cars-jaunes — Source Data Validation Report

This report was generated by the Canonical GTFS Schedule validator, version 8.0.1 at 2026-07-10T22:47:13Z,
for the dataset file:///shared/cars-jaunes_b9013ec3.zip. No country code was provided.

Use this report alongside our documentation.

Summary

Agencies included


Feed Info


Publisher Name:
N/A
Publisher URL:
N/A
Feed Email:
N/A
Feed Language:
N/A

Files included


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

Counts


  • Agencies: 1
  • Blocks: 428
  • Routes: 16
  • Shapes: 38
  • Stops: 463
  • Trips: 2082

Specification Compliance report

36408 notices reported (0 errors, 34306 warnings, 2102 infos)

Notice Code Severity Total
expired_calendar WARNING 2

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.
2 "1"
4 "2"
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.
2026 "8-470155272" "28" 182.74689818396052 9.137344909198026 33518 15 "346" "Pointe au Sel" "12:29:00" 33519 16 "370" "RDT Étang-Salé" "12:31:00"
986 "5-470155301" "28" 182.74689818396052 9.137344909198026 33518 15 "346" "Pointe au Sel" "12:29:00" 33519 16 "370" "RDT Étang-Salé" "12:31:00"
1753 "7-470155318" "28" 182.74689818396052 9.137344909198026 33518 15 "346" "Pointe au Sel" "12:29:00" 33519 16 "370" "RDT Étang-Salé" "12:31:00"
2024 "8-470155270" "28" 182.74689818396052 9.137344909198026 33480 15 "346" "Pointe au Sel" "13:29:00" 33481 16 "370" "RDT Étang-Salé" "13:31:00"
988 "5-470155303" "28" 182.74689818396052 9.137344909198026 33480 15 "346" "Pointe au Sel" "13:29:00" 33481 16 "370" "RDT Étang-Salé" "13:31:00"
1754 "7-470155319" "28" 182.74689818396052 9.137344909198026 33480 15 "346" "Pointe au Sel" "13:29:00" 33481 16 "370" "RDT Étang-Salé" "13:31:00"
missing_recommended_file WARNING 1

missing_recommended_file

A recommended file is missing.

You can see more about this notice here.

filename (?) The name of the faulty file.
"feed_info.txt"
missing_timepoint_value WARNING 34296

missing_timepoint_value

stop_times.timepoint value is missing for a record.

When at least one of stop_times.arrival_time or stop_times.departure_time are provided, stop_times.timepoint should be defined

You can see more about this notice here.

Only the first 50 of 34296 affected records are displayed below.

csvRowNumber (?) The row number of the faulty record. tripId (?) The faulty record's `stop_times.trip_id`. stopSequence (?) The faulty record's `stop_times.stop_sequence`.
2 "5-100728833" 1
3 "5-100728833" 2
4 "5-100728833" 3
5 "5-100728833" 4
6 "5-100728833" 5
7 "5-100728833" 6
8 "5-100728833" 7
9 "5-100728833" 8
10 "5-100728833" 9
11 "5-100728833" 10
12 "5-100728833" 11
13 "5-100728833" 12
14 "5-100728833" 13
15 "5-100728833" 14
16 "5-100728833" 15
17 "5-100728833" 16
18 "5-100728833" 17
19 "5-100728833" 18
20 "5-100728834" 1
21 "5-100728834" 2
22 "5-100728834" 3
23 "5-100728834" 4
24 "5-100728834" 5
25 "5-100728834" 6
26 "5-100728834" 7
27 "5-100728834" 8
28 "5-100728834" 9
29 "5-100728834" 10
30 "5-100728834" 11
31 "5-100728834" 12
32 "5-100728834" 13
33 "5-100728834" 14
34 "5-100728834" 15
35 "5-100728834" 16
36 "5-100728834" 17
37 "5-100728834" 18
38 "5-100728836" 1
39 "5-100728836" 2
40 "5-100728836" 3
41 "5-100728836" 4
42 "5-100728836" 5
43 "5-100728836" 6
44 "5-100728836" 7
45 "5-100728836" 8
46 "5-100728836" 9
47 "5-100728836" 10
48 "5-100728836" 11
49 "5-100728836" 12
50 "5-100728836" 13
51 "5-100728836" 14
mixed_case_recommended_field WARNING 1

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.

filename (?) Name of the faulty file. fieldName (?) Name of the faulty field. fieldValue (?) Faulty value. csvRowNumber (?) The row number of the faulty record.
"agency.txt" "agency_name" "CAR JAUNE" 2
big_gap_in_service INFO 20

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.
"1" "2025-12-14" "2026-01-25" 41
"1" "2026-02-22" "2026-03-22" 27
"1" "2026-04-26" "2026-05-24" 27
"17" "2026-01-01" "2026-04-06" 94
"17" "2026-04-06" "2026-05-01" 24
"17" "2026-05-25" "2026-07-14" 49
"17" "2026-07-14" "2026-08-15" 31
"2" "2025-12-13" "2026-01-24" 41
"2" "2026-02-21" "2026-03-21" 27
"2" "2026-04-25" "2026-05-23" 27
"3" "2025-12-18" "2026-01-21" 33
"3" "2026-02-27" "2026-03-16" 16
"3" "2026-04-30" "2026-05-18" 17
"3" "2026-07-03" "2026-08-18" 45
"7" "2026-01-18" "2026-03-01" 41
"7" "2026-03-15" "2026-05-03" 48
"7" "2026-05-17" "2026-07-05" 48
"8" "2026-01-20" "2026-02-28" 38
"8" "2026-03-14" "2026-05-02" 48
"8" "2026-05-16" "2026-07-04" 48
trip_with_shape_dist_traveled_but_no_shape_distances INFO 2082

trip_with_shape_dist_traveled_but_no_shape_distances

A trip has shape_dist_traveled values in stop_times.txt but the shape referenced by the trip's shape_id does not have shape_dist_traveled values on all of its points in shapes.txt.

When stop times define distance values but the shape does not carry matching distances on every point, consumers cannot use those distances to align stops to the shape geometry reliably. This inconsistency may cause incorrect routing or display behaviour.

Note: Only the first stop time carrying a shape_dist_traveled value is referenced in the notice; this is a representative row rather than an exhaustive list.

You can see more about this notice here.

Only the first 50 of 2082 affected records are displayed below.

tripCsvRowNumber (?) The row number of the faulty record in trips.txt. tripId (?) The trip_id of the faulty trip. shapeId (?) The shape_id referenced by the trip. stopTimeCsvRowNumber (?) The row number of the first stop_times.txt record for this trip that contains a shape_dist_traveled value. Provided as a representative location; other stop times for the same trip may also carry distance values.
1152 "5-67240050" "E2A" 18841
942 "5-436469866" "S6R" 16138
214 "5-151126160" "O1R" 3440
1155 "5-67240057" "E2A" 18889
1154 "5-67240055" "E2A" 18873
216 "5-151126164" "O1R" 3464
1153 "5-67240054" "E2A" 18857
215 "5-151126162" "O1R" 3452
218 "5-151126167" "O1R" 3488
217 "5-151126165" "O1R" 3476
1501 "7-268566530" "S1R" 24412
1148 "5-67240040" "E2A" 18777
1312 "7-184615006" "O2A" 21385
1502 "7-268566535" "S1R" 24443
1503 "7-268566536" "S1R" 24474
1311 "7-184615004" "O2A" 21370
1504 "7-268566537" "S1R" 24505
1092 "5-67174449" "E2R" 17881
1151 "5-67240045" "E2A" 18825
1310 "7-184615003" "O2A" 21355
1505 "7-268566538" "S1R" 24536
1091 "5-67174448" "E2R" 17865
1506 "7-268566539" "S1R" 24567
1150 "5-67240042" "E2A" 18809
1149 "5-67240041" "E2A" 18793
1313 "7-184615007" "O2A" 21400
1093 "5-67174451" "E2R" 17897
1309 "7-184615002" "O2A" 21340
1147 "5-67240039" "E2A" 18761
939 "5-436469863" "S6R" 16105
940 "5-436469864" "S6R" 16116
941 "5-436469865" "S6R" 16127
1916 "8-184680585" "O2R" 31358
604 "5-302383111" "S2R" 9995
1318 "7-184615017" "O2A" 21475
605 "5-302383112" "S2R" 10016
1317 "7-184615015" "O2A" 21460
606 "5-302383114" "S2R" 10037
1316 "7-184615014" "O2A" 21445
1087 "5-67174436" "E2R" 17801
1086 "5-67174435" "E2R" 17785
1085 "5-67174434" "E2R" 17769
1090 "5-67174443" "E2R" 17849
1089 "5-67174441" "E2R" 17833
1088 "5-67174440" "E2R" 17817
607 "5-302383120" "S2R" 10058
1315 "7-184615011" "O2A" 21430
1314 "7-184615010" "O2A" 21415
608 "5-302383122" "S2R" 10079
1083 "5-67174429" "E2R" 17737