IEEE Circuits and Systems Magazine - Q4 2019 - 41

Section VI, a few important conclusions are drawn, and
the possible scope of future work is discussed.
II. Data Collection, Mining and Visualization
Although significant research interest in the field of network science theory has been cultivated for several decades, applying the established concepts to real-world
data has been practiced only recently as a consequence
of the availability of real-world datasets and the highend tools for processing such huge datasets. With the aid
of real-world datasets, a network topology which closely
mimics the real-world structure is generated using the
concepts of graph theory. Building a network topology
forms the fundamental and important aspect in a PTN
analysis since the course of the defined topology significantly influences the understanding of both the local
and global aspects of a network. A list of online sources
and relevant datasets are given in Appendix A. The extracted datasets include information on
i)	 List of stops/stations along with their id's, names,
latitude/northing and longitude/easting data.

ii)	 List of routes/sequence-of-stops along with their
stop sequence id's and names for the inbound,
outbound, and round-trip routes.
Here, a stop or station is a designated place allocated
to pick up or drop off passengers, and a route (sequence
of stops) is a path taken to reach the destination from
a source along the intermediate stops. Furthermore,
other information such as the list of routes operated
by different operators, end-to-end travel cost, frequency of operation, specific day and time (e.g., weekday,
weekend, special days, peak hours, off-peak hours,
day-time, night-time routes), etc., are also available in
a few datasets.
Like other complex networks, the availability of huge
data has posed big challenge to transport network analysis. Fortunately, the obtained datasets for PTNs are
relatively midget, and can be processed in a reasonable
time. Here, we describe three basic steps in mining the
crude datasets for extracting meaningful information:
Step 1: Eliminate the anomalies that are commonly
observed in the extracted datasets, e.g., data redundancies

Appendix A: Online Sources
City

Country

Source

Ref.
Bus Transport Network

Hangzhou

China

www.hzbuda.com.cn

[23]

Chennai

India

www.mtcbus.org/

[11]

Ahmedabad

India

www.ahmedabadbrts.org/web/commuters.html

[11]

Delhi

India

delhitravelhelp.in/StopsOfBus.aspx

[11]

Hyderabad

India

www.hyderabadbusroutes.com

[11]

Kolkata

India

www.kolkataonline.in

[11]

Mumbai

India

github.com/transitmetrics/ntd/tree/master

[11]

-

Singapore

www.streetdirectory.com.sg/

-

Hong Kong

China

data.gov.hk/en-data/category/transport?organization= hk-td/

[68]

London

UK

data.london.gov.uk/dataset/tfl-bus-stop-locations-and-routes

-

Bengaluru

India

opencity.in/topic/transportation/

-

-

Australia

opendata.transport.nsw.gov.au/search/type/dataset

-

-

-

www.apta.com

[17]

Metro Transport Network
Beijing

China

www.ebeijing.gov.cn/feature_2/BeijingSubway/

[33]

Shanghai

China

service.shmetro.com/en/

[31]

Hong Kong

China

www.mtr.com.hk/en/customer/tourist/index.php

[32]

Tokyo

Japan

www.tokyometro.jp/en/subwaymap/index.html

[32]

London

UK

tfl.gov.uk/maps/track?intcmp=40400

[32]

New York

America

web.mta.info/maps/submap.html

[32]

Boston

America

mbta.com/schedules/subway

[69]

Paris

France

parisbytrain.com/paris-metro/

[32]

Seoul

Korea

www.korea4expats.com/korean-subways.php

[35]

FOURTH QUARTER 2019 		

IEEE CIRCUITS AND SYSTEMS MAGAZINE	

41

http://www.hzbuda.com http://www.mtcbus.org/ http://www.ahmedabadbrts.org/web/commuters.html http://www.delhitravelhelp.in/StopsOfBus.aspx http://www.hyderabadbusroutes.com http://www.kolkataonline.in http://www.github.com/transitmetrics/ntd/tree/master http://www.streetdirectory.com.sg/ https://data.gov.hk/en-data/category/transport?organization=hk-td http://data.london.gov.uk/dataset/tfl-bus-stop-locations-and-routes http://www.opencity.in/topic/transportation/ http://opendata.transport.nsw.gov.au/search/type/dataset http://www.apta.com http://www.ebeijing.gov.cn/feature_2/BeijingSubway/ http://service.shmetro.com/en/ http://www.mtr.com.hk/en/customer/tourist/index.php http://www.tokyometro.jp/en/subwaymap/index.html http://tfl.gov.uk/maps/track?intcmp=40400 http://web.mta.info/maps/submap.html http://www.mbta.com/schedules/subway http://www.parisbytrain.com/paris-metro/ http://www.korea4expats.com/korean-subways.php

IEEE Circuits and Systems Magazine - Q4 2019

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