GTFS Schedule Validation Report

This report was generated by the Canonical GTFS Schedule validator, version 7.1.0 at 2026-06-11T10:54:16Z,
for the dataset file:///shared/omitsju_a74dc426.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:
OMITSJU
Feed Email:
N/A
Feed Language:
French
Feed Start Date:
2026-04-21
Feed End Date:
2026-08-23

Files included

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

Counts

  • Agencies: 1
  • Blocks: 0
  • Routes: 14
  • Shapes: 29
  • Stops: 233
  • Trips: 1030

Specification Compliance report

4483 notices reported (0 errors, 4482 warnings, 1 infos)

Notice Code Severity Total
equal_shape_distance_same_coordinates WARNING 380

equal_shape_distance_same_coordinates

Two consecutive points have equal shape_dist_traveled and the same lat/lon coordinates in shapes.txt.

When sorted by shape.shape_pt_sequence, the values for shape_dist_traveled must increase along a shape. Two consecutive points with equal values for shape_dist_traveled and the same coordinates indicate a duplicative shape point.

You can see more about this notice here.

Only the first 50 of 380 affected records are displayed below.

shapeId (?) The id of the faulty shape. csvRowNumber (?) The row number from `shapes.txt`. shapeDistTraveled (?) Actual distance traveled along the shape from the first shape point to the faulty record. shapePtSequence (?) The faulty record's `shapes.shape_pt_sequence`. prevCsvRowNumber (?) The row number from `shapes.txt` of the previous shape point. prevShapeDistTraveled (?) Actual distance traveled along the shape from the first shape point to the previous shape point. prevShapePtSequence (?) The previous record's `shapes.shape_pt_sequence`.
"6000042" 9113 22.5917 20001 9112 22.5917 10347
"300119" 3165 28.9508 20001 3164 28.9508 10316
"300119" 3180 29.5097 30001 3179 29.5097 20015
"300119" 3202 30.1342 40001 3201 30.1342 30022
"300119" 3223 30.7294 50001 3222 30.7294 40021
"300119" 3243 31.0929 60001 3242 31.0929 50020
"300119" 3254 31.6647 70001 3253 31.6647 60011
"300119" 3271 32.7138 80001 3270 32.7138 70017
"300119" 3279 33.0657 90001 3278 33.0657 80008
"300119" 3284 33.3536 100001 3283 33.3536 90005
"3400078" 6806 14.4068 20001 6805 14.4068 10335
"3400078" 6824 14.7923 30001 6823 14.7923 20018
"3400078" 7101 27.6129 40001 7100 27.6129 30277
"3400079" 7397 13.6905 20001 7396 13.6905 10266
"3400079" 7415 14.076 30001 7414 14.076 20018
"300118" 2386 0.9182 20001 2385 0.9182 10021
"300118" 2390 1.1942 30001 2389 1.1942 20004
"300118" 2399 1.5631 40001 2398 1.5631 30009
"300118" 2414 2.5755 50001 2413 2.5755 40015
"300118" 2427 3.1853 60001 2426 3.1853 50013
"300118" 2447 3.5682 70001 2446 3.5682 60020
"300118" 2467 4.1332 80001 2466 4.1332 70020
"300118" 2486 4.7218 90001 2485 4.7218 80019
"300118" 2504 5.311 100001 2503 5.311 90018
"40105" 1010 0.6308 20001 1009 0.6308 10041
"40105" 1022 1.0129 30001 1021 1.0129 20012
"40105" 1039 1.4104 40001 1038 1.4104 30017
"40105" 1045 1.9278 50001 1044 1.9278 40006
"40105" 1048 2.1477 60001 1047 2.1477 50003
"40105" 1051 2.2649 70001 1050 2.2649 60003
"40105" 1059 2.5118 80001 1058 2.5118 70008
"40105" 1064 2.8976 90001 1063 2.8976 80005
"40105" 1071 3.0713 100001 1070 3.0713 90007
"40105" 1074 3.3504 110001 1073 3.3504 100003
"40105" 1083 3.8072 120001 1082 3.8072 110009
"40105" 1086 3.9617 130001 1085 3.9617 120003
"40105" 1091 4.111 140001 1090 4.111 130005
"40105" 1099 4.3084 150001 1098 4.3084 140008
"40105" 1102 4.4196 160001 1101 4.4196 150003
"40105" 1112 4.7892 170001 1111 4.7892 160010
"40105" 1122 5.0354 180001 1121 5.0354 170010
"40105" 1134 5.3076 190001 1133 5.3076 180012
"40105" 1141 5.4799 200001 1140 5.4799 190007
"40105" 1151 5.8202 210001 1150 5.8202 200010
"40105" 1158 6.0414 220001 1157 6.0414 210007
"40105" 1164 6.3203 230001 1163 6.3203 220006
"40105" 1170 6.6267 240001 1169 6.6267 230006
"40105" 1178 6.7256 250001 1177 6.7256 240008
"40105" 1191 7.085 260001 1190 7.085 250013
"40105" 1206 7.4029 270001 1205 7.4029 260015
expired_calendar WARNING 1

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.

csvRowNumber (?) The row of the faulty record. serviceId (?) The service id of the faulty record.
7 "SJU-H26-SJU_GTFS-Fête-1-01"
missing_feed_contact_email_and_url WARNING 1

missing_feed_contact_email_and_url

Best Practices for feed_info.txt suggest providing at least one of feed_contact_email and feed_contact_url.

You can see more about this notice here.

csvRowNumber (?) The row number of the validated record.
2
missing_recommended_field WARNING 4

missing_recommended_field

A recommended field is missing.

The given field has no value in some input row, even though values are recommended.

You can see more about this notice here.

filename (?) The name of the faulty file. csvRowNumber (?) The row of the faulty record. fieldName (?) The name of the missing field.
"feed_info.txt" 2 "feed_version"
"fare_attributes.txt" 2 "agency_id"
"fare_attributes.txt" 3 "agency_id"
"fare_attributes.txt" 4 "agency_id"
mixed_case_recommended_field WARNING 70

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 70 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_headsign" "secteur rural" 925
"trips.txt" "trip_headsign" "secteur rural" 926
"trips.txt" "trip_headsign" "secteur rural" 927
"trips.txt" "trip_headsign" "secteur rural" 928
"trips.txt" "trip_headsign" "secteur rural" 929
"trips.txt" "trip_headsign" "secteur rural" 930
"trips.txt" "trip_headsign" "secteur rural" 931
"trips.txt" "trip_headsign" "secteur rural" 932
"trips.txt" "trip_headsign" "secteur rural" 933
"trips.txt" "trip_headsign" "secteur rural" 934
"trips.txt" "trip_headsign" "secteur rural" 935
"trips.txt" "trip_headsign" "secteur rural" 936
"trips.txt" "trip_headsign" "secteur rural" 937
"trips.txt" "trip_headsign" "secteur rural" 938
"trips.txt" "trip_headsign" "secteur rural" 939
"trips.txt" "trip_headsign" "secteur rural" 940
"trips.txt" "trip_headsign" "secteur rural" 941
"trips.txt" "trip_headsign" "secteur rural" 942
"trips.txt" "trip_headsign" "secteur rural" 943
"trips.txt" "trip_headsign" "secteur rural" 944
"trips.txt" "trip_headsign" "secteur rural" 945
"trips.txt" "trip_headsign" "secteur rural" 946
"trips.txt" "trip_headsign" "secteur rural" 947
"trips.txt" "trip_headsign" "secteur rural" 948
"trips.txt" "trip_headsign" "secteur rural" 949
"trips.txt" "trip_headsign" "secteur rural" 950
"trips.txt" "trip_headsign" "secteur rural" 951
"trips.txt" "trip_headsign" "secteur rural" 952
"trips.txt" "trip_headsign" "secteur rural" 953
"trips.txt" "trip_headsign" "secteur rural" 954
"trips.txt" "trip_headsign" "secteur rural" 955
"trips.txt" "trip_headsign" "secteur rural" 956
"trips.txt" "trip_headsign" "secteur rural" 957
"trips.txt" "trip_headsign" "secteur rural" 958
"trips.txt" "trip_headsign" "secteur rural" 975
"trips.txt" "trip_headsign" "secteur rural" 976
"trips.txt" "trip_headsign" "secteur rural" 977
"trips.txt" "trip_headsign" "secteur rural" 978
"trips.txt" "trip_headsign" "secteur rural" 979
"trips.txt" "trip_headsign" "secteur rural" 980
"trips.txt" "trip_headsign" "secteur rural" 981
"trips.txt" "trip_headsign" "secteur rural" 982
"trips.txt" "trip_headsign" "secteur rural" 983
"trips.txt" "trip_headsign" "secteur rural" 984
"trips.txt" "trip_headsign" "secteur rural" 985
"trips.txt" "trip_headsign" "secteur rural" 986
"trips.txt" "trip_headsign" "secteur rural" 987
"trips.txt" "trip_headsign" "secteur rural" 988
"trips.txt" "trip_headsign" "secteur rural" 989
"trips.txt" "trip_headsign" "secteur rural" 990
non_ascii_or_non_printable_char WARNING 4023

non_ascii_or_non_printable_char

Non ascii or non printable char in ID field.

A value of a field with type ID contains non ASCII or non printable characters. This is not recommended.

You can see more about this notice here.

Only the first 50 of 4023 affected records are displayed below.

filename (?) Name of the faulty file. csvRowNumber (?) Row number of the faulty record. columnName (?) Name of the column where the error occurred. fieldValue (?) Faulty value.
"calendar.txt" 6 "service_id" "SJU-E26-SJU_GTFS-Fête-1-01"
"calendar.txt" 7 "service_id" "SJU-H26-SJU_GTFS-Fête-1-01"
"calendar_dates.txt" 8 "service_id" "SJU-E26-SJU_GTFS-Fête-1-01"
"calendar_dates.txt" 9 "service_id" "SJU-E26-SJU_GTFS-Fête-1-01"
"calendar_dates.txt" 10 "service_id" "SJU-H26-SJU_GTFS-Fête-1-01"
"stop_times.txt" 8010 "trip_id" "3340865-SJU-E26-SJU_GTFS-Fête-1-01"
"stop_times.txt" 8011 "trip_id" "3340865-SJU-E26-SJU_GTFS-Fête-1-01"
"stop_times.txt" 8012 "trip_id" "3340865-SJU-E26-SJU_GTFS-Fête-1-01"
"stop_times.txt" 8013 "trip_id" "3340865-SJU-E26-SJU_GTFS-Fête-1-01"
"stop_times.txt" 8014 "trip_id" "3340865-SJU-E26-SJU_GTFS-Fête-1-01"
"stop_times.txt" 8015 "trip_id" "3340865-SJU-E26-SJU_GTFS-Fête-1-01"
"stop_times.txt" 8016 "trip_id" "3340865-SJU-E26-SJU_GTFS-Fête-1-01"
"stop_times.txt" 8017 "trip_id" "3340865-SJU-E26-SJU_GTFS-Fête-1-01"
"stop_times.txt" 8018 "trip_id" "3340865-SJU-E26-SJU_GTFS-Fête-1-01"
"stop_times.txt" 8019 "trip_id" "3340865-SJU-E26-SJU_GTFS-Fête-1-01"
"stop_times.txt" 8020 "trip_id" "3340865-SJU-E26-SJU_GTFS-Fête-1-01"
"stop_times.txt" 8021 "trip_id" "3340865-SJU-E26-SJU_GTFS-Fête-1-01"
"stop_times.txt" 8022 "trip_id" "3340865-SJU-E26-SJU_GTFS-Fête-1-01"
"stop_times.txt" 8023 "trip_id" "3340865-SJU-E26-SJU_GTFS-Fête-1-01"
"stop_times.txt" 8024 "trip_id" "3340865-SJU-E26-SJU_GTFS-Fête-1-01"
"stop_times.txt" 8025 "trip_id" "3340865-SJU-E26-SJU_GTFS-Fête-1-01"
"stop_times.txt" 8026 "trip_id" "3340865-SJU-E26-SJU_GTFS-Fête-1-01"
"stop_times.txt" 8027 "trip_id" "3340865-SJU-E26-SJU_GTFS-Fête-1-01"
"stop_times.txt" 8028 "trip_id" "3340865-SJU-E26-SJU_GTFS-Fête-1-01"
"stop_times.txt" 8029 "trip_id" "3340865-SJU-E26-SJU_GTFS-Fête-1-01"
"stop_times.txt" 8030 "trip_id" "3340865-SJU-E26-SJU_GTFS-Fête-1-01"
"stop_times.txt" 8031 "trip_id" "3340865-SJU-E26-SJU_GTFS-Fête-1-01"
"stop_times.txt" 8032 "trip_id" "3340865-SJU-E26-SJU_GTFS-Fête-1-01"
"stop_times.txt" 8033 "trip_id" "3340865-SJU-E26-SJU_GTFS-Fête-1-01"
"stop_times.txt" 8034 "trip_id" "3340865-SJU-E26-SJU_GTFS-Fête-1-01"
"stop_times.txt" 8035 "trip_id" "3340865-SJU-E26-SJU_GTFS-Fête-1-01"
"stop_times.txt" 8036 "trip_id" "3340865-SJU-E26-SJU_GTFS-Fête-1-01"
"stop_times.txt" 8037 "trip_id" "3340865-SJU-E26-SJU_GTFS-Fête-1-01"
"stop_times.txt" 8038 "trip_id" "3340865-SJU-H26-SJU_GTFS-Fête-1-01"
"stop_times.txt" 8039 "trip_id" "3340865-SJU-H26-SJU_GTFS-Fête-1-01"
"stop_times.txt" 8040 "trip_id" "3340865-SJU-H26-SJU_GTFS-Fête-1-01"
"stop_times.txt" 8041 "trip_id" "3340865-SJU-H26-SJU_GTFS-Fête-1-01"
"stop_times.txt" 8042 "trip_id" "3340865-SJU-H26-SJU_GTFS-Fête-1-01"
"stop_times.txt" 8043 "trip_id" "3340865-SJU-H26-SJU_GTFS-Fête-1-01"
"stop_times.txt" 8044 "trip_id" "3340865-SJU-H26-SJU_GTFS-Fête-1-01"
"stop_times.txt" 8045 "trip_id" "3340865-SJU-H26-SJU_GTFS-Fête-1-01"
"stop_times.txt" 8046 "trip_id" "3340865-SJU-H26-SJU_GTFS-Fête-1-01"
"stop_times.txt" 8047 "trip_id" "3340865-SJU-H26-SJU_GTFS-Fête-1-01"
"stop_times.txt" 8048 "trip_id" "3340865-SJU-H26-SJU_GTFS-Fête-1-01"
"stop_times.txt" 8049 "trip_id" "3340865-SJU-H26-SJU_GTFS-Fête-1-01"
"stop_times.txt" 8050 "trip_id" "3340865-SJU-H26-SJU_GTFS-Fête-1-01"
"stop_times.txt" 8051 "trip_id" "3340865-SJU-H26-SJU_GTFS-Fête-1-01"
"stop_times.txt" 8052 "trip_id" "3340865-SJU-H26-SJU_GTFS-Fête-1-01"
"stop_times.txt" 8053 "trip_id" "3340865-SJU-H26-SJU_GTFS-Fête-1-01"
"stop_times.txt" 8054 "trip_id" "3340865-SJU-H26-SJU_GTFS-Fête-1-01"
unexpected_enum_value WARNING 3

unexpected_enum_value

An enum has an unexpected value.

You can see more about this notice here.

filename (?) The name of the faulty file. csvRowNumber (?) The row number of the faulty record. fieldName (?) The name of the field where the error occurred. fieldValue (?) Faulty value.
"routes.txt" 13 "route_type" 1501
"routes.txt" 14 "route_type" 1501
"routes.txt" 15 "route_type" 1501
unknown_column INFO 1

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.
"stop_times.txt" "platform_track" 10