GTFS Schedule Validation Report

This report was generated by the Canonical GTFS Schedule validator, version 7.1.0 at 2026-05-04T15:19:41Z,
for the dataset file:///shared/cloud-metropolitan_dd144658.zip. No country code was provided.

Use this report alongside our documentation.

Summary

Agencies included

Feed Info

Publisher Name:
Busmaps.com
Publisher URL:
https://busmaps.com
Feed Email:
alex@busmaps.com
Feed Language:
English
Feed Start Date:
2026-01-04
Feed End Date:
2026-05-16

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: 72
  • Routes: 16
  • Shapes: 34
  • Stops: 710
  • Trips: 793

Specification Compliance report

181 notices reported (0 errors, 181 warnings, 0 infos)

Notice Code Severity Total
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 "20260504" "20260516" "20260603"
mixed_case_recommended_field WARNING 180

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 180 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" "33rd AVE / 1ST ST N" 3
"stops.txt" "stop_name" "33rd AVE N & 3RD ST N" 4
"stops.txt" "stop_name" "33rd AVE N & 4TH ST N" 5
"stops.txt" "stop_name" "33rd AVE N & 5TH ST N" 6
"stops.txt" "stop_name" "33rd AVE N" 7
"stops.txt" "stop_name" "33rd AVE N & 10th ST N" 9
"stops.txt" "stop_name" "33rd AVE & 12th ST N" 10
"stops.txt" "stop_name" "33rd AVE N & 14th ST N" 11
"stops.txt" "stop_name" "15th ST N & 32nd AVE N" 12
"stops.txt" "stop_name" "15th ST N & 29th AVE N" 13
"stops.txt" "stop_name" "15th ST N & 24th AVE N" 15
"stops.txt" "stop_name" "12th AVE N & 14th ST N" 20
"stops.txt" "stop_name" "13th ST N & 10th AVE N" 22
"stops.txt" "stop_name" "13th ST N & 8TH AVE N" 23
"stops.txt" "stop_name" "13th ST N & 6TH AVE N" 24
"stops.txt" "stop_name" "NB 6TH AVE N & 15th ST N" 26
"stops.txt" "stop_name" "NB 6TH AVE N & 17th ST N" 27
"stops.txt" "stop_name" "2ND AVE N & 1ST ST N" 29
"stops.txt" "stop_name" "SB 6TH AVE N & 17th ST N" 32
"stops.txt" "stop_name" "SB 6TH AVE N & 15th ST N" 33
"stops.txt" "stop_name" "13th ST N & 8TH AV N" 36
"stops.txt" "stop_name" "13th ST N & 10th AV N" 37
"stops.txt" "stop_name" "12th AVE N & 13th ST N" 38
"stops.txt" "stop_name" "12th AVE N 14th ST N" 39
"stops.txt" "stop_name" "1580 12th AVE N" 40
"stops.txt" "stop_name" "15th ST N & 24th AVE N" 45
"stops.txt" "stop_name" "15th ST N & 29th AV N" 47
"stops.txt" "stop_name" "15th ST N & 32nd AVE N" 48
"stops.txt" "stop_name" "33rd AVE N & 14th ST N" 49
"stops.txt" "stop_name" "33rd AVE N & 12th ST N" 50
"stops.txt" "stop_name" "33rd AVE N & 10th ST N" 51
"stops.txt" "stop_name" "33rd AVE N" 53
"stops.txt" "stop_name" "33rd AVE N & 4TH ST N" 54
"stops.txt" "stop_name" "33rd AVE N & 3RD ST N" 55
"stops.txt" "stop_name" "33rd AVE N & 1ST ST N" 56
"stops.txt" "stop_name" "3RD ST N & 11th AVE N" 62
"stops.txt" "stop_name" "10th AVE N & 3RD ST N" 63
"stops.txt" "stop_name" "2ND ST N & 8TH AVE N" 64
"stops.txt" "stop_name" "2ND ST N & 6TH AVE N" 65
"stops.txt" "stop_name" "2ND ST N & 4TH AVE N" 66
"stops.txt" "stop_name" "2ND ST N & 2ND AVE N" 67
"stops.txt" "stop_name" "3RD ST & 30th AVE N" 71
"stops.txt" "stop_name" "3RD ST & 28th AVE N" 72
"stops.txt" "stop_name" "3RD ST & 26th AVE N" 73
"stops.txt" "stop_name" "3RD ST & 24th AVE N" 74
"stops.txt" "stop_name" "3RD ST & 22nd AVE N" 75
"stops.txt" "stop_name" "3RD ST & 19 1/2 AVE N" 76
"stops.txt" "stop_name" "3RD ST & 18th AVE N" 78
"stops.txt" "stop_name" "3RD ST & 16th AVE N" 79
"stops.txt" "stop_name" "12th AVE N & 1ST ST N" 82