The Postgres database used by some of the following is created by applying pgloader to the initial SQLite database.

Files

• one_file/: directory containing a single example SIRI-VM data file encoded in XML

• delays.py: Read one or more directory names from the command line. From these, read all *.xml files and assume each contains a collection of SIRI-VM records encoded in XML. For each record, print the difference between the event's time (RecordedAtTime) and our time of receipt as encoded in the file name.

• compare_reciept.py: Read one or more directory names from the command line. From these, read all *.xml files and assume each contains one day's worth of SIRI-VM data encoded in XML. Print a text summary of the differences between the event's time (RecordedAtTime) and our time of receipt as encoded in the file name.

• sumarise_reciept.py: Read one or more directory names from the command line. From these, read all *.xml files and assume each contains one day's worth of SIRI-VM data encoded in XML. For each day, print to stdout in CSV summary statistics of the difference between the event's time (RecordedAtTime) and our time of receipt as encoded in the file name.

• latencies.csv: Example output from sumarise_reciept.py

• plotter.py: Read the file latencies.csv, assumed to contain the output from sumarise_reciept.py. Plot the contents.

• siri_analysis.pdf: example output from plotter.py

• sqlite_loader.py: Read one or more directory names from the command line. From these, read all *.xml files and assume each contains SIRI-VM data encoded in XML. Extract selected fields and print them to stdout in a format suitable for sqlite_loader.sh

• sqlite_loader.sh: run sqlite_loader.py. load data extracted into the table activity in the SQLite database activity.sqlite

• activity.sqlite: example SQLite database created by sqlite_loader.sh

• questions.sql: Extract misc summaries from the data in the SQLite database created by sumarise_reciept.py

• schema.sql: Schema for the SQLite database created by sumarise_reciept.py

• extract_journeys.py: extract a set of possible journeys from the SQLite database created by sqlite_loader.sh

• extract_one_journey.py: extract a particular hard-coded journey from the SQLite database created by sqlite_loader.sh

• deltas.sql: from a Postgres version of the SQLite database created by sqlite_loader.sh extract the time (delta) between consecutive position reports for each journey identified by (vehiclemonitoringref, originref, originaimeddeparturetime) tuples.

• deltas.csv: example output from deltas.sql

• deltas.ods: LibreOffice spreadsheet of deltas.csv data

• deltas.png: Plot of the data from deltas.png

• find-dups.sql: Select records containing duplicated data

• flag-dups.sql: set a flag on the second and subsequent record containing duplicated data in a Postgres version of the SQLite database created by sqlite_loader.sh

• iterator.py: Iteratively query a Postgres table of unique journey data grouping it by all plausible combinations of columns to establish which combinations are unique (see summary in Looking-at-journies)

• Looking-at-journies: notes on how to partition SIRI-VM records into distinct journeys

• animation/: directory containing a simple animation of a single bus journey

• siri-1.3: Siri 1.3 documentation and schema

• siri-1.3.zip: Source of siri-1.3

• siri_vehicleMonitoring_service.svg: SVG diagram of SIRI vehicleMonitoring_service schema

• siri_summary.md: Summary of observer characteristics of the SIRI data

• siri_summary.pdf: Formatted version of siri_summary.md