My presentation to the August 2014 ABP RhD "Dialogue" peer-talks series, "Examples of Collaborative Data, and Free and Open Source Software, of interest to Urban Researchers”.

1. ExamplesofCollaborativeData,andFreeand
OpenSourceSoftware,ofinteresttoUrban
Researchers
Patrick Sunter: PhD Candidate in Architecture Building and
Planning, University of Melbourne
Acknowledgment: maps produced during this presentation have
been part of collaborative work with Beyond Zero Emissions (BZE).

2. Outline
 Collaborative Data (OpenStreetMap) and
customised cartography
 Importance of Open Data standards: GTFS
 About Free & Open Source Software (FOSS)
 FOSS for urban researchers (QGIS)
 FOSS in my PhD for public transport:
OpenTripPlanner
 Other resources & web-based informatics
projects

3. OpenStreetMap
 http://www.openstreetmap.org
 A global impressive collaboratively-developed street database
 Unlike Google Maps etc, can download the data, license allows use and
further modifications
 Hint: segments for major city-regions, inc. Melbourne, downloadable from
https://mapzen.com/metro-extracts
 OSM in Iquique, Chile (re Jorge’s talk last month)
 Spin-off projects: www.cycletour.org (cartography & hosting by Steve
Bennett, here at UniMelb)
Image left from
http://www.ideasintransit.org/wiki/
OpenStreetMap : showing global edits
to OSM in 2008

4. Data Standards: 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/
 Now available for all AU state capitals,
not yet Melbourne (though other data
released ~Mar 2014)
 Quite strong ecosystem of tools, apps to
process & work with this format
 (* re Territories, not sure about Darwin?)
Top diagram courtesy Martin Davis via
http://lin-ear-th-inking.blogspot.com.au/2011/09/data-model-diagrams-for-gtfs.html

5. Intro to Free & Open Source
Software (FOSS)
 Movement partisans claim its “free as in speech, not as in beer”;
 (One) definition of Open Source (http://opensource.org/osd )
 Inclusion of source code with program;
 Free redistribution of source code;
 Permits derived works;
 Retention of license;
 Or via http://www.gnu.org/philosophy/free-sw.html , “roughly it means that users have the
freedom to run, copy, distribute, study, change and improve the software”.
 Different types of FOSS licenses, broadly categorised into strong/’viral’ (GPL) and permissive
 FOSS is about many things, but these include:
 Ability to share your work and ideas with others;
 Ability to collaborate on building complex artifacts by people in different organisations and
locations (often difficult under other IP regimes);
 Ability to make software portable and improved over time, compared to proprietary software’s
possibility to languish (if original commercial publishing company folds etc)
 Supported by collaborative web platforms to manage and share source code:
https://github.com/

6. FOSS and Academia
 Arguably fits very well with an academic context:-
 Similar to publishing articles :- publishing software related to
your research for others to read, critique, and possibly re-
use, while required to give due credit (especially if publically
funded);
 (Thus, like articles, both enhance your reputation but
support ideal of peer-review)
 Ability for many academics to collaborate and cooperate
and not have to all “re-invent the wheel” – especially
relevant to us PhD students with limited time and zero
budget!
 Makes the software aspect of your work “portable” when
you move between research institutions;
 Later:- I’ll talk re Python and other high-level languages
very much designed with the non-full-time programmer
in mind

7. Quantum GIS
https://www.dropbox.com/s/
8ss39pxjswmd721/Screenshot
%202014-05-11%2016.41.18.png

8. Other helpful & useful FOSS tools
for spatial analysis I use
 Languages: Python, Javascript
 http://www.osgeo.org/ Foundation manages many of these:
 GDAL (Geospatial Data Abstraction Layer) & OGR – for raster &
vector data file conversion & manipulation (www.gdal.org);
 Shapely – spatial geometry processing (toblerity.org/shapely/)
 PostGIS – PostgreSQL database spatial extensions (postgis.net/);
 Leaflet - Interactive spatial web app development (leafletjs.com/)
 Stuff I’m interested in:
 D3 (lightweight javascript interactive web application devt) -
http://d3js.org/

9. Context of my PhD
 Interpretive Action-Research Paradigm
using:-
 Co-Development of Tools
 Participant Observation
 Interviews,
 Focus Groups,
 Artifact Analysis
PhD: Focus is on exploring Free & Open Source software as a potential
means of increasing civil society organisation’s ability to engage with
Metropolitan-scale transport planning and propose alternative futures
Partner Organisations:-
* Beyond Zero Emissions (BZE)
* Public Transport Users Association (PTUA)
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.

10. 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.

11. OpenTripPlanner
 Open Source software that at core is a fast Journey Planner
(algorithms for time-dependent route-finding), collaboration
between Portland’s TriMet and several researchers, + OpenPlans
organisation
 Primarily Java-based, built on other standards and software such
as Tomcat (web services), Leaflet for web application.

12. Potential to employ in spatial network
analysis
 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/

13. 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.

14. OTP Post-Processed in QGIS

15. Comparing current and ‘virtual’
networks & timetables
Left: calculated accessibility from Chadstone, PTV current.
Right: same location & time, but with revised bus network and ‘best case’ service (30km/h avg
speed, 5min headways, implies significant road prioritisation measures)
NECTAR server:- http://130.56.248.56/opentripplanner-analyst-client/

16. Info re NECTAR and AURIN
 NECTAR:- A “cloud computing” service, to allow
researchers Australia-wide to run applications
that need servers on ‘virtual machines’. Can
apply at
http://www.nectar.org.au/research-cloud
 AURIN: Australian Urban Research Infrastructure
Network. Main work happening here at UniMelb.
http://aurin.org.au/

17. Other examples
 Other examples, lowering barriers to using
interactive web maps as a form on
communication, engagement, activism
 UCAl Berkeley PhD-ers “visualising urban data
idealab”:
 http://vudlab.com/#/
 http://www.ghggo.com/d4_PEMS_080813 (By
@MikeTaptich )

18. Software Carpentry course and
learning opps
 Upcoming Free Software Carpentry course here
@ UniMelb – learn (basic essentials of) Python!:
 http://resbaz.github.io/2014-09-15-unimelb/
 Sep 2014 – sold out ! But check
http://resbaz.tumblr.com/bootcamps in future!
 Local meetups:
 Melbourne Open GIS:
http://www.meetup.com/Melbourne-Open-GIS/
 Datahack Melbourne:
http://www.meetup.com/Datahack-Melbourne/

19. References & Contacts
Hillsman, E. & Barbeau, S. 2011, 'Enabling Cost-Effective Multimodal Trip Planners
through Open Transit Data', National Center for Transit Research (University of
Southern Florida), Final Report, FDOT BDK85 TWO 977-20,
http://www.locationaware.usf.edu/ongoing-research/projects/open-transit-
data/.
McGurrin, M. F. & Greczner, D. 2011, 'Performance Metrics: Calculating
Accessibility Using Open Source Software and Open Data', 11-0230.
Contacts & Project Website:
 P.sunter@pgrad.unimelb.edu.au
 http://www.appropedia.org/OSSTIP
 http://bze.org.au/zero-carbon-australia-2020/transport-plan