abashiribus-current — Source Data Validation Report

This report was generated by the Canonical GTFS Schedule validator, version 7.1.0 at 2026-03-27T23:53:18Z,
for the dataset file:///shared/abashiribus-current_bbf66db6.zip. No country code was provided.

Use this report alongside our documentation.

Summary

Agencies included


Feed Info


Publisher Name:
網走バス株式会社
Feed Email:
N/A
Feed Language:
Japanese
Feed Start Date:
2026-03-29
Feed End Date:
2026-03-31

Files included


  1. agency.txt
  2. agency_jp.txt
  3. calendar.txt
  4. calendar_dates.txt
  5. fare_attributes.txt
  6. fare_rules.txt
  7. feed_info.txt
  8. office_jp.txt
  9. routes.txt
  10. routes_jp.txt
  11. shapes.txt
  12. stop_times.txt
  13. stops.txt
  14. translations.txt
  15. trips.txt

Counts


  • Agencies: 1
  • Blocks: 2
  • Routes: 60
  • Shapes: 60
  • Stops: 550
  • Trips: 146

Specification Compliance report

5876 notices reported (3 errors, 5867 warnings, 6 infos)

Notice Code Severity Total
missing_required_column ERROR 3

missing_required_column

A required column is missing in the input file.

You can see more about this notice here.

filename (?) The name of the faulty file. fieldName (?) The name of the missing column.
"translations.txt" "field_name"
"translations.txt" "language"
"translations.txt" "table_name"
duplicate_route_name WARNING 50

duplicate_route_name

Two distinct routes have either the same route_short_name, the same route_long_name, or the same combination of route_short_name and route_long_name.

All routes of the same route_type with the same agency_id should have unique combinations of route_short_name and route_long_name.

Note that there may be valid cases where routes have the same short and long name, e.g., if they serve different areas. However, different directions must be modeled as the same route.

Example of bad data:

route_id route_short_name route_long_name
route1 U1 Southern
route2 U1 Southern

You can see more about this notice here.

csvRowNumber1 (?) The row number of the first occurrence. routeId1 (?) The id of the the first occurrence. csvRowNumber2 (?) The row number of the other occurrence. routeId2 (?) The id of the the other occurrence. routeShortName (?) Common `routes.route_short_name`. routeLongName (?) Common `routes.route_long_name`. routeTypeValue (?) Common `routes.route_type`. agencyId (?) Common `routes.agency_id`.
2 "11" 3 "12" "" "小清水線" 3 "5460301003048"
2 "11" 4 "13" "" "小清水線" 3 "5460301003048"
2 "11" 5 "21" "" "小清水線" 3 "5460301003048"
2 "11" 6 "22" "" "小清水線" 3 "5460301003048"
2 "11" 7 "23" "" "小清水線" 3 "5460301003048"
2 "11" 8 "24" "" "小清水線" 3 "5460301003048"
9 "31" 10 "32" "" "常呂線" 3 "5460301003048"
9 "31" 11 "41" "" "常呂線" 3 "5460301003048"
12 "51" 13 "61" "" "常呂栄浦線" 3 "5460301003048"
14 "102" 15 "103" "" "つくしヶ丘団地線" 3 "5460301003048"
14 "102" 16 "104" "" "つくしヶ丘団地線" 3 "5460301003048"
14 "102" 17 "105" "" "つくしヶ丘団地線" 3 "5460301003048"
14 "102" 18 "106" "" "つくしヶ丘団地線" 3 "5460301003048"
14 "102" 19 "107" "" "つくしヶ丘団地線" 3 "5460301003048"
14 "102" 20 "108" "" "つくしヶ丘団地線" 3 "5460301003048"
14 "102" 21 "109" "" "つくしヶ丘団地線" 3 "5460301003048"
14 "102" 22 "111" "" "つくしヶ丘団地線" 3 "5460301003048"
14 "102" 23 "112" "" "つくしヶ丘団地線" 3 "5460301003048"
14 "102" 24 "113" "" "つくしヶ丘団地線" 3 "5460301003048"
14 "102" 25 "114" "" "つくしヶ丘団地線" 3 "5460301003048"
14 "102" 26 "116" "" "つくしヶ丘団地線" 3 "5460301003048"
14 "102" 27 "117" "" "つくしヶ丘団地線" 3 "5460301003048"
14 "102" 28 "118" "" "つくしヶ丘団地線" 3 "5460301003048"
14 "102" 29 "120" "" "つくしヶ丘団地線" 3 "5460301003048"
14 "102" 30 "121" "" "つくしヶ丘団地線" 3 "5460301003048"
14 "102" 31 "124" "" "つくしヶ丘団地線" 3 "5460301003048"
32 "201" 33 "203" "" "羽衣・向陽線" 3 "5460301003048"
32 "201" 34 "204" "" "羽衣・向陽線" 3 "5460301003048"
32 "201" 35 "205" "" "羽衣・向陽線" 3 "5460301003048"
32 "201" 36 "211" "" "羽衣・向陽線" 3 "5460301003048"
32 "201" 37 "212" "" "羽衣・向陽線" 3 "5460301003048"
32 "201" 38 "214" "" "羽衣・向陽線" 3 "5460301003048"
39 "301" 40 "302" "" "東京農大線" 3 "5460301003048"
39 "301" 41 "303" "" "東京農大線" 3 "5460301003048"
39 "301" 42 "311" "" "東京農大線" 3 "5460301003048"
39 "301" 43 "312" "" "東京農大線" 3 "5460301003048"
39 "301" 44 "313" "" "東京農大線" 3 "5460301003048"
39 "301" 45 "315" "" "東京農大線" 3 "5460301003048"
46 "401" 47 "404" "" "お買い物バス" 3 "5460301003048"
46 "401" 48 "411" "" "お買い物バス" 3 "5460301003048"
46 "401" 49 "415" "" "お買い物バス" 3 "5460301003048"
50 "701" 51 "702" "" "女満別空港線" 3 "5460301003048"
50 "701" 52 "711" "" "女満別空港線" 3 "5460301003048"
50 "701" 53 "712" "" "女満別空港線" 3 "5460301003048"
54 "821" 55 "822" "" "市内観光施設めぐり" 3 "5460301003048"
54 "821" 56 "831" "" "市内観光施設めぐり" 3 "5460301003048"
54 "821" 57 "832" "" "市内観光施設めぐり" 3 "5460301003048"
54 "821" 58 "833" "" "市内観光施設めぐり" 3 "5460301003048"
59 "901" 60 "911" "" "知床エアポートライナー" 3 "5460301003048"
59 "901" 61 "912" "" "知床エアポートライナー" 3 "5460301003048"
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 "1月17日~3月8日まで運行"
feed_expiration_date7_days WARNING 1

feed_expiration_date7_days

Dataset should be valid for at least the next 7 days.

The dataset expiration date defined in feed_info.txt is in seven days or less. At any time, the published GTFS dataset should be valid for at least the next 7 days.

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 "20260327" "20260331" "20260403"
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 90

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.

Only the first 50 of 90 affected records are displayed below.

filename (?) The name of the faulty file. csvRowNumber (?) The row of the faulty record. fieldName (?) The name of the missing field.
"fare_attributes.txt" 2 "agency_id"
"fare_attributes.txt" 3 "agency_id"
"fare_attributes.txt" 4 "agency_id"
"fare_attributes.txt" 5 "agency_id"
"fare_attributes.txt" 6 "agency_id"
"fare_attributes.txt" 7 "agency_id"
"fare_attributes.txt" 8 "agency_id"
"fare_attributes.txt" 9 "agency_id"
"fare_attributes.txt" 10 "agency_id"
"fare_attributes.txt" 11 "agency_id"
"fare_attributes.txt" 12 "agency_id"
"fare_attributes.txt" 13 "agency_id"
"fare_attributes.txt" 14 "agency_id"
"fare_attributes.txt" 15 "agency_id"
"fare_attributes.txt" 16 "agency_id"
"fare_attributes.txt" 17 "agency_id"
"fare_attributes.txt" 18 "agency_id"
"fare_attributes.txt" 19 "agency_id"
"fare_attributes.txt" 20 "agency_id"
"fare_attributes.txt" 21 "agency_id"
"fare_attributes.txt" 22 "agency_id"
"fare_attributes.txt" 23 "agency_id"
"fare_attributes.txt" 24 "agency_id"
"fare_attributes.txt" 25 "agency_id"
"fare_attributes.txt" 26 "agency_id"
"fare_attributes.txt" 27 "agency_id"
"fare_attributes.txt" 28 "agency_id"
"fare_attributes.txt" 29 "agency_id"
"fare_attributes.txt" 30 "agency_id"
"fare_attributes.txt" 31 "agency_id"
"fare_attributes.txt" 32 "agency_id"
"fare_attributes.txt" 33 "agency_id"
"fare_attributes.txt" 34 "agency_id"
"fare_attributes.txt" 35 "agency_id"
"fare_attributes.txt" 36 "agency_id"
"fare_attributes.txt" 37 "agency_id"
"fare_attributes.txt" 38 "agency_id"
"fare_attributes.txt" 39 "agency_id"
"fare_attributes.txt" 40 "agency_id"
"fare_attributes.txt" 41 "agency_id"
"fare_attributes.txt" 42 "agency_id"
"fare_attributes.txt" 43 "agency_id"
"fare_attributes.txt" 44 "agency_id"
"fare_attributes.txt" 45 "agency_id"
"fare_attributes.txt" 46 "agency_id"
"fare_attributes.txt" 47 "agency_id"
"fare_attributes.txt" 48 "agency_id"
"fare_attributes.txt" 49 "agency_id"
"fare_attributes.txt" 50 "agency_id"
"fare_attributes.txt" 51 "agency_id"
mixed_case_recommended_field WARNING 130

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 130 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.
"routes.txt" "route_long_name" "羽衣・向陽線" 32
"routes.txt" "route_long_name" "羽衣・向陽線" 33
"routes.txt" "route_long_name" "羽衣・向陽線" 34
"routes.txt" "route_long_name" "羽衣・向陽線" 35
"routes.txt" "route_long_name" "羽衣・向陽線" 36
"routes.txt" "route_long_name" "羽衣・向陽線" 37
"routes.txt" "route_long_name" "羽衣・向陽線" 38
"stops.txt" "stop_name" "駒場8丁目" 126
"stops.txt" "stop_name" "駒場8丁目" 127
"stops.txt" "stop_name" "駒場8丁目" 128
"stops.txt" "stop_name" "駒場5丁目" 129
"stops.txt" "stop_name" "駒場5丁目" 130
"stops.txt" "stop_name" "駒場5丁目" 131
"stops.txt" "stop_name" "駒場5丁目" 132
"stops.txt" "stop_name" "駒場3丁目" 133
"stops.txt" "stop_name" "駒場3丁目" 134
"stops.txt" "stop_name" "駒場3丁目" 135
"stops.txt" "stop_name" "駒場3丁目" 136
"stops.txt" "stop_name" "駒場3丁目" 137
"stops.txt" "stop_name" "駒場1丁目" 138
"stops.txt" "stop_name" "駒場1丁目" 139
"stops.txt" "stop_name" "駒場1丁目" 140
"stops.txt" "stop_name" "桂町3丁目" 141
"stops.txt" "stop_name" "桂町3丁目" 142
"stops.txt" "stop_name" "桂町3丁目" 143
"stops.txt" "stop_name" "台町3丁目" 144
"stops.txt" "stop_name" "台町3丁目" 145
"stops.txt" "stop_name" "台町3丁目" 146
"stops.txt" "stop_name" "台町2丁目" 150
"stops.txt" "stop_name" "台町2丁目" 151
"stops.txt" "stop_name" "台町2丁目" 152
"stops.txt" "stop_name" "台町1丁目" 153
"stops.txt" "stop_name" "台町1丁目" 154
"stops.txt" "stop_name" "桂町2丁目" 158
"stops.txt" "stop_name" "桂町2丁目" 159
"stops.txt" "stop_name" "東1丁目 網走市役所前" 166
"stops.txt" "stop_name" "東1丁目 網走市役所前" 167
"stops.txt" "stop_name" "東1丁目 網走市役所前" 168
"stops.txt" "stop_name" "つくしヶ丘6丁目" 388
"stops.txt" "stop_name" "つくしヶ丘6丁目" 389
"stops.txt" "stop_name" "つくしヶ丘5丁目" 395
"stops.txt" "stop_name" "つくしヶ丘5丁目" 396
"stops.txt" "stop_name" "つくしヶ丘5丁目" 397
"stops.txt" "stop_name" "つくしヶ丘4丁目" 398
"stops.txt" "stop_name" "つくしヶ丘4丁目" 399
"stops.txt" "stop_name" "つくしヶ丘4丁目" 400
"stops.txt" "stop_name" "つくしヶ丘3丁目" 401
"stops.txt" "stop_name" "つくしヶ丘3丁目" 402
"stops.txt" "stop_name" "つくしヶ丘3丁目" 403
"stops.txt" "stop_name" "つくしヶ丘2丁目" 404
non_ascii_or_non_printable_char WARNING 5594

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 5594 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" 2 "service_id" "毎日"
"calendar.txt" 3 "service_id" "平日"
"calendar.txt" 4 "service_id" "土日祝"
"calendar.txt" 5 "service_id" "学校休校日運休"
"calendar.txt" 6 "service_id" "前学期の授業日"
"calendar.txt" 7 "service_id" "1月17日~3月8日まで運行"
"calendar_dates.txt" 2 "service_id" "毎日"
"calendar_dates.txt" 3 "service_id" "毎日"
"calendar_dates.txt" 4 "service_id" "毎日"
"calendar_dates.txt" 5 "service_id" "毎日"
"calendar_dates.txt" 6 "service_id" "毎日"
"calendar_dates.txt" 7 "service_id" "毎日"
"calendar_dates.txt" 8 "service_id" "毎日"
"calendar_dates.txt" 9 "service_id" "毎日"
"calendar_dates.txt" 10 "service_id" "毎日"
"calendar_dates.txt" 11 "service_id" "毎日"
"calendar_dates.txt" 12 "service_id" "毎日"
"calendar_dates.txt" 13 "service_id" "毎日"
"calendar_dates.txt" 14 "service_id" "毎日"
"calendar_dates.txt" 15 "service_id" "毎日"
"calendar_dates.txt" 16 "service_id" "毎日"
"calendar_dates.txt" 17 "service_id" "毎日"
"calendar_dates.txt" 18 "service_id" "毎日"
"calendar_dates.txt" 19 "service_id" "毎日"
"calendar_dates.txt" 20 "service_id" "毎日"
"calendar_dates.txt" 21 "service_id" "毎日"
"calendar_dates.txt" 22 "service_id" "毎日"
"calendar_dates.txt" 23 "service_id" "毎日"
"calendar_dates.txt" 24 "service_id" "毎日"
"calendar_dates.txt" 25 "service_id" "毎日"
"calendar_dates.txt" 26 "service_id" "毎日"
"calendar_dates.txt" 27 "service_id" "毎日"
"calendar_dates.txt" 28 "service_id" "毎日"
"calendar_dates.txt" 29 "service_id" "毎日"
"calendar_dates.txt" 30 "service_id" "毎日"
"calendar_dates.txt" 31 "service_id" "毎日"
"calendar_dates.txt" 32 "service_id" "毎日"
"calendar_dates.txt" 33 "service_id" "毎日"
"calendar_dates.txt" 34 "service_id" "毎日"
"calendar_dates.txt" 35 "service_id" "毎日"
"calendar_dates.txt" 36 "service_id" "毎日"
"calendar_dates.txt" 37 "service_id" "毎日"
"calendar_dates.txt" 38 "service_id" "毎日"
"calendar_dates.txt" 39 "service_id" "毎日"
"calendar_dates.txt" 40 "service_id" "毎日"
"calendar_dates.txt" 41 "service_id" "毎日"
"calendar_dates.txt" 42 "service_id" "毎日"
"calendar_dates.txt" 43 "service_id" "毎日"
"calendar_dates.txt" 44 "service_id" "毎日"
"calendar_dates.txt" 45 "service_id" "毎日"
unknown_column INFO 3

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.
"routes.txt" "jp_parent_route_id" 7
"translations.txt" "trans_id" 1
"translations.txt" "lang" 2
unknown_file INFO 3

unknown_file

A file is unknown.

You can see more about this notice here.

filename (?) The name of the unknown file.
"agency_jp.txt"
"office_jp.txt"
"routes_jp.txt"