Home
United States Feeds
park-city2
Source Data Validation Report

park-city2 — Source Data Validation Report

This report was generated by the Canonical GTFS Schedule validator, version 8.0.1 at 2026-08-08T11:03:45Z,
for the dataset file:///shared/park-city2_9b0fc357.zip. No country code was provided.

Use this report alongside our documentation.

Summary

Agencies included

Park City Transit
- website: https://www.parkcity.gov
- phone number:
- email: Not provided

Feed Info

Publisher Name:
N/A: Publisher URL:
N/A: Feed Email:
N/A: Feed Language:
N/A: Service Window:
2026-08-07 to 2026-10-06 (?) The range of service dates covered by the feed, based on trips with an associated service_id in calendar.txt and/or calendar_dates.txt

Files included

agency.txt
calendar.txt
calendar_dates.txt
routes.txt
shapes.txt
stop_times.txt
stops.txt
transfers.txt
trips.txt

Counts

Agencies: 1
Blocks: 18
Routes: 10
Shapes: 45
Stops: 368
Trips: 1917

GTFS Features included (?) GTFS features provide a standardized vocabulary to define and describe features that are officially adopted in GTFS.

ShapesRoute ColorsHeadsignsLocation Types

Specification Compliance report

118 notices reported (0 errors, 117 warnings, 1 infos)

Notice Code Severity Total

equal_shape_distance_diff_coordinates_distance_below_threshold WARNING 31

equal_shape_distance_diff_coordinates_distance_below_threshold

Two consecutive points have equal shape_dist_traveled and different lat/lon coordinates in shapes.txt and the distance between the two points is greater than 0 but less than 1.11m.

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 small difference of coordinates (greater than 0 but less than 1.11 m distance) result in a warning.

You can see more about this notice here.

shapeId (?) The id of the faulty shape.	csvRowNumber (?) The row number from `shapes.txt`.	shapeDistTraveled (?) The faulty record's `shape_dist_traveled` value.	shapePtSequence (?) The faulty record's `shapes.shape_pt_sequence`.	prevCsvRowNumber (?) The row number from `shapes.txt` of the previous shape point.	prevShapeDistTraveled (?) The previous shape point's `shape_dist_traveled` value.	prevShapePtSequence (?) The previous record's `shapes.shape_pt_sequence`.	actualDistanceBetweenShapePoints (?) Actual distance traveled along the shape from the first shape point to the previous shape point.
"20 Tan_2346_49"	2916	2939.0	79	2915	2939.0	78	0.6837267963362506
"20 Tan_170_107"	4483	0.0	1	4482	0.0	0	0.355327204913351
"20 Tan_170_107"	4804	6337.0	322	4803	6337.0	321	0.518341614917187
"20 Tan_170_49"	6469	0.0	1	6468	0.0	0	0.355327204913351
"01 Red_35_170"	989	734.0	26	988	734.0	25	0.8507127159191625
"01 Red_170_35"	7948	0.0	1	7947	0.0	0	0.355327204913351
"01 Red_35_293"	602	734.0	26	601	734.0	25	0.8507127159191625
"09 Purple_170_216"	4265	0.0	1	4264	0.0	0	0.355327204913351
"03 Blue_293_30800"	242	5125.0	240	241	5125.0	239	0.23785206892035382
"50 Teal_170_35"	7381	0.0	1	7380	0.0	0	0.355327204913351
"Trolley_170_72"	3365	0.0	1	3364	0.0	0	0.355327204913351
"05 Yellow_35_170"	5058	734.0	26	5057	734.0	25	0.8507127159191625
"05 Yellow_35_77"	4003	734.0	26	4002	734.0	25	0.8507127159191625
"05 Yellow_35_293"	10086	734.0	26	10085	734.0	25	0.8507127159191625
"05 Yellow_35_293"	10352	6152.0	292	10351	6152.0	291	0.631071658048949
"04 Orange_107_170"	5460	0.0	1	5459	0.0	0	0.3629141239281988
"06 Express_170_29010"	8838	0.0	1	8837	0.0	0	0.355327204913351
"06 Express_170_29010"	8961	2480.0	124	8960	2480.0	123	0.08435238950787899
"50 Teal_35_293"	10487	734.0	26	10486	734.0	25	0.8507127159191625
"50 Teal_35_293"	10643	4240.0	182	10642	4240.0	181	0.631071658048949
"03 Blue_170_30800"	7029	0.0	1	7028	0.0	0	0.355327204913351
"03 Blue_170_30800"	7162	3203.0	134	7161	3203.0	133	0.23785206892035382
"50 Teal_35_170"	9140	734.0	26	9139	734.0	25	0.8507127159191625
"Trolley_170_1005"	2269	0.0	1	2268	0.0	0	0.355327204913351
"03 Blue_30800_293"	9983	4391.0	199	9982	4391.0	198	0.631071658048949
"09 Purple_170_125"	3496	0.0	1	3495	0.0	0	0.355327204913351
"04 Orange_170_107"	4084	0.0	1	4083	0.0	0	0.355327204913351
"20 Tan_49_170"	9300	807.0	36	9299	807.0	35	0.3648326833078442
"20 Tan_49_170"	9301	807.0	37	9300	807.0	36	0.3648326833078442
"20 Tan_107_170"	2328	0.0	1	2327	0.0	0	0.3629141239281988
"20 Tan_107_170"	2538	5710.0	211	2537	5710.0	210	0.518341614917187

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"

mixed_case_recommended_field WARNING 77

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 77 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"	"PC MARC"	15
"stops.txt"	"stop_name"	"PC MARC"	233
"trips.txt"	"trip_headsign"	"PC MARC"	129
"trips.txt"	"trip_headsign"	"PC MARC"	154
"trips.txt"	"trip_headsign"	"PC MARC"	157
"trips.txt"	"trip_headsign"	"PC MARC"	166
"trips.txt"	"trip_headsign"	"PC MARC"	169
"trips.txt"	"trip_headsign"	"PC MARC"	170
"trips.txt"	"trip_headsign"	"PC MARC"	173
"trips.txt"	"trip_headsign"	"PC MARC"	174
"trips.txt"	"trip_headsign"	"PC MARC"	177
"trips.txt"	"trip_headsign"	"PC MARC"	178
"trips.txt"	"trip_headsign"	"PC MARC"	181
"trips.txt"	"trip_headsign"	"PC MARC"	249
"trips.txt"	"trip_headsign"	"PC MARC"	251
"trips.txt"	"trip_headsign"	"PC MARC"	252
"trips.txt"	"trip_headsign"	"PC MARC"	263
"trips.txt"	"trip_headsign"	"PC MARC"	264
"trips.txt"	"trip_headsign"	"PC MARC"	266
"trips.txt"	"trip_headsign"	"PC MARC"	270
"trips.txt"	"trip_headsign"	"PC MARC"	277
"trips.txt"	"trip_headsign"	"PC MARC"	284
"trips.txt"	"trip_headsign"	"PC MARC"	289
"trips.txt"	"trip_headsign"	"PC MARC"	291
"trips.txt"	"trip_headsign"	"PC MARC"	292
"trips.txt"	"trip_headsign"	"PC MARC"	327
"trips.txt"	"trip_headsign"	"PC MARC"	330
"trips.txt"	"trip_headsign"	"PC MARC"	785
"trips.txt"	"trip_headsign"	"PC MARC"	788
"trips.txt"	"trip_headsign"	"PC MARC"	789
"trips.txt"	"trip_headsign"	"PC MARC"	792
"trips.txt"	"trip_headsign"	"PC MARC"	797
"trips.txt"	"trip_headsign"	"PC MARC"	800
"trips.txt"	"trip_headsign"	"PC MARC"	804
"trips.txt"	"trip_headsign"	"PC MARC"	809
"trips.txt"	"trip_headsign"	"PC MARC"	812
"trips.txt"	"trip_headsign"	"PC MARC"	813
"trips.txt"	"trip_headsign"	"PC MARC"	816
"trips.txt"	"trip_headsign"	"PC MARC"	881
"trips.txt"	"trip_headsign"	"PC MARC"	888
"trips.txt"	"trip_headsign"	"PC MARC"	892
"trips.txt"	"trip_headsign"	"PC MARC"	894
"trips.txt"	"trip_headsign"	"PC MARC"	895
"trips.txt"	"trip_headsign"	"PC MARC"	906
"trips.txt"	"trip_headsign"	"PC MARC"	907
"trips.txt"	"trip_headsign"	"PC MARC"	909
"trips.txt"	"trip_headsign"	"PC MARC"	927
"trips.txt"	"trip_headsign"	"PC MARC"	964
"trips.txt"	"trip_headsign"	"PC MARC"	966
"trips.txt"	"trip_headsign"	"PC MARC"	967

route_long_name_contains_short_name WARNING 2

route_long_name_contains_short_name

Long name should not contain short name for a single route.

In routes.txt, route_long_name should not contain the value for route_short_name, because when both are provided, they are often combined by transit applications. Note that only one of the two fields is required. If there is no short name used for a route, use route_long_name only.

Good examples:

route_short_name/route_long_name	Dataset
"N"/"Judah"	Muni San Fransisco
"6"/"ML King Jr Blvd"	Trimet Portland Streetcar
"55"/"Boulevard Saint Laurent"	STM Montreal
"1"/"Rangiora/Cashmere"	Metro Christchurch

Bad examples:

route_short_name/route_long_name
"604"/"604"
"14"/"Route 14"
"2"/"Route 2: Bellows Falls In-Town"

You can see more about this notice here.

routeId (?) The id of the faulty record.	csvRowNumber (?) The row number of the faulty record.	routeShortName (?) The faulty record's `route_short_name`.	routeLongName (?) The faulty record's `route_long_name`.
"20 Tan"	2	"20"	"20 Tan"
"50 Teal"	5	"50"	"50 Teal"

stop_without_stop_time WARNING 6

stop_without_stop_time

A stop in stops.txt is not referenced by any stop_times.stop_id.

Such stops are not used by any trip and normally do not provide user value. This notice may indicate a typo in stop_times.txt.

You can see more about this notice here.

csvRowNumber (?) The row number of the faulty record.	stopId (?) The id of the faulty stop.	stopName (?) The name of the faulty stop.
33	"0:79"	"Heber & Main Down"
34	"0:1004"	"Town Lift Down"
88	"0:219"	"Hawkeye Place Up"
92	"0:100180"	"Bonanza Dr-I"
105	"0:248"	"Lunchroom Shop"
107	"0:1007"	"Town Lift Up"

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.
"stops.txt"	"vehicle_type"	11