat-Sun_20260303-20260405"
134 "Mon-Tue-Wed-Thu-Fri-Sat-Sun_20260327-20260331"
135 "Mon-Tue-Wed-Thu-Fri-Sat-Sun_20260317-20260331"
142 "Mon-Tue-Wed-Thu-Fri-Sat-Sun_20260319-20260331"
143 "Mon-Tue-Wed-Thu-Fri-Sat-Sun_20260101-20260413"
144 "Mon-Tue-Wed-Thu-Fri-Sat-Sun_20260319-20260401"
146 "Mon-Tue-Wed-Thu-Fri-Sat-Sun_20260307-20260331"
147 "Mon-Tue-Wed-Thu-Fri-Sat-Sun_20260301-20260330"
155 "Mon-Tue-Wed-Thu-Fri-Sat-Sun_20260414-20260507"
156 "Mon-Tue-Wed-Thu-Fri-Sat-Sun_20260101-20260531"
157 "Mon-Tue-Wed-Thu-Fri-Sat-Sun_20260413-20260507"
fast_travel_between_consecutive_stops WARNING 4

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.
9310 "75202" "75202" 593.9910774315391 9.899851290525651 187635 17 "PPV" "PRATAPGANJ" "09:55:00" 187636 18 "LLP" "LALITGRAM" "09:55:00"
6768 "54086" "54086" 748.5700445534726 12.476167409224542 144463 1 "STD" "SATROD" "14:20:00" 144464 2 "HNS" "HANSI" "14:20:00"
8751 "68118" "68118" 841.8148718353057 7.015123931960881 179194 10 "GHDA" "GHOLBAGDA" "12:54:00" 179195 11 "HEN" "HENRIA PH" "12:54:30"
6916 "54781" "54781" 508.8824885316081 8.481374808860135 147434 24 "MAYR" "MAYAR" "21:22:00" 147435 25 "HNS" "HANSI" "21:22:00"
fast_travel_between_far_stops WARNING 1

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.
6768 "54086" "54086" 748.5700445534726 12.476167409224542 144463 1 "STD" "SATROD" "14:20:00" 144464 2 "HNS" "HANSI" "14:20:00"
feed_expiration_date30_days WARNING 1

feed_expiration_date30_days

Dataset should cover at least the next 30 days of service.

At any time, the GTFS dataset should cover at least the next 30 days of service, and ideally for as long as the operator is confident that the schedule will continue to be operated.

You can see more about this notice here.

csvRowNumber (?) The row number of the faulty record. currentDate (?) Current date (YYYYMMDD format). feedEndDate (?) Feed end date (YYYYMMDD format). suggestedExpirationDate (?) Suggested expiration date (YYYYMMDD format).
2 "20260606" "20260630" "20260706"
mixed_case_recommended_field WARNING 18014

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 18014 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.
"stops.txt" "stop_name" "AMBIKA BHAWANI HALT" 3
"stops.txt" "stop_name" "AMB ANDAURA" 4
"stops.txt" "stop_name" "AMBLI ROAD" 16
"stops.txt" "stop_name" "AMBARI FALAKATA" 18
"stops.txt" "stop_name" "ARABAGATTA HALT" 20
"stops.txt" "stop_name" "AMBIKA KALNA" 23
"stops.txt" "stop_name" "ASTHAL BOHAR" 26
"stops.txt" "stop_name" "ABU ROAD" 28
"stops.txt" "stop_name" "AMBARI RICHHAVI" 29
"stops.txt" "stop_name" "AZIMGANJ CITY" 41
"stops.txt" "stop_name" "ACHUARA HALT" 45
"stops.txt" "stop_name" "ADAS ROAD" 48
"stops.txt" "stop_name" "ADARI ROAD" 49
"stops.txt" "stop_name" "AHMEDABAD JN" 53
"stops.txt" "stop_name" "MANDI ADAMPUR" 57
"stops.txt" "stop_name" "ADI SAPTAGRAM" 59
"stops.txt" "stop_name" "ANANT PAITH" 66
"stops.txt" "stop_name" "ANEKAL ROAD" 68
"stops.txt" "stop_name" "AGRA FORT" 71
"stops.txt" "stop_name" "AGRA CITY" 75
"stops.txt" "stop_name" "AGRA CANTT JN." 79
"stops.txt" "stop_name" "AGARAM SIBBANDI" 83
"stops.txt" "stop_name" "AGORI KHAS" 93
"stops.txt" "stop_name" "ACHHNERA JN" 95
"stops.txt" "stop_name" "ADARSH MANPUR" 102
"stops.txt" "stop_name" "AHERA HALT" 105
"stops.txt" "stop_name" "ALAWALPUR I PUR" 112
"stops.txt" "stop_name" "AJMER JN" 113
"stops.txt" "stop_name" "ATTIPATTU PUDU NAGAR.H" 116
"stops.txt" "stop_name" "ANJHI SHAHABAD" 122
"stops.txt" "stop_name" "ARAKKONAM JN." 124
"stops.txt" "stop_name" "AJITGILL MATTA" 132
"stops.txt" "stop_name" "AKOLA JN." 135
"stops.txt" "stop_name" "AKAIPUR HALT" 139
"stops.txt" "stop_name" "ADHYATMIK NAGAR" 145
"stops.txt" "stop_name" "AKALKOT ROAD" 146
"stops.txt" "stop_name" "ANKLESHWAR JN" 154
"stops.txt" "stop_name" "ALIA BADA" 163
"stops.txt" "stop_name" "ALIGARH JN" 167
"stops.txt" "stop_name" "AKELAHANSPUR(HALT)" 175
"stops.txt" "stop_name" "ALAMPUR ROAD" 178
"stops.txt" "stop_name" "AMLORI SARSAR" 179
"stops.txt" "stop_name" "AMLA JN" 198
"stops.txt" "stop_name" "AHAMADPUR JN." 206
"stops.txt" "stop_name" "AMMAPALLI HALT" 208
"stops.txt" "stop_name" "AMARPURA RATHAN" 209
"stops.txt" "stop_name" "AMHA PIPRA" 211
"stops.txt" "stop_name" "AMARAVILA HALT" 217
"stops.txt" "stop_name" "AMAN VADI" 218
"stops.txt" "stop_name" "AUNTA HALT" 222
unknown_column INFO 4

unknown_column

A column name is unknown.

You can see more about this notice here.

filename (?) The name of the faulty file. fieldName (?) The name of the unknown column. index (?) The index of the faulty column.
"agency.txt" "cemv_support" 9
"stops.txt" "stop_access" 16
"routes.txt" "cemv_support" 14
"trips.txt" "cars_allowed" 11