Glossary
Commonly used Strava Metro terminology:
Activities - Complete activities as recorded by Strava users.
Trips (Streets Data) - Crossings of a given edge by Strava users. This can include multiple crossings per activity (when a user traverses an edge multiple times, regardless of direction in a single activity)
Commutes - Activities determined to be utilitarian in nature. More information about how we classify commutes here.
Leisure Activities - All activities that are not classified as commutes.
Locals - Users whose primary location is the same as or within the defined area of interest.
Visitors - Users whose primary location is outside of the defined area of interest.
Bike Data - Bicycle data does not include rides that have been marked as E-Bike rides by the Strava user.
Pedestrian Data - Pedestrian data includes run, walk, and hike data combined into a single dataset.
Data Fields / Data Dictionary
The exported data contains the following columns:
edge_UID – the identifier for the street block
activity_type – the type of activity, e.g. (ride)
*hour/date/month/year* – one row per aggregated time frame
"Forward" indicates trips traveling in the direction the street was digitized into OSM (from the first point of the line to the last point of the line).
"Reverse" indicates trips traveling in the opposite direction the street was digitized into OSM (does not indicate wrong-way travel).
"Trip" counts indicate the number of bicycle or pedestrian trips on that edge during the given timeframe.
"People" counts indicate the number of unique people who completed a bicycle or pedestrian trip on that edge during the given timeframe. For instance, 10 people may have completed 30 trips on an edge during the timeframe.
For each row, the following pairs of columns are provided.
Trip counts:
forward_trip_count, reverse_trip_count
forward_commute_trip_count, reverse_commute_trip_count
forward_leisure_trip_count, reverse_leisure_trip_count
People counts:
forward_people_count, reverse_people_count
People counts by Gender:
forward_male_people_count, reverse_male_people_count
forward_female_people_count, reverse_female_people_count
forward_unspecified_people_count, reverse_unspecified_people_count
People counts by Age:
forward_13_19_people_count, reverse_13_19_people_count
forward_20_34_people_count, reverse_20_34_people_count
forward_35_54_people_count, reverse_35_54_people_count
forward_55_64_people_count, reverse_55_64_people_count
forward_65_plus_people_count, reverse_65_plus_people_count
Average Speed:
forward_average_speed, reverse_average_speed (meters per second)
Data Export and Schema Changes
As of May 2021, changes have been made to Data Export functionality and the associated data tables.
Metroview users now have the ability to export hourly, daily, monthly and yearly aggregated datasets. This feature was added as a direct result of the feedback provided by partners and aims to make temporal analysis more efficient. Users will no longer need to add together the daily data to reach monthly or yearly insights. These datasets will be ready to use in your GIS or Data Analysis system with no additional math required.
In conjunction with export changes, there is an updated data structure that can be found when working with the data tables/CSV file.
Noteworthy changes to the tabular data have been highlighted below:
- Hourly columns have been replaced with hourly rows in the CSV file
- Previously present morning/evening columns have been removed from the hourly data. Morning/Evening columns will still appear in the daily, monthly, and yearly data.
- The date column will become hour, date, month, or year depending on the export’s timeframe. The values are ISO 8601 formatted for the appropriate time frame.
If you have scripts in place to ingest, load, or transform Metroview data please review a sample export and take into consideration the aforementioned changes when adjusting your workflows.