A presentation at the 2013 meeting of the UniMelb-based "Transport, Health & Chronic Diseases Research Network", on 13 Nov, 2013 (See http://cwhgs.unimelb.edu.au/knowledge/knowledge ). Talk title:- 'Some Remarks on Issues around Data and Tools for Understanding Public Transport Networks from My PhD Work'.

1. SomeRemarksonIssuesaroundDataandToolsfor
UnderstandingPublicTransportNetworks fromMyPhD
Work
Patrick Sunter: PhD Candidate in Architecture Building and
Planning, University of Melbourne
Transport, Health & Chronic Diseases Research Network Seminar
13 November, 2013

2. Research Context
 Primary Research Methods:-
 Co-Development of Tools
 Participant Observation
 Interviews,
 Focus Groups,
 Artifact Analysis
 Approach part of reflexive tradition in I.S. Discipline such as Soft
Systems Methodology. Specifically drawing from McKay &
Marshall’s (2000) “dual cycles” model of interleaving research
project (researcher) with pragmatic project (partners)
Research Paradigm: Interpretive Action Research (Info Systems)
Undertake a GIS-T System Design, Development & Evaluation with 2
Civil Society Organisations (CSOs) in Melbourne
Network image from HiTrans Best Practice Guide (Nielsen et
al, 2005). Photo credits: www.pt4me2.org.au, Wikimedia
commons user "voland b", Flickr user "avlxyz”. Travel time
map from www.mapumental.com.

3. Target Capability: Public
Transport Network Analysis
 “Travel Time Maps” (IsoChrone
maps)
 Display either:-
 Locations reachable from a
given origin in a given time;
 ‘Catchment’ to reach a given
destination
 Generally involve A* network
calculation but can be
optimised.
 Good because they indicate
overall network quality,
including interchanges
Travel time map from www.mapumental.com.

4. Data: GTFS
 GTFS = “General Transit Feed
Specification’
 developers.google.com/transit/
 Emerged in mid 2000s from
Portland TriMet and Google’s
20% time
 Plaintext format: Entire GTFS
feed of Portland is ~169 Mb
 Live feeds available from 376+
agencies, see:-
www.gtfs-data-exchange.com/
 Includes Sydney, Adelaide,
Brisbane, Canberra: not yet
Melbourne

5. OpenStreetMap is other key
data source
 A very impressive collaboratively-developed street
database
 Hint: segments for major city-regions, inc. Melbourne,
downloadable from http://metro.teczno.com/#melbourne
Image from http://www.ideasintransit.org/wiki/OpenStreetMap : showing global
edits to OSM in 2008

6. Progress with OpenTripPlanner
 With a mixture of running existing Open Source tools –
especially OpenTripPlanner and Quantum GIS, and some
scripting and GIS work, we’ve developed useful visualisations.

7. Looks different in growth areas?
With BZE, are working on ability to visualise different future ‘network scenarios’

8. More advanced visualisations with this
platform & data
 Left: Differential impact to New York Transit network after Hurricane Sandy
 Right: Mode “Accessibility gap” in Washington D.C. between car and
public transport, plus employment
McGurrin, M. F. & Greczner, D. 2011,
'Performance Metrics: Calculating
Accessibility Using Open Source
Software and Open Data', 11-0230.
http://www.theatlanticcities.com/commute/2013/01/
best-maps-weve-seen-sandys-transit-outage-new-york/
4488/

9. Reflections
 Would it be worth a more open, commonly-maintained ‘platform’ of tools &
data for the public transit system for different stakeholders to study, improve –
inc. in growth areas where different requirements apply?
 If yes – what are barriers & issues for greater contribution from data
providers? What is governments, universities role, ABS, etc? Are there
international examples worth looking at more closely e.g. in Finland, Boston,
…
 What problems might there be with these data & tools for different user
groups? E.g. in the developing world “para-transit” may not work so well with
GTFS’s format as-is …
 P.sunter@pgrad.unimelb.edu.au T: @PatSunter
 http://www.appropedia.org/OSSTIP