ArticlePDF Available

Open Data-Set of Seven Canadian Cities

January 2017
IEEE Access PP(99):1-1

DOI:10.1109/ACCESS.2016.2645658

License
CC BY-NC-ND 4.0

Authors:

Haiwei Dong

University of Ottawa

Abdulmotaleb El Saddik

University of Ottawa

Open data has attracted huge attention for the construction of smart city in terms of delivering useful city information to citizens and interacting with citizens from the city council perspective. In this paper, we present an overview of the current status and issues of open data opened by different seven Canadian cities. We start by presenting the characters of open data, followed by data format conclusion and detailed dataset explaination for each Canadian city (e.g., Calgary, Halifax, Surrey, Waterloo, Ottawa, Vancouver, and Toronto) including the different data catalogues and their detailed characteristics. Next, we discuss the state-of-the-art of the tools and applications developed over each city’s open data. Here, we not only illustrate the most successful examples, but particularly consider the potential issues due to the characters of the city datasets. This paper is not only beneficial for a government which can compare its open data status with that of the Canadian cities but also quite useful for users or companies interested in tool development over open city data.

Tools developed on open data of different cities. (a) Sportsity Application: The city of Calgary. (b) Low Cost and Free Resources Application: The city of Surrey. (c) PingStreet Toronto Application: The city of Waterloo. (d) Save the Rain Application: The city of Ottawa. (e) PayByPhone Application: The city of Vancouver. (f) Wellbeing Toronto Application: The city of Toronto.

…

Different Formats of same data-set (Traffic Camera). (a) CSV format for the city of Toronto. (b) XML format for city of Ottawa. (c) JSON format for city of Surrey. (d) the combined output in XML format.

…

Figures - uploaded by Abdulmotaleb El Saddik

Content may be subject to copyright.

Content uploaded by Abdulmotaleb El Saddik

Content may be subject to copyright.

Available via license: CC BY-NC-ND 4.0

Content may be subject to copyright.

http://www.ieee.org/publications_standards/publications/rights/index.html for more information.

This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/ACCESS.2016.2645658, IEEE Access

Open Data-Set of Seven Canadian Cities

Haiwei Dong, Senior Member, IEEE, Gobindbir Singh, Aarti Attri, and Abdulmotaleb El Saddik, Fellow, IEEE

Abstract—Open data has attracted huge attention for the

construction of smart city in terms of delivering useful city

information to citizens and interacting with citizens from the city

council perspective. In this paper, we present an overview of the

current status and issues of open data opened by different seven

Canadian cities. We start by presenting the characters of open

data, followed by data format conclusion and detailed dataset

explaination for each Canadian city (e.g., Calgary, Halifax,

Surrey, Waterloo, Ottawa, Vancouver, and Toronto) including

the different data catalogues and their detailed characteristics.

Next, we discuss the state-of-the-art of the tools and applications

developed over each city’s open data. Here, we not only illustrate

the most successful examples, but particularly consider the

potential issues due to the characters of the city datasets. This

paper is not only beneﬁcial for a government which can compare

its open data status with that of the Canadian cities but also quite

useful for users or companies interested in tool development over

open city data.

Index Terms—big data, characters of open-data, smart city,

city application tools.

I. INT ROD UC TI ON

NOWADAYS, all cities in the world are great producers of

data, and this data is given a new term which is known

as Big Data [1]. Efﬁcient management of this huge data is

very essential to constitute powerful tool to have structured

form of data and giving back to the public with the data

having more utility. This real-world data is a key to the

implementation and validation of cities’ social, economic and

educational structure as it contains useful reviews from public

about various activities within the cities. City administrators

need integrated the factual data to make better decisions and

policies to make cities smarter and sustainable. Thus the

availability and accuracy are the major parameters that may

affect the reliability of the resulting estimates. Thus there

are various steps under which a city open data constantly

goes through before it is converted into useful information.

The process involves the collection and then storage of data

for further processing [2]. The data is closely analysed and

segregated in different categories and formats to convert it into

a meaningful information. Furthermore the data visualization

is important concept to make the information available for

citizens in a better structured form. The main purpose to

analyse Open Data is to extract the meaningful information

from this open government data that can contribute to the

H. Dong and A. El Saddik are with Multimedia Computing Research Lab-

oratory (MCRLab), School of Electrical Engineering and Computer Science,

University of Ottawa, 800 King Edward Avenue, ON K1N 6N5, Canada e-

mail: {hdong; elsaddik}@uottawa.ca

G. Singh is with the Department of Electronic Business Technologies,

University of Ottawa, 800 King Edward Avenue, ON K1N 6N5, Canada e-

mail: gsingh032@uottawa.ca.

A. Attri is with the Department of Electrical and Computer Engineering,

Carleton University, 1125 Colonel By Dr, ON K1S 5B6, Canada e-mail:

aarti@cmail.carleton.ca.

betterment of public [3]. There are many efforts made by

researchers and by different organizations to study this huge

data [4].

The signiﬁcance of open data to bring in innovations and

developments is given a lot of stress to bring sustainability in a

city. Thus many entrepreneurs [5] of IT companies [6] mention

the importance of open data in a sense that it helps to ﬁgure

out present issues in a city and give notion to work towards

the betterment of citizens. This is the basis of selecting seven

cities from Canada which has a ﬂourishing IT market so that it

can be helpful for professionals looking for ideas and speciﬁc

sectors to work on that ideas. A substantial work has been

done by researchers to emphasize on developing e-services

from government open data [7], [8]. An effort has been made

where a framework has been developed [9] to explore the

status of present Open Government Data (OGD) by using the

content analysis of web portals of government open data from

35 countries and also actually working brieﬂy on open data

portals from four countries Morocco, UAE, Kenya and Ghana

listing only number of data-sets and the formats used.

However there is still a void for detailed analysis at city level

in Canadian cities, which is one of the driving force for this

paper. A city level discussion for open data utilisation in ﬁve

smart cities namely Barcelona, Chicago, Manchester, Amster-

dam, and Helsinki has been done [10] in order to highlight the

signiﬁcance of open data and its resulting innovations in these

cities. In different parts of the world researchers are working

on the initiatives taken by governments for OGD and how

these initiatives has valued the country in its economic growth

as well as democratic empowerment [11]. A considerable

effort has been made in [12] where an event management

system has been developed to generate events in different

categories, after which the huge amount of data generated from

events is analysed and is utilised in a manner to extract results

from it. Although this platform is presented for big data in

general but this can be used as a good platform to study open

data from different categories listed by the cities and develop

tools that might result in an innovation. It has deﬁned the data

collection from different sources such as social media, hard-

sensors and public itself. Also this includes analysis of this

data in structured form to create events that include various

categories as municipal, trafﬁc, medical etc. and thus gives

useful information to the public. Therefore it is a public-

oriented platform which takes information from public and

gives informative knowledge of the city to the public.

However the domain of applications is not limited to city

organization or locations only, it can be different based on

the category of data provided by the city. Application de-

velopment has been done on open city data in the ﬁeld of

environmental science [13] where visualizations has been used

for Geographical Information System (GIS) in order to show

http://www.ieee.org/publications_standards/publications/rights/index.html for more information.

the effect of clusters of buildings in coastal areas on non-

mitigation of higher temperatures even if sea breezes ﬂows into

inland areas due to obstruction offered by these buildings. The

motivation of this paper is to study open-data-sets available in

different Canadian cities (Calgary, Halifax, Ottawa, Toronto,

Surrey, Waterloo and Vancouver) and perform analysis on this

data which can be used by IT professionals to build a platform

to use this information.

The paper is organized in the manner that ﬁrstly the section

II briefs about the characteristics of open data based on which

the quality of of open data provided by a city can be judged.

Further, section III describes the current status of the data

and emphasizes the various characteristics, formats and diverse

catalogues describing the open (government) data. Section IV

addresses various tools developed for open data in different

cities. Further, section V discusses some challenges for open

data and brieﬂy touches the proposed model to deal with

heterogeneous data.

II. CH AR ACT ER IS TI CS O F OPE N DATA

This section will explain a few characteristics of open-data.

The idea has been taken form the general characteristics of

data discussed in the literature [14] which clearly mention

that government if government or any organization wants to

makes its open for public then the deep study of the data

characteristics is very essential. It helps the organization to

look into the resources and then decide what to make open

and in which format it should be ﬂooded to the public. Those

characteristics are as explained as follows:

A. Completeness (Volume)

The completeness of open data refers to the amount of open

data released by the city. It does not refers to the data in

different domains but volume of data in a particular domain.

Most of the cities do not release the full-ﬂedged data available

for a particular category but instead release a sample of the

data which can help the user to work around with the available

attributes and sample data with the attribute values. Ideally

the public data should be available completely to the public

because this data does not have privacy or security issues. The

sense of completeness can only be achieved when electronic

copies of bulk ﬁles for public data are provided to the user.

B. Availability

This characteristic deﬁnes the availability of the city open

data either through the city open data website or by other

means. Every city provides an open license to all the viewers

to access the data. Usually there are no restrictions on open

data because the sense of open data is lost when the authorities

put restrictions on the released data. It may also happen that

sensitive categories like criminal records might not be made

available without a license or if it is made available, the user

must accept that the city is not responsible for any inferences

made from the available data.

C. Usability

The data provided should be such that the data can be

easily used by the user. Thus the cities are producing data

in digital formats (CSV) over internet. Similarly a particular

data demonstrating number values is much more usable when

represented in tables instead of plain text. So lesser the

processing required on data, more usable the data is.

D. Non-Proprietary

The control of a particular entity or organisation over the

data proves the proprietary rights over the data. However the

open data must have the feature that no one should have

proprietary rights over the data. Therefore, non-proprietary is

a characteristic that open data needs to have.

E. Non-Discriminatory

The data released by the responsible entity should not be

biased towards a group, community, religion or region. The

availability of data should not depend whether the user belongs

to the same city or country, a particular religion, race or

community. Thus city data should be available to anyone who

want it without any prior registration.

F. Variety

The categories of open data must not be limited to selected

sectors. It should have the variety in terms of the categories for

which the open data needs to be collected. The data-sets of the

open data should not focus on the same subject. For example,

if all the data-sets of the city focus on transportation of the

city and ignore the categories like criminal records, buildings,

municipal operations, elections, electricity and water, then the

data-sets of the city lacks variety.

G. Timely Processed and Updated

This characteristics is deﬁned in a sense that the data is

made available as quickly as necessary to reserve the value of

data. Thus the released data for the public must be up to date.

The access to these updated data-sets should also be given

by providing APIs (Application Program Interface) which can

be used directly in applications to fetch the latest data. The

usefulness of the data decreases as the data gets outdated.

H. Summary

Based on the data analysis performed on data-sets for each

city, it would be useful to discuss whether the cities has

attained majority of the open data characteristics discussed

above or not. All the cities except Halifax has maintained

variety in their data-sets in different domains. However, in

terms of completeness Halifax, Surrey, Vancouver and Wa-

terloo have worked on building open data with considerable

number of entries in majority of the data-sets whereas Calgary,

Toronto and Ottawa are still struggling in developing in terms

of numbers. All the cities have made the data available online

on their web portals irrespective of the user’s race, gender,

religion or a region. None of the cities has any proprietary

http://www.ieee.org/publications_standards/publications/rights/index.html for more information.

rights on the open data available on its website. Every city

has listed formats of its data which are machine processable

and are usable in their original form for the user. Each

city is making best of its efforts to process the data timely

or frequently so as to provide users with the latest data.

However, the update frequency actually depends upon the

kind of data-set. For example, “transportation” data is more

frequently updated as compared to “elected ofﬁcials” data-

sets as “transportation” data is more vulnerable to changes.

For all the cities the laws of usage of open data are governed

by respective provinces of the cities. The detailed description

and analysis of each city’s open data has been done in section

IV where these characteristics are discussed with respect to

the city’s open data.

III. OPE N DATA BY DIFFERENT CANA DI AN CI TI ES

This section discusses and analyses the open data collected

by seven Canadian cities namely Calgary [15], Ottawa [16],

Surrey [17], Toronto [18], Vancouver [19], Waterloo [20]

and Halifax [21]. The data is collected from their respective

websites, on which it is available open to public in the form of

different visualization tools and also to make any changes as

per their needs. This data is categorized in various catalogues

and formats. Several open data catalogues are deﬁned in

various categories which are explained in section IV. These

catalogues are available in different formats as discussed

further in this section. A few of the catalogues from different

cities are available in common formats.

A. Different Formats of Data

There are various formats in which data is represented in

different cities. Some of them are machine-readable which are

difﬁcult for users to understand but there are some formats

which can be easily understood by users. All formats in which

data-sets from seven Canadian cities are deﬁned are as follows:

1) CSV (Comma Separated Files): This formats is very

useful as it is compatible to deﬁne large data-sets. Usually the

data-sets like censuses data results, election results, number of

parks/beaches, trafﬁc volume etc. within the cities are available

in CSV formats.

2) DWG (from Drawing): It is a binary ﬁle format meta

data related with various open data-sets. It also includes

geometric data information such as maps to deﬁne locations

and corresponding photos. Data sets such as road networks,

transportation bikeways, parking etc. are deﬁned in this format.

3) JSON (Java Script Object Notation): Java Script Object

Notation- JSON is one of the format which is easy to read

for any programming language. This ﬁle format has been

used by Ottawa, Surrey, Vancouver, Toronto and Waterloo for

listing various data-sets such as Trafﬁc Data (Ottawa), Park

Lights (Surrey), Bicycle Stations (Toronto), Business License

(Vancouver) etc.

4) KML (Keyhole Markup Language): Keyhole Markup

Language is an XML notation for representation of geographic

/geospatial information related with any data-sets for example

trafﬁc cameras location, transport route information, trafﬁc

count, intersection location, parking location etc.

5) SHP (Shapeﬁle): It is one of the most widely used

format for geospatial data representation speciﬁcally for geo-

graphic information system (GIS) software. Thus all the data-

sets of various cities which involved with GIS software to de-

ﬁne them more precisely, are essential to write in this format.

Thus the data-sets related with transportation or any service

location (health, recreation, parking) etc. are represented in

this format.

6) XLS (Microsoft Excel Spreadsheet): Many of the data-

sets are available in XLS formats which can be directly used

with correct description given by each columns. It is one of the

format which is easily understood by users. Data sets related

with elections, city boundaries, events etc. are deﬁned in this

format.

7) XML (Extensible Mark-up Language): It is the most

commonly used ﬁle format for data exchange as it keeps

the exact structure of the data. It also gives opportunity to

developers to divide and modify different parts of the ﬁle.

Various data-sets of different cities like city transit routes and

schedule, trafﬁc cameras, job opportunities etc. are represented

in this format.

B. Open Data-sets of Calgary

According to the city of Calgary, open data is deﬁned as

the information gathered by government on citizen’s behalf

also including their personal information, which is relevant to

use for any purpose including commercial. This information

can be found in different data-sets on the website. Users are

granted a non-exclusive licence to change the data or modify it

according to their own needs but should follow the terms and

conditions deﬁned as “open data catalogue terms of use” on the

city’s website [22]. Transparency of this data is the key factor

to promote accountability and provide useful information to

citizen about their government and their personal needs. The

main purpose of this open data is for the public to explore the

whole information regarding city on a single web link. This

data is categorized in different data-sets which are available

in alphabetical order [15] or in different categories. This data

is extracted by different department such as transport, hydro,

public security, city welfare societies etc. The main purpose

to cover all these sectors of a city is to give an opportunity to

reuse this diversiﬁed data in innovative way by citizens and

other organizations.

There are total 12 categories which are related with social,

educational and business areas of citizens and are also based

on government activities in these areas. Various data-sets are

deﬁned under these categories and data is given in different

formats as explained below:

•Administrative Boundaries: It includes data related with

the city, community, election wards and natural sites

boundaries (parks, rivers). The data is deﬁned mainly in

DWG, SHP, KML and XML formats.

•Census Information: This category deﬁnes census data

for residential units and total population count in those

areas along with the area names. This data is given by

community district and by wards from the year 1999-

2015. The data is given in CSV, DWG, SHP, KML and

XML format.

http://www.ieee.org/publications_standards/publications/rights/index.html for more information.

•City Facilities: This category includes data for public

provision, thus the data-sets under this category are

park amenity equipment, parks monuments, playground

equipment, sport equipment, sport surfaces etc. This data

is also deﬁned in DWG, SHP, KML, XML formats.

•City of Calgary 2013 election information: It deﬁnes the

city’s election information in three different data-sets as

2013 election results by station (XLS and XML), 2013

election results companion guide (XML and DOCX),

2013 election summary results (XML and FILE).

•City of Calgary Human Resources: This category deﬁnes

data related with the career opportunities within the city

which helps users to explore different career options as

per their needs and skills. This data is available in XML,

URL formats.

•City of Calgary News Feed: It describes data-sets related

with various newsroom of the city in XML, URL formats.

This category has the least downloaded data-sets number

as only 33 in the month of June 2016 as per data available

in July 2016.

•City Services: It emphasis on various emergency facilities

provided by different government bodies within the city

such as 311 customer satisfaction, ﬁre emergency, ﬁre

station locations and services etc.

•Environmental: It includes various data-sets mainly as

habitat, hydrology, natural areas, parks water delivery,

waste recycling facility, water features, water single

family consumption, land use information. The data is

available in DWG, SHP, KML, XML formats.

•Geospatial Reference: This category contains only one

data-set i.e. high precision network which deﬁnes a con-

trol network within the city for its development, surveying

and mapping. This is monitored by “ﬁeld surveying

service division”. It is available in XML and PDF format.

•311 Requests: This category has data-sets such as 311

call center activity, march 2015 public service requests by

community, road service requests. This data is available

in CSV, KML, SHP and XML formats.

•Subdivision and Development Appeal Board Rulings:

This category contains Subdivision and Development Ap-

peal Board Rulings for 2014-2016. The data is available

in XML format. It gives a complete view of all the

hearings. Each hearing has a unique ﬁle number and

also a appeal and decision number. The ﬁle includes a

summary of hearings, their reason, place and date etc.

•Transportation: This is the last category which has maxi-

mum data-sets describing all information related with city

transportation such as road network, trafﬁc volume, trafﬁc

cameras, truck routes etc. Data is deﬁned in CSV, XML,

SHP, KML, DWG under this category. This category has

maximum download number as 2573 in the month of

June 2016 as deﬁned by the data available in July 2016.

Furthermore, RSS feeds for these data-sets are available

online and links to Google maps and bing maps are available

in case of geo-spatial data-sets. The website also have a

few sections to involve the citizens to have their reviews on

the available data-sets. There is a “discussion forum” and a

“citizen dashboard” for public to write their ideas about the

data-sets to improve existing categories.

There is one major drawback of the data available and

that is incompleteness of data i.e. data-sets include only the

sampled data. For instance the data set “trafﬁc cameras” under

“transportation” category has only 77 total entries in CSV

ﬁle. This ﬁle includes the information about the location of

the trafﬁc cameras along with the reference image but from

researcher point of view or even for commercial use, this data

is not enough to explore it with proper results. This is a prime

challenge for the concerned authorities.

C. Open Data-sets of Halifax

Halifax (Halifax Regional Municipality-HRM) is a new

name in the ﬁeld of open data. It deﬁnes the data as “something

for everyone”, which means that the data is available for public

including technical and non-technical users. The data is man-

aged by ESRI’s ArcGIS (Aeronautical Reconnaissance Cover-

age Geographic Information System) Open Data platform and

is available in different data-sets which can be accessed on [23]

but these data-sets are quite scattered as they are not segregated

either alphabetically or clubbed in categories for easy lookup.

Only 33 data-sets are deﬁned as open-data catalogues [21]

which are named as zoning boundary, transit areas rates, trails,

street centrelines, soild waste collection areas, residents asso-

ciation area rates, recreation area rates, local improvements

area rates, HRP parks, community boundaries, ﬁre protection

area rates, crime, civic addresses, by-law areas, bus-routes,

building symbols, building permits, building outlines, BID area

rates, HRM park recreation features, contours 5m, bus stops,

parking meters, tax designation, transportation area rates,

spot heights, pre-amalgamation boundaries, polling districts,

polling division and community council boundaries. All these

data-sets are avaibale in CSV, KML and Shapeﬁle formats.

Furthermore, the city of Halifax has failed to bring much

variety into the categories but there are data-sets such as

data deﬁned by transportation department that contains enough

data for users (citizens, researchers, analysts, developers) to

extract useful information as per their needs. Thus the city has

deﬁnitely provided quality data having considerable number of

entries in most of the data-sets. This data is easy to use by

citizens, researchers and analysts as almost all data-sets are

deﬁned in tabular format. Also different APIs (Application

Programming Interface) are available for software developers

to easily access the data directly. A lot of detailing about

the attributes, data-sets and the creation of data-sets has been

provided as metadata.

D. Open Data-sets of Surrey

The city of Surrey in the province British Columbia has

deﬁned the open data to be an idea according to which some

data must be available for every one free of cost and can be

used and republished. The data is available worldwide under

the open non-exclusive license provided by the City of Surrey

and governed by the laws of province of British Columbia and

the applicable laws of Canada which allows the user to copy,

modify, reuse, publish and translate the data without giving

http://www.ieee.org/publications_standards/publications/rights/index.html for more information.

any warranty over the errors, omissions and completeness of

the data. The objective of the city to promote open data is

to empower citizens with a good quality data, help small

businesses ﬂourish, build a chance to develop its health and

education facilities, economic productivity and create more

scope for scientiﬁc research. Moreover the city of Surrey also

expects that a useful research or data evaluation done on this

data could come handy for the city in future. The city has taken

the help of open data portal platform CKAN (Comprehensive

Knowledge Archive Network) for maintaining its open data.

Surrey has broadly classiﬁed its 325 data-sets among 12

categories which are explained as follows:

•Business and Economy: It has mainly 11 data-sets which

are business licenses, population estimation, employment

in arts, culture, individuals with low income, land in

food production, availability of employment, businesses

by sector, employees by sector, rental market, business

improvement areas, restaurants and majority of these

data-sets are available in CSV formats.

•Community Services: The data-sets under this category

are places of interest (available in CSV), licensed child

care (in CSV), low cost and free resources (in CSV,

KML, FGDB), registration in city programs (in CSV),

social housing (CSV), schools (available in DWG, FGDB,

KML, JSON, API), garbage recycling collection days

(available in DWG, FGDB, KML, JSON, API) and

collection route boundaries (available in DWG, FGDB,

KML, JSON, API).

•Environment: It has various data-sets related with en-

vironmental bodies such as water consumption, trees

planted, parks, drainage water bodies, drainage ﬂood

control, ecosystem sites, community waste etc. and the

majority of the data-sets are available in CSV formats

thus easy to understand and use by the users.

•Finance: It includes three major data-sets namely city

spending on public art, city tax base and city funding

on beautiﬁcation projects and all these three data-sets are

available in CSV format.

•Health and Safety: It includes data-sets for public health

based facilities such as availability of doctors, crime and

collision incidents and criminal offenses. All of these

data-sets are available in CSV formats thus easy to

explore by public.

•Infrastructure: It is mainly deﬁned to give the idea of

whole network connectivity within the city such as water

supply, sanitary manholes, sanitary valves, signs etc.

Almost all of these data-sets are deﬁned in the formats

which are speciﬁcally built to locate the geographic

location of the entity such as KML, JSON, DWG, FGDB.

•Land Use and Development: It is built to deﬁne pro-

portion of land utilization for different purposes such as

buildings, farming, urban centers etc. This data is need to

be deﬁned with exact location thus the formats which are

used for these data-sets are DWG, FGDB, KML, JSON,

API.

•Recreation and Culture: It includes data-sets as heritage

sites (CSV), public art (CSV), arts and culture groups

(CSV), youth centered events (CSV), events (JSON) and

heritage routes (available in CSV, FGDB, KML, JSON,

API ).

•Transportation: It deﬁnes various data-sets related with

trafﬁc network within the city such as trafﬁc cameras

(CSV), trafﬁc signals (CSV, JSON, KML, DWG), poles

(CSV, JSON, KML, DWG), railway crossing (CSV,

JSON, KML, DWG), trafﬁc count (CSV), etc.

Thus Surrey has surely tried to achieve variety in its data-

sets and has covered many different domains. Further a lot of

serious efforts have been committed by the city to build and

maintain this much amount of data.

E. Open Data-sets of Waterloo

The city of waterloo has maintained a very good quality

of open data covering all the aspects of open data. The data

is open to everyone irrespective of the region, age, race or

community. Hence, the open data is purely non-discriminatory.

The work done by the city of Waterloo to collect and organize

the data is clearly remarkable in contrast to other Ontario cities

like Toronto or Ottawa. Waterloo has focused on maintaining

the variety as well as the volume in the city open data. The

city has provided access to 13 categories which further have

various data-sets. These categories are explained below:

•Events: This category contains data-sets related to differ-

ent events in the city on different dates along with loca-

tions helping the public to plan their activities according

to their interests. The data available in these data-sets is

provided in spreadsheet format.

•Base Data: It mainly has data-sets as buildings, railway

contours 2012 city boundary historical, addresses and

roads which are available in spreadsheet, KML and SHP

ﬁle format.

•Boundaries: It is having various data-sets such as city

boundary, polling 2014, wards 2014, wards, 2010, neigh-

borhood associations, district plans and all are available

in spreadsheet, KML, shapeﬁle format.

•Closures: This category is available in spreadsheet, KML

and SHP ﬁle. The spreadsheet consists with only sample

data with a very few entries. It gives information re-

garding closure name (sidewalk, road, intersection), street

name, date for closure and some speciﬁc information as

“sidewalk closed- please use other side of street” to for

user’s convenience.

•Community: It has four data-sets which are community

access bikeshare stations, neighborhood matching fund,

neighborhood associations, older adult housing directory.

All are available in spreadsheet, KML and SHP format.

The ﬁrst data-set gives complete information regarding

bike station such as station name, location, access time

and bike counts etc. The second data-sets deﬁnes projects

name which are focusing on one community such as arts,

education, environment, history, public safety, community

building or recreation. They have received neighborhood

fund matching grant. The third data-set describes the

boundaries within neighborhood association within the

http://www.ieee.org/publications_standards/publications/rights/index.html for more information.

city. The last data-sets deﬁnes information about residen-

tial areas for older adults in the city.

•Elections: It is having 19 data-sets equipped with data

from different wards related to candidates, results etc for

different years in the city.

•Environment: It is mainly for the users to explore the

current status of the data and help in maintaining sus-

tainability of the resources. The data is available in

spreadsheet, KML, SHP ﬁle.

•Heritage: It deﬁnes data-sets as walkability network,

heritage buildings, city boundary historical, historical

streets and all of these data-sets are avaiable in three

formats- spreadsheet, KML, SHP ﬁle.

•Parks and Recreation: It has 9 data-sets namely parks,

bicycle parking, bylaw parking infraction, parking lots,

sports ﬁeld and diamonds, trails, playground, recreation

points, outdoor rinks. All these data-sets are easily ac-

cessible by all users as it is available in simple tabular

format too.

•Points of Interest: It is available in spreadsheet, SHP,

KML formats and it contains the data-sets which describe

the points of interest in this city like important dates and

places.

•Records: Its data is also in the same three formats as

deﬁne above.

•Transportation: It has maximum data-sets as a total of 23

which are related with the transportation activities within

the city such as bicycle counts, walkability network,

major transportation routes, parking etc.

Thus each of the mentioned categories have subsets falling

under that particular category which sums up to 122 data-sets

overall.

F. Open Data-sets of Ottawa

The capital city of Canada has provided access to its open

data with the help of CKAN (Comprehensive Knowledge

Archive Network) and it can be downloaded in multiple for-

mats as well as the data can be fetched by using API functions

provided on the website which ensures that every time the

API is hit, the most recently updated data is fetched. The

city of Ottawa provides an open non-exclusive license to the

user worldwide to use, distribute and modify the data without

granting any proprietary rights to the user. This user license

is governed by the laws of the Province of Ontario. However

the city does not give any warranty for the completeness or

accuracy of the data.

The city of Ottawa has listed 15 organizations which have

helped the city to build and maintain this data. These organiza-

tions are- City Clerk and Solicitor (7 Data-sets), Community

and Social Services (8 Data-sets), Crime Prevention Ottawa

(1 Data-set), Emergency and Protective Services (2 Data-

sets), Environmental Services (5 Data-sets), Financial Services

(2 Data-sets), Human Resources (3 Data-sets), Infrastructure

Services (35 Data-sets), OC Transpo (3 Data-sets), Ottawa

Public Library (5 Data-sets), Parks, Recreation and Cultural

Services (23 Data-sets), Planning and Growth Management

(12 Data-sets), Ottawa Public Health (3 Data-sets), Public

Works (7 Data-sets), Service Ottawa (7 Datasets). All these

organizations belong to different domains and have provided

data according to that particular domain. The data is placed

under 9 groups or categories namely Business and Economy,

City Hall,Demographics,Environment,Geography and Maps,

Health and Safety,Living,Planning and Development and

Transportation. These 9 categories contain 129 data-sets from

different sectors ensuring the variety in the open data. Those

are explained as follows:

•Business and Economy: This is the ﬁrst category which

has deﬁned 2 data-sets namely business improvement

areas (available in SHP, GeoJSON formats) and Job

Opportunity (available in XML, JSON format).

•City Hall: It has information related with the elections,

voting places and nominated candidates in SHP, CSV,

GeoJSON and CSV formats respectively.

•Demographics: This category has mainly two data-sets

providing data for 311 monthly service requests submis-

sion from 2013-2014 (available in XLS, XLSx formats)

and ward data from census for 2006 and 2011 (available

in CSV format).

•Environment: It mainly emphasise on natural bodies

within the city as water, rivers, beach water, water quality,

street trees and various formats are used for these data-

sets such as XML, DWG, CSV, SHP, GeoJSON for water,

XML, DWG, CSV, KMZ, SHP, GeoJSON for rivers and

XLS for beach water sampling data, CSV format for

water quality, KMZ, SHP, CSV, XML for street trees and

XLS for drinking water.

•Geography and Maps: It deﬁnes various routes with exact

locations for various means of transportation such as bus,

rails, airports runways. It also has data-sets related with

beaches within city, also the sports ﬁeld, basketball, ten-

nis, volleyball courts, truck routes and pedestrian network

in all over the city. The main formats for these data-sets

are XML, DWG, KMZ, SHP, GeoJSON.

•Health and Safety: It mainly includes data related with

health clinics which is mainly in tabular format.

•Living: It deﬁnes the data for public facilities such as

cultural resources, garbage schedule, library, street food

vendors, library programs, library hours and locations,

museums etc.

•Planning and Development: It has main three data-sets

as large buildings, drainage and neighborhood names. All

these data-sets are avaiable in XML, DWG, KMZ, CSV,

SHP, GeoJSON formats.

•Transportation: It has the data-sets as O-train stations,

tracks, cycling network, OC-transpo schedule, parking

lots, truck routes, railway, trafﬁc data etc. The data related

with OC-Tranpo gives live changes in the schedule of

buses to the users.

Thus the city of Ottawa has diversiﬁed data however, as

stated above the city clearly states that it provides no warranty

of the completeness of the data which is pretty much clear by

looking at the data. The data entries range maximum up to a

few hundreds and with very less detailing. The city of Ottawa

has left a lot of room for the workers to make more progress

http://www.ieee.org/publications_standards/publications/rights/index.html for more information.

in building a good quality of city data.

The city of Ottawa has maintained the metadata for each

set describing the creation date as well as the last update for

the data-set. The city has not failed to deliver the details about

the dataset and its attributes or ﬁelds and also the frequency

of updates for each dataset and has also listed the accuracy

for each dataset.

G. Open Data-sets of Vancouver

The city of Vancouver deﬁnes open data as the the data

that people want, i.e., the data that is of the most interest to

the community. The notion of this project came into existence

when in May 2009, Vancouver City Council passed a project

named as Open3 which was to make data public for everyone

to explore and make changes as per their requirements. The

prime root for this draft was to do research to ﬁnd out

which data would be more useful for public such as legal,

public services, technical and business related data. After the

successful efforts, the city was able to launch its open data

website in September 2009 [19] and have been adding new

data-sets on the website since then. It is for public to use or

make changes as per the open government license deﬁned on

the website. The important thing to be noticed here is that this

city have not deﬁned any category for its data rather the data

is made available to public in data-sets. Those are on the city’s

website in alphabetical order. There are total 186 data-sets and

are related with social, business and government areas within

the city.

The ﬁrst data-set is accessible Parking that is available in

DWG, SHP, KML format. It deﬁnes all locations which is

meant for parking. The next data-set is parks, rivers. The

apartment recycling area in which data is deﬁned mainly in

SHP, KML formats. The next data-set is bike ways that is

available in DWG, SHP, KML. The data-set business license

deﬁnes all the business related license in CSV, XLS, JSON,

XML format. The next data-set is census local area proﬁle

2001, 2006, 2011 including data for public provision. This

data is deﬁned in CSV, XLS formats. The next data-set is

city boundaries which is available in DWG, SHP, KML.

Further alphabetically deﬁned data-sets are community centers

(CSV, DWG, SHP, KML, XLS), community gardens and food

trees (CSV, XLS), crime (CSV, XLS, JSON, SHP), drinking

fountains (DWG, SHP, KML, CSV, XLS, JSON), employee

remuneration and expenses (CSV, XLS), elementary school

boundaries (DWG, SHP, KML, XML), food vendors (CSV,

KML, XLS), garbage collection schedule zones (DWG, SHP,

KML), heritage property (CSV, KML, XLS), intersections

(DWG, SHP, KML), libraries (CSV, DWG, KML, SHP, XLS),

local area boundary (CSV, DWG, XLS, SHP), motorcycle

parking (DWG, KML, SHP), municipal election results (CSV,

XLS), noise control areas (DWG, KML, SHP), Olympic city

site (DWG, KML, SHP), one way streets (DWG, KML,

SHP), parks listing (CSV, XLS, XML), parking meter (DWG,

KML, SHP), public art series (DWG, KML, SHP), public

streets (DWG, KML, SHP), public washrooms (CSV, XLS,

KML), railway (KML, SHP), road ahead closures (DWG,

KML, SHP), road ahead under construction (DWG, KML,

SHP), sanitary mains (DWG, KML, SHP), sanitary manhole

(DWG, KML, SHP), schools (CSV, XLS, DWG, KML, SHP),

street lighting pole (DWG, KML, SHP), street trees (CSV,

XLS, JSON, XML), trafﬁc count directional (DWG, KML,

SHP), trafﬁc signals (DWG, KML, SHP), truck route (SHP),

voting places (CSV, XLS, KML, SHP), water control valves

(DWG, KML, SHP), weekend play-ﬁeld status (CSV, XLS,

JSON, XML), water transmission mains (DWG, KML, SHP),

zoning districts and labels (DWG, KML, SHP). The data is

available in different formats and most of the data-sets have

the entries in thousands which is good for researchers and also

for analysts for evaluation purpose.

H. Open Data-sets of Toronto

Toronto, the largest city of Canada is working alongside

Montreal, Vancouver, Ottawa and Edmonton on improving

the quality standards and maintenance of open city data. This

project is being called G4Plus. Toronto has deﬁnitely achieved

a good rating in developing tools over its city open data but

it still has not provided the users with a good volume of data.

The city has provided access to 214 data-sets which are deﬁned

under ten categories which are explained as follows:

•Business: This is the ﬁrst category which has mainly

ﬁve data-sets namely bicycle shops (available in SHP

ﬁle), business improvement areas (SHP ﬁle), economic

indicators (excel ﬁle), Toronto economic bulletin(excel

ﬁle), Toronto employment survey summary table (excel

ﬁle).

•Community Services: It has seven data-sets which are

deﬁned to give information to public for various social

activities such as human right ofﬁce service statistics,

licensed child care centers, marriage licensed statistics,

Ontario early year centers (Toronto), school locations,

social housing, sports and recreation, Toronto public

library branch locations. These data-sets are deﬁned in

different formats such as CSV, Excel ﬁle, SHP, KML etc.

•Culture and Tourism: This category is deﬁned with six

data-sets which gives useful information to citizens and

tourists about city’s cultural life. The data-sets which are

involved with this category are bicycle stations (XML,

JSON), cultural hot-spots (SHP), festival and events

(XML), places of interest and Toronto attractions (excel,

SHP), places of worship (SHP), sports and recreation

(excel).

•Development and Infrastructure: It deﬁnes the city’s

infrastructure and also give an idea of construction-

standards within the city. Main data-sets under this cat-

egory are building permits (available in CSV, XML),

heritage districts (SHP), intersection ﬁle (SHP), urban

centers (DWG, FGDB, KML, JSON, API), farming pro-

tection development permit area (DWG, FGDB, KML,

JSON, API), town center land use plan( FGDB, KML,

JSON, API), legal plan boundaries (DWG, FGDB, KML,

JSON, API), agriculture land reserve (DWG, FGDB,

KML, JSON, API).

•Environment: This category includes data-sets related

with various environmental activities like chemical track-

http://www.ieee.org/publications_standards/publications/rights/index.html for more information.

ing, renewable energy installation and many more. These

data-sets are available in SHP, excel, XML formats.

•Finance: It deﬁnes data-sets which provides city’s capital

budget (excel ﬁle), tax information (excel ﬁle), parking

ticket price (CSV format), water billing (excel ﬁle) etc.

•Health: This category is mainly deﬁned to give essential

information related with various health services such as

ambulance station locations, care centers etc.

•Parks and Recreation: This category is mainly design to

give a brief knowledge of parks location and recreation

activities within cities. The main data-sets are forest and

land cover, parks, parks drinking fountains.

•Public Safety: It has data-sets for public safety related

information such as ﬁre station location, police station

locations, Also it has data-sets called road restriction to

provide safety instructions to public.

•Transportation: This is the last category which has max-

imum number of data-sets. Those are trafﬁc cameras

(CSV), trafﬁc signals (CSV, DWG, FGDB, KML, JSON,

API), railway crossing (CSV, FGDB, KML, JSON, API),

poles (CSV, DWG, FGDB, KML, JSON, API), mode of

travel to work (CSV), trafﬁc counts 2013-2015 (CSV),

trafﬁc volume (CSV), walking routes (DWG, FGDB,

KML, JSON, API), truck routes (DWG, FGDB, KML,

JSON, API).

Furthermore, as explained above various data-sets are de-

ﬁned under these categories for users to explore complete

information of the city. The users are given access to all data-

sets along with a very descriptive metadata for that particular

data-set having information about the data itself, data-set

publish date, update frequency, data owner and the available

formats. The data is updated frequently and API (Application

Programming Interface) functions have also been provided by

the organizations to get the latest data with a single API hit.

As discussed in the conclusion of Section II, Halifax has

left a plenty of room to be ﬁlled both on maintaining quality

open data. The best practice every city has followed is to

provide a descriptive metadata containing details about the

dataset, update frequency, creation date, attribute description

etc. CKAN (Comprehensive Knowledge Archive Network) is

helping most of the cities to maintain its data and the license

for all the cities is governed by laws of respective provinces.

IV. TOO LS DE VE LO PE D OVE R OPE N DATA OF DIFFERENT

CIT IE S

Data visualization is a very important aspect in this open

data study. The raw data has a very limited utility for a user

who is not working on processing and analysis of this data.

Therefore, there must be a method to create or derive mean-

ingful data from this raw data. This data needs pre-processing

and analysis to get inferences from this data. However the

inferences made can best be presented in form of visualizations

and comparisons. Hence almost every city has worked on

building applications aiming at doing the analysis part and

then visualizing the analysed data. Not only the cities has

built applications but also users has contributed by working on

data-sets from different categories and getting useful results.

Most of these cities has listed the applications built on its

city open data and have opted various visualization tools and

methods. Out of all those, one of the most widely used is

information graphics (Infographics) which is the combined

version of illustration methods and text representation. It is

good enough to give a clear idea to any user. The basis for

each application and visualization method is converting the

raw data into a form such that it is understood by a tool

on which the user is working. For example, a user Lauren

Archer has used the Garbage and Recycling Data provided by

the City of Toronto to produce a Web App named Garbage

and Recycling Day Google Calendars having visualisations in

form of Google Calendars [24]. The user has managed the raw

data by converting it into a data that can be directly used into

Google calendars application and has developed a schedule for

garbage and recycling days which can be downloaded by other

users. The following sub-sections illustrate the tools developed

by the respective cities on city open data.

A. Tools Developed over Calgary’s Open Data

There are various data-visualization tools which are formu-

lated with the city’s open data. Sports is the one of highlighted

area within the city as the city of Calgary is one of the sports

rich city which is proved by the fact that sport business group,

London shortlisted Calgary as “ultimate sport city 2016” in

the month of January, 2016. Thus it has attracted developers’

attentions and they made one applications which is quite

famous in the city, called Sportsity. This is meant to give

the information about various sports ﬁelds within the city all

in one place. The pictorial view of one of the application

Sportsity is shown in (Figure 1(a)) which is basically designed

to help users to ﬁnd out any sport court or athletic park in the

city and also provides the user with the directions with the help

of integrated Google Maps in the application. This application

uses City of Calgary’s open dataset “city amenities” to ﬁgure

out various sports recreation centres for soccer, basketball,

cricket, golf, tennis and many more available throughout the

city. It also lists the reviews provided by the visitors for each

location and also provides the user with an option to write a

review.

Another tool developed with city’s open data is Calgary

Trafﬁc Alerts which is designed to give live trafﬁc alerts to

users. It includes information such as notiﬁcation alerts for

trafﬁc incidents as accidents, construction etc., paid and unpaid

parking lots, construction closures detours, trafﬁc cameras

location. Similarly work has been done on other data-sets as

well to develop tools such as +15 Walkway,TransitGo and

Live Transit.

B. Tools Developed over Halifax’s Open Data

The city of Halifax worked progressively towards develop-

ing tools over its open data. The city has conducted the open

data application contest named “Apps4Halifax” with the help

of IBM where the users are open to post their ideas as well as

submit their developed tools [25]. By the end of this contest,

a winner is decided amongst both the categories-Ideas and

Apps. In the 2013-14 contest, a total of 275 ideas and 38 apps

http://www.ieee.org/publications_standards/publications/rights/index.html for more information.

(a) (b) (c)

(d) (e) (f)

Fig. 1: Tools developed on open data of different cities. (a) Sportsity Application: The city of Calgary. (b) Low Cost and

Free Resources Application: The city of Surrey. (c) PingStreet Toronto Application: The city of Waterloo. (d) Save the Rain

Application: The city of Ottawa. (e) PayByPhone Application: The city of Vancouver. (f) Wellbeing Toronto Application: The

city of Toronto.

were submitted online. The major sponsors of this contest were

IBM (Main title sponsor), Esri Canada (Challenge sponsor),

Global Halifax (Media Sponsor) and Telus (Category sponsor).

The Ideas and Apps were submitted under 4 broad categories

namely Your City, Go Green, Live It Up and Keep’er Movin’.

One of the winners in the idea category was Garbage When?

which uses the GPS of the mobile device and based on the

location it notiﬁes the user about the garbage day and also

sends notiﬁcations in case of cancellations. The app which

won in the Go Green category was Haliﬁcation which is again

based on municipal notiﬁcations for the city residents. The

residents can choose from a number of subscriptions such

as crime, power outages, school closures, weather warnings

and trafﬁc feeds. The sources of these alerts are the Open

data catalogue of Halifax city, Twitter, Environment Canada

and Halifax.ca. The data-sets used by this app from the

Halifax data catalogue are “civic addresses”, “solid waste

collection areas” and “crime statistics”. A contest ensures

more participation and interest from the users as it instils the

competitive spirit amongst the participants due to which they

thrive for achieving the best. Hence it a progressive step by

the city of Halifax for promoting the tool development over

its open data.

C. Tools Developed over Surrey’s Open Data

There are various applications which are built with various

open data-sets available on the open data website of the city.

Out of those application, one is built on the idea of the

Surrey’s poverty reduction plan i.e. which was made up by

Surrey’s planning and development department along with the

engineering department. This plan was based on the vision to

make ”low cost and free resources” available to every citizen

of Surrey. The application and its name is based on the same

concept. The pictorial view of the application is shown in

Figure 1(b), the complete view of one of the application is

shown which is to ﬁnd out the location of low cost services

as food, health services etc. The system provides users to apply

ﬁlter as per their needs and thus shows the result accordingly.

There are many other tools which are developed from the

various open data-sets to help people in various ways. The

http://www.ieee.org/publications_standards/publications/rights/index.html for more information.

most popular tools are My Surrey App,Surrey Request App,

Rethink Waste Mobile App,Building Inspection Request App,

COSMOS App,Surrey Libraries App. One of the applica-

tion that uses variety of data-sets is My Surrey App as it

gives informative access to users to have a almost complete

information about the city. It is the combination of all the

other applications that are mentioned above. The main page

includes news, point of interest, events, jobs, Surrey request,

COSMOS, rethink waste, library, parking, bike routes etc. It

has also introduced new services like Contact Surrey, which

allows users can write their questions and they can get answers

for those in pilot project within the city that is handled by

IBM Watson technology. This application has gained a lot of

popularity within the city of Surrey.

D. Tools Developed over Waterloo’s Open Data

Waterloo uses different mobile applications for users to

visualize the data which is collected from different government

bodies and from the citizens of the city. As the data collected

is very complex and unstructured, so software applications are

required to re-use this data in structured manner before giving

to users to explore it. One of the famous mobile application

which uses city’s open data is Pingstreet (Figure 1(c)), which

is designed for daily interaction of citizens and different

government organization, social media etc. It is quite popular

within the city as it provides real time access to various

activities such as road closures, events, garbage and recycling,

overnight parking etc. It is a location based discovery tool

and thus all information is delivered directly to user’s mobile

devices without any cost cost.

Waterloo park ﬁnder is an another tool that is using open

data-set parks that comes under Parks and Recreation category

to help users to ﬁnd out the exact location of parks within city.

There are three options to do the search easily on the applica-

tion i.e. search can be made by name (albert green, Alexandra

lot etc.) of the park or by type of park (neighborhood park,

environmental reserves, special agreement parkland, culturally

signiﬁcant parks etc.) or by facilities (benches, playground,

hydro, water service, etc.) included in the park. After this

selection the next page will show all the exact location of

the park. It can be seen as a small icon, which on selection

provides a short description about the park to the user. Another

popular tool is Public Art Waterloo which is developed to

give a complete knowledge about public art and its location

within the city. It also gives information about nearby public

art locations.

E. Tools Developed over Ottawa’s Open Data

There are more than 60 applications which are developed

based upon the open data of Ottawa by the users participating

in Ottawa Open Data App Contest sponsored by Microsoft.

There are four categories under which these applications were

developed [24]. Those are listed as follows:

•On the Move (Sponsored by Telus)

•Having Fun (Sponsored by Nova Networks)

•Your City (Sponsored by CGI)

•Data Analysis and Visualization (Sponsored by Oracle)

All these categories have a few applications to give simple

view of information as per their needs. The application that

has pleased the users is Save the Rain. It uses the open data-

sets Drinking Water Summary and Ontario Well Record Data.

The signiﬁcance of this application is to make the users realise

that how much rain water could be harvested over their roof

tops in a year. The reports generated from this application

is amazing the users and the users like it as well. Moreover

this tool has been equipped with an attractive user interface

as shown in Figure 1(d).

There are many other tools developed over Ottawa’s open

data-sets in the contest. Another example of such tools is

Ottawa events which is designed to have a complete knowl-

edge of Ottawa’s present and upcoming events. The events are

grouped together on the basis of date, month and week. It also

shows the address and tickets for each events. The main menu

of this application gives two options to users to explore events

either by event type (dance, fair/festival, ﬁlm/new media etc.)

or by location (Ottawa urban area, Ottawa rural area etc.). It

also gives a short description about the event such as dance

party timing, meal menu etc. Thus it is good way to explore

social activities within the city. There are many other applica-

tions like Ottawa Garbage collecting schedule,Recreation in

Ottawa,OC Transpo Tracker,Ottawa Construction permits,

Environmental Inspection App,Libraries Ottawa,Ottawa 311

Service Request etc. which are using various open data-sets to

give a useful information to citizens.

F. Tools Developed over Vancouver’s Open Data

There are main four mobile applications developed by open

data of Vancouver namely VanConnect, VanCollect, VanGolf,

PayByPhone. These are meant to provide required updated

information to the users such as road closures, emergency

alerts and many more. PayByPhone is a very useful tool with

maximum downloads by users that has been released by the

City of Vancouver that allows the user to pay for the street

parking by phone and also extend the parking via call or text.

The user is charged only for the speciﬁc time he occupies the

parking slot which costs less as compared to a speciﬁc time

interval charge. There is also a provision to set alerts for the

expiry of the parking ticket and also lets the user to get the

receipts on the phone. The user interface of the application

looks as shown in Figure 1(e).

City of Vancouver has developed another application Van-

connect that proves its utility to build an interaction bridge

between Vancouver city hall and the citizens of the city. It

allows the users to submit there requests as per their need

or they can submit any complaints regarding garbage, street

light, trafﬁc light, abandoned vehicle etc. It gives users various

options to clarify their issues such as type, location, time and

description and users can also upload a pictures for the same. It

also updates users with news, emergency information etc. One

of the biggest advantage of this application is that it connects

users with Vancouver city hall 24X7.

G. Tools Developed over Toronto’s Open Data

The city of Toronto has made a huge progress in terms of

visualisations of its available data. Many different organisa-

http://www.ieee.org/publications_standards/publications/rights/index.html for more information.

tions have come forward to utilise the open data and make

inferences from it and use various kinds of visualisations

for representation. The city has listed a number of mobile

applications as well as web applications which have used

the city data for visualisations. For example, a user Lauren

Archer has used the Garbage and Recycling Data provided

by the city to produce a Web Application named Garbage

and Recycling Day Google Calendars having visualisations in

form of Google Calendars [26]. The user has managed the raw

data by converting it into a data that can be directly used into

Google calendars application and has developed a schedule for

garbage and recycling days which can be downloaded by other

users. Similarly other users have contributed and worked on

various data-sets at different platforms to develop visualisation

tools for the given data.

City of Toronto has ofﬁcially released a web based map

visualisation application that is designed to ensure as well as

evaluate the city’s well being and is thus named as Wellbeing

Toronto (WT) as shown in Figure 1(f). This visualisation tool is

targeted for residents who need to have a good understanding

of the area and communities they are living in and working

and also for businesses or organizations that require parameter

evaluations in order to be informed about their customers.

WT provides a central platform for discussion of issues at

neighbourhood level. It covers multiple domains such as

transportation, crime, safety, education, culture etc to select

indicators or parameters and provides an option to select the

reference period. WT allows to select parameters from listed

domains within the framework with a ﬂexibility of changing

the weight of a particular parameter and provide corresponding

data for the users. It does not provide the open data in its raw

form but in a business processed form which is more usable

for the user. It also gives the user an option to use WT as a

basis of developing other tools by using indicators in WT.

One more tool build on Toronto’s open data is Open Toronto

which is build to provide an easy access to Events and

Festivals information within the city of Toronto. It allows

users to browse the events and festivals on a particular date

or in a particular months as it gives three options to users

for browsing the data i.e. all, today and selected date. Thus

as per the predeﬁned information the next will show the

results accordingly. Users can add information to their personal

calenders in their mobile phones. Also they can share the

information to their friends and relatives by sending them

emails, SMS etc.

H. Summary

From the discussion about tools developed by different

cities, it can be deduced that researchers, business organ-

isations, city authorities and users as well understand the

importance of application development on city’s open data.

All cities discussed above have worked upon developing tools

on open data either directly or through the users. Toronto

leads all the seven city in this department as not only the

users have participated in enormous numbers but also city of

Toronto has developed extremely useful tools like Wellbeing

Toronto that has proved its utility in the users, businesses and

researchers. It can also be concluded about these tools that

most of the tools developed are using Maps as its basis for

visualisation and lesser of previously used methods like graphs

and charts as Maps look more presentable to display the useful

information. This analysis also leaves scope for developers and

organizations to set foot in and develop tools based on city

open data.

V. OP EN DATA CHA LL EN GE S

This section talks about the open challenges for open data.

This includes mainly the open data challenges/problems for

academia and industries who want to work on it on a large

scale.

A. Research Challenges

Based on the discussion on open data-sets and its charac-

teristics so far, some research challenges can be drawn. This

sub-section addresses the shortcomings in the study of open

data for educational and research prospective. Today the var-

ious technical/non-technical organizations and also different

educational institutes are working on open data and trying to

ﬁgure out some dynamic way to deal with such a huge open

data. Researchers are trying to ﬁnd out that the solutions for

the following questions:

•How much data is available for the public to access and

view?

•Is the released open data useful enough for users

with different backgrounds (technical/non-technical pro-

fessionals etc.)?

•How can applications be developed in such a way that

visualization, usage and comparison of open data can be

made easy accessible and understandable to everyone?

•What amount of data and in which format should open

data in cities be opened to the public by governmental

and non-governmental organizations and how can they

manage this public data in an efﬁcient way?

There are limitations related to the access of this data as some

cities either did not publish the complete data sets or did not

make the open to the public. Some of the existing data-sets

are only available with a few lines of ﬁeld entries. To make

city data available (opened) completely there is a need to reﬁne

and bundle complete set of data in public APIs. The developers

should publish the software patches related with the APIs as

an open source so that the researchers can contribute to public

code projects.

B. Open Challenges for Integration of Open Data

Integration of this heterogeneous open data is a very pow-

erful approach. It allows to put the open data together across

various data-sets in such a way that it can be easily explored by

the users. As the section III has explained the various data-

sets available in different cities, it is quite understood that

every city is working independently in its own way to put data

available for users and therefore these data-sets have generally

not been designed to integrate together. The ﬁrst problem to

deal with integration process of this open data is a lack of

common open source platform to study this data.

http://www.ieee.org/publications_standards/publications/rights/index.html for more information.

TABLE I: Characteristics of Open Data and Tools/Applications Used

City

Name

Open Data Characteristics Visualization Tools/Applications Used

Calgary Availability, Non-Proprietary, Non-

Discriminatory, Timely Processed and

Updated

Sportsity, Calgary Trafc Alerts, +15 Walk-

way, TransitGo and Live Transit

Halifax Availability, Non-Proprietary, Non-

Discriminatory, Timely Processed and

Updated, Variety

Halication

Surrey Completeness, Availability, Non-

Proprietary, Non-Discriminatory, Timely

Processed and Updated

My Surrey App, Surrey Request App, Re-

think Waste Mobile App, Building Inspec-

tion Request App, COSMOS App, Surrey

Libraries App, My Surrey App, low cost

and free resources

Waterloo Completeness, Availability, Non-

Proprietary, Non-Discriminatory , Timely

Processed and Updated, Variety

Pingstreet, Waterloo park nder, Parks and

Recreation, Public Art Waterloo

Ottawa Availability, Non-Proprietary, Non-

Discriminatory, Timely Processed and

Updated

Ottawa Garbage collecting schedule,

Recreation in Ottawa, OC Transpo

Tracker, Ottawa Construction permits,

Environmental Inspection App, Libraries

Ottawa, Ottawa 311 Service Request,

Save the Rain

Vancouver Availability, Non-Proprietary, Non-

Discriminatory, Timely Processed and

Updated, Variety

VanConnect, VanCollect, VanGolf, Pay-

ByPhone

Toronto Availability, Non-Proprietary , Non-

Discriminatory, Timely Processed and

Updated

Garbage and Recycling Day Google Cal-

endars, Wellbeing Toronto (WT), Open

Toronto

Furthermore, the differences in formats (CSV, XML, DMG,

KML etc.) is the another problem in the integration of open

data sources. It is easy to download the data from the re-

spective websites of the cities but it difﬁcult and challenging

to recognize the common ﬁelds between data collected from

various cities. Moreover the characteristics of this open data

and tools/applications build on the data-sets are different in all

cities as mentioned in table I. Thus it is difﬁcult for a developer

to integrate the data and make a common visualization tool for

this huge open data. Also the diversity of characteristics and

tools used in these seven cities create usage difﬁculties for the

users.

Also the other kind of problems that are shown up for

the integration of open data may include improper data entry,

missing data or a lack of common attributes between data from

different sources. But on the high level view of integrated open

data may see these problems in a way that cannot be seen by

individual data-sets and thus lead to data quality improvements

without the need for extensive polishing.

C. Proposed Model : Data Wrapper

We discuss an example of the performed study of open data

in seven Canadian cities by extracting common information

regarding some data in these cities. The data ﬁles are shown

in Figure 2 which speciﬁes the three formats of same data-set

i.e. trafﬁc camera. We developed a common model called Data

Wrapper which parses various datasets from different domains

and with different structure and formats (CSV, XML, JSON)

and ﬁelds (latitude, longitude, id, image, location etc.) and

produce a uniﬁed output in XML format.Table II shows the

various data-sets ﬁelds used for trafﬁc cameras in a few cities

(Toronto, Ottawa and Surrey).

http://www.ieee.org/publications_standards/publications/rights/index.html for more information.

(a) (b)

Fig. 2: Different Formats of same data-set (Trafﬁc Camera). (a) CSV format for the city of Toronto. (b) XML format for city

of Ottawa. (c) JSON format for city of Surrey. (d) the combined output in XML format.

TABLE II: Data Wrapper Fields

City Name Data-set Format Parameters

Surrey Trafﬁc Camera JSON Location, Image, Rotation, Longitude, Latitude

Ottawa Trafﬁc Camera XML Id, LocationDesc, Longitude, Latitude

Toronto Trafﬁc Camera CSV Camera Number, Latitude, Longitude, Main Road, Cross

Street, Trafﬁc Image, Reference, Static Image

VI. CO NC LU SI ON

In this paper, the current status of seven Canadian cities have

been depicted with respect to open data. It closely represents

the open data-sets and open data tools in those cities. One

of the biggest advantage of this data is to use it for making

applications which keeps its users up-to-date for all activities

within cities and also in their neighbourhood. This data helps

to improve the lifestyle of citizens as there is feedback column

on each city’s websites to get reviews of citizens for data and

also to know about needs and ideas of citizens to improve the

data presentation. Thus it intensiﬁes citizen engagement.

Furthermore, the research on open data of seven cities

is quite complex. Users are inundated with this huge data.

As different cities have different data-sets and further which

are in various formats. Therefore to study this huge data on

one single platform is very tricky because of diversiﬁed data

collected from different cities. This is an open challenge for

researchers and for cities’ authorities as to bring all data-

sets in single format is the ﬁrst thing that researchers and

analysts have to build out and to work on the same data-sets,

the same formats are the biggest tasks for cities. Thus cities

have made this data to be opened for researchers, analysts, IT

http://www.ieee.org/publications_standards/publications/rights/index.html for more information.

companies to work on it and make useful tools for the city’s

social, cultural betterment and governmental, technological

development.

REF ER EN CE S

[1] D. Takaishi, H. Nishiyama, N. Kato, and R. Miura, “Towards energy

efﬁcient big data gathering in densely distributed sensor networks,” IEEE

Transactions on Emerging Topics in Computing, vol. 2, no. 3, pp. 388–

397, 2014.

[2] C. Perera, C. H. Liu, and S. Jayawardena, “The emerging Internet of

Things marketplace from an industrial perspective: A survey,” IEEE

Transactions on Emerging Topics in Computing, vol. 3, no. 4, pp. 585–

598, 2015.

[3] C. Millette and P. Hosein, “A consumer focused open data platform,”

in Proceedings of the 3rd MEC International Conference on Big Data

and Smart City, 2016, pp. 1–2.

[4] X. Hu, T. Chu, H. Chan, and V. Leung, “Vita: A crowdsensing-oriented

mobile cyber-physical system,” IEEE Transactions on Emerging Topics

in Computing, vol. 1, no. 1, pp. 148–165, 2013.

[5] Y. Tammisto and J. Lindman, “Open data business models,” in Proceed-

ings of the 34th Information Systems Seminar in Scandinavia, 2011.

[6] E. Lakomaa and J. Kallberg, “Open data as a foundation for innovation:

The enabling effect of free public sector information for entrepreneurs,”

IEEE Access, vol. 1, pp. pp. 558–563, 2013.

[7] C. Chan, “From open data to open innovation strategies: Creating

eservices using open government data,” in Proceedings of the 46th

Hawaii International Conference on System Sciences, 2013, pp. 1890

–1899.

[8] S. Qanbari, N. Rekabsaz, and S. Dustdar, “Open government data as

a service (godaas): Big data platform for mobile app developers,” in

Proceedings of the 3rd International Conference on Future Internet of

Things and Cloud, 2015, pp. 398 – 403.

[9] S. Djoko, P. Theresa, and M. Cook, “A framework for benchmarking

open government data efforts,” in Proceedings of the 47th Hawaii

International Conference on System Sciences, 2015, pp. 1896 – 1905.

[10] A. Ojo, E. Curry, and F. A. Zeleti, “A tale of open data innovations

in ﬁve smart cities,” in Proceedings of the 48th Hawaii International

Conference on System Sciences, 2015, pp. 2326 – 2335.

[11] T. Vrai, M. Varga, and K. Curko, “Effects and evaluation of open govern-

ment data initiative in croatia,” in Proceedings of the 39th International

Convention on Information and Communication Technology, 2016.

[12] C. Xu, D. Chu, and C. Li, “City event management system based on

multiple data source,” in Proceedings of the International Conference

on Service Science, 2015, pp. 169 – 173.

[13] K. Yamamoto, “Visualization of gis analytic for open big data in

environmental science,” in Proceedings of the International Conference

on Cloud Computing and Big Data, 2015, pp. 201 – 208.

[14] “Open government data principles,” https://public.resource.org, October

2016, [Online].

[15] “The City of Calgary-Open Data Catalogue-Datasets Alphabetical,”

https://data.calgary.ca/OpenData/Pages/DatasetListingAlphabetical.aspx,

May 2016, [Online].

[16] “Groups - Open Data Ottawa,” http://data.ottawa.ca/en/group, May 2016,

[Online].

[17] “Welcome - City of Surrey Open Data Catalogue,” http://data.surrey.ca/,

May 2016, [Online].

[18] “Open Data - Accessing City Hall - City of Toronto,”

http://www1.toronto.ca/wps/portal/, May 2016, [Online].

[19] “Data Catalogue: City of Vancouver Open Data Catalogue - Beta

version,” http://data.vancouver.ca/datacatalogue/index.htm, May 2016,

[Online].

[20] “Home - City of Waterloo Open Data,” http://opendata.city-of-

waterloo.opendata.arcgis.com, May 2016, [Online].

[21] “Search - Halifax Open Data Catalogue,”

http://catalogue.hrm.opendata.arcgis.com/datasets, June 2016, [Online].

[22] “The City of Calgary - Open Data Catalogue - Open Data Terms

of Use,” https://data.calgary.ca/OpenData/Pages/TermsofUse.aspx, June

2016, [Online].

[23] “Halifax Open Data,” http://www.halifax.ca/opendata/, June 2016, [On-

line].

[24] “AppsContest - An Open Data App Contest,”

http://www.apps4ottawa.ca/en, July 2016, [Online].

[25] “Apps4Halifax- Open Data App Contest,” http://apps4halifax.ca/, Au-

gust 2016, [Online].

[26] “Toronto Waste Pickup Calendars by Laurenarcher,”

http://laurenarcher.github.io/iCalTOWaste/, June 2016, [Online].

A semantic web approach to land use regulations in urban planning: The OntoZoning ontology of zones, land uses and programmes for Singapore

Article

Full-text available

Feb 2023

Semantic web technologies have the potential to significantly improve urban regulatory data access, integration and usability, with potentially large implications for planning practice. Ontologies are a cornerstone of the semantic web. In this paper, we describe OntoZoning, an ontology representing relationships between zoning types, land uses and programmes (more specific land uses) in Singapore. We link the ontology to geospatial data stored in a knowledge graph, which allows executing multi-domain queries on urban data. We demonstrate how such a semantic web based approach can improve access to and usability of land use regulation data, and in particular facilitate site selection and exploration. We also discuss the difficulty of defining some concepts in the land use regulation field, and how OntoZoning could be linked to a broader semantic-web based urban planning regulatory framework.

Multi-criteria site selection using an ontology: the OntoZoning ontology of zones, land uses and programmes for Singapore

Preprint

Full-text available

May 2022

Data related to urban planning is diverse both in terms of sources and formats. To facilitate urban analyses and public access to regulatory information, greater data in-teroperability is needed. Semantic web technologies, which use ontologies to link diverse data, are a promising solution to this problem. In this paper, we describe OntoZoning, an ontology representing relationships between zoning types, land uses and programmes (more specific land uses) in Singapore. We link the ontology to geospatial data stored in a knowledge graph, which allows executing multi-domain queries on urban data. We demonstrate how such queries can improve access to urban data, and in particular facilitate site selection and exploration. These are common tasks in urban planning and urban development processes. We also discuss how certain parts of zoning regulations are difficult to represent through ontologies, and would likely need to be defined more explicitly to fully represent city planning knowledge digitally. Highlights • We develop an ontology representing land uses and programmes allowed in each zoning type in Singapore. • We link this ontology to multi-domain geospatial data in a knowledge graph. • We query the data to explore sites and access zoning regulations. Available at: https://como.ceb.cam.ac.uk/preprints/295/

Towards linked open government data in Canada

Article

Full-text available

Jan 2020

Enayat Rajabi

Governments are publishing enormous amounts of open data on the web every day in an effort to increase transparency and reusability. Linking data from multiple sources on the web enables the performance of advanced data analytics, which can lead to the development of valuable services and data products. However, Canada's open government data portals are isolated from one another and remain unlinked to other resources on the web. In this paper, we first expose the statistical data sets in Canadian provincial open data portals as Linked Data, and then integrate them using RDF Cube vocabulary, thereby making different open data portals available through a single search endpoint. We leverage Semantic Web Technologies to publish open data sets taken from two provincial portals (Nova Scotia and Alberta) as RDF (the Linked Data format), and to connect them to one another. The success of our approach illustrates its high potential for linking open government data sets across Canada, which will in turn enable greater data accessibility and improved search results.

CHAPTER 6 Examining the Value of Geospatial Open Data

Chapter

Full-text available

Dec 2021

Open health data: Mapping the ecosystem

Article

Full-text available

Nov 2021

Background Governments around the world own multiple datasets related to the policy domain of health. Datasets range from vaccination rates to the availability of health care practitioners in a region to the outcomes of certain surgeries. Health is believed to be a promising subject in the case of open government data policies. However, the specific properties of health data such as its sensibilities regarding privacy, ethics, and ownership encompass particular conditions either enabling or preventing datasets to become freely and easily accessible for everyone. Objective and methods This paper aims to map the ecosystem of open health data. By analyzing the foundations of health data and the commonalities of open data ecosystems via literature analysis, the socio-technical environment in which health data managed by governments are opened up or potentially stay closed is created. After its theoretical development, the open health data ecosystem is tested via a case study concerning the Data for Better Health initiative from the government of Belgium. Results Creation and assessment of an open health data ecosystem consisting of stakeholders, interests, information policies, and data preparation activities. Conclusions The policy domain of health includes de-identification activities, bioethical assessments, and the specific role of data providers within its open data ecosystem. However, the concept of open data does not always fully apply to the topic of health. Such several health datasets may be findable via government portals but not directly accessible. Differentiation within types of health data and data user capacities are recommendable for future research.

Graph Neural Network to Solve the Dynamic Emergency Vehicles Routing Problems

Conference Paper

Apr 2024

Smart Government and Future Trends

Chapter

Oct 2023

Several technologies are available to help citizens, and government officials perform their daily activities in a city. The current state-of-the-art technologies to help citizens and government officials exist wireless sensor networks, RFDI technology, combinatorial optimisation, machine learning, big data, data visualisation, internet of government things, big-data analytics, and others to enhance the quality of the government. The authors have collected the relevant literature published during 2001-2021 by searching and browsing all the major digital libraries and publisher websites. The findings show the importance of the smart government's technology-assisted (electronic government, management of the economy, open data, civil works, tourism, management of the disasters, healthcare systems, and others). This chapter aims to determine how smart government components improve the activities in a city of the citizens and government officials. This paper also presents a survey of the characteristics, taxonomy, smart government indicators, history, and future trends.

Designing Open Government Data Management Platform Through the Implementation of Data Governance Based on SOA

Conference Paper

Nov 2022

Construire les usages des données ouvertes en France : proposition d'un Open Data Canvas par l'approche du design science

Thesis

Jul 2021

Arthur Sarazin

Depuis l’entrée en vigueur de la Loi pour une République numérique en 2016, toutes les collectivités de plus de 3500 habitants ont l’obligation de publier leurs données de manière accessible, gratuitement et dans un format ne nécessitant pas l’utilisation d’un logiciel spécifique. Derrière la loi transparaît la promesse de voir émerger de nouvelles applications, services, informations issues de l’utilisation que le public ferait des données ouvertes. Or, si l’ouverture des données publiques se veut être un facteur qui encourage le développement de nouveaux usages, une telle démarche n’est pas nécessairement un gage de succès. En effet, depuis 2016, très peu d’usages utilisant l’ouverture des données ont vu le jour, à tel point que certains activistes définissent la période actuelle comme celle du “baby blues de l’open data”. Dans ce cadre, l’objet de cette thèse est de construire un dispositif en Système d’Information pour lever les barrières qui freinent la construction des usages. Une approche par le design science a été adoptée. Une première phase qualitative a permis de développer un modèle théorique de compréhension des phénomènes à l'œuvre dans la construction des usages des données ouvertes et des barrières socio-techniques qui freinent le processus. Une seconde phase de conception a permis de construire le design d’un dispositif en Système d’Information appelé Open Data Canvas qui permet de lever ces barrières. Il s’appuie sur trois théories : la théorie de la construction sociale de la technologie, la théorie de la cognition distribuée et la théorie du middleground. Enfin, une dernière phase dite d’évaluation a permis d’interroger les usagers des données ouvertes sur l’utilité perçue de l’Open Data Canvas. Ces trois phases se sont affinées itérativement pour permettre au Canvas de s’intégrer dans le quotidien des usagers des données ouvertes.

Knowledge Representation and Reasoning in AI-Based Solutions and IoT Applications

Chapter

Jan 2021

Marcus Tanque

Artificial intelligence (AI)-based solutions, knowledge representation and reasoning, and the Internet of Things applications have transformed how researchers and practitioners view the analytical and computational capabilities. The disruptive evolution of these technologies has encouraged researchers and practitioners to develop integrated AI-based analytical solutions needed for solving pervasive issues affecting computational applications. The capabilities include AI, knowledge Representation and Reasoning and Internet of Things. Such capabilities are designed to support AI-based solutions, knowledge representation and reasoning, and the Internet of Things (IoT) applications. These technology trends involve relevant computational areas, that is, intelligent devices, sensors, autonomous vehicles, robotics, virtual reality, augmented intelligence, and others. The study addresses and validates solutions on how researchers can solve issues that affect AI, knowledge representation and reasoning, and IoT applications.

Effects and evaluation of open government data initiative in Croatia

Conference Paper

Full-text available

May 2016

A Consumer Focused Open Data Platform

Conference Paper

Full-text available

Mar 2016

Open data has been around for many years but with the advancement of technology and its steady adoption by businesses and governments it promises to create new opportunities for the advancement of society as a whole. Many popular open data platforms have focused on solving the problems faced by the data producer and offers limited support for the data consumers in the way of tools and supported processes for easy access, modeling and mining of data within the various platforms. In this paper we present the specifications for a data consumer oriented platform for open data, the Data-TAP. We demonstrate how this platform is able to (a) meet the goal of leveraging the data resources of existing Open Data platforms, (b) provide a means to standardize and structure data to allow for the merging of related data resources and (c) use a rule-based method for parsing resources. This paper will show how Data-TAP provides an easy to use and understand interface for making open data friendlier for consumers.

A Tale of Open Data Innovations in Five Smart Cities

Conference Paper

Full-text available

Mar 2015

Abstract Open Data initiatives are increasingly considered as defining elements of emerging smart cities. However, few studies have attempted to provide a better understanding of the nature of this convergence and the impact on both domains. This paper presents findings from a detailed study of 18 open data initiatives across five smart cities – Barcelona, Chicago, Manchester, Amsterdam, and Helsinki. Specifically, the study sought to understand how open data initiatives are shaped by the different smart cities contexts and concomitantly what kinds of innovations are enabled by open data in these cities. The findings highlight the specific impacts of open data innovation on the different smart cities domains, governance of the cities, and the nature of datasets available in the open data ecosystem.

The Emerging Internet of Things Marketplace From an Industrial Perspective: A Survey

Article

Full-text available

Jan 2015

The Internet of Things (IoT) is a dynamic global information network consisting of Internet-connected objects, such as RFIDs, sensors, actuators, as well as other instruments and smart appliances that are becoming an integral component of the future Internet. Over the last decade, we have seen a large number of the IoT solutions developed by start-ups, small and medium enterprises, large corporations, academic research institutes (such as universities), and private and public research organizations making their way into the market. In this paper, we survey over 100 IoT smart solutions in the marketplace and examine them closely in order to identify their applications and the technologies they use. More importantly, we identify the trends, opportunities, and open challenges in the industry-based IoT solutions. Based on the application domain, we classify and discuss these solutions under five different categories: 1) smart wearable; 2) smart home; 3) smart city; 4) smart environment; and 5) smart enterprise. This survey is intended to serve as a guideline and a conceptual framework for future research in the IoT and to motivate and inspire further developments. It also provides a systematic exploration of existing research and suggests a number of potentially significant research directions. 14 INDEX TERMS Internet of Things, industry solutions, IoT marketplace.

City Event Management System Based on Multiple Data Source

Conference Paper

May 2015

Since IBM proposed the concept of "Smarter Planet", the construction of "Smarter City" has been spread all over the world. Our country's construction in "Smarter City" is just at the beginning, and it appears with serious information silos, although data has been simply integrated, there still exists the problem of single source of data, fixed monitoring position and details can be hardly found. In response to these problems, this paper presents the design of City Event Management System, which integrates the data from public monitoring facilities, social media and crowd sourcing. Meanwhile, topic model has been used to extract city events, these events can be classified in different categories by matching with the predefined repository. The proposed system pushes events as well as relative viable solutions to users. Hence, problems of the fixed monitoring positions are solved via users' activity, and their high sensitivity of city events. Issues on single source of data are solved by the data integration of social media and crowd sourcing. Challenges of information silos are overcame by strength the data mobility.

Visualization of GIS Analytic for Open Big Data in Environmental Science

Conference Paper

Nov 2015

Kayoko Yamamoto

Open Government Data as a Service (GoDaaS): Big Data Platform for Mobile App Developers

Conference Paper

Aug 2015

A Tale of Open Data Innovations in Five Smart Cities

Conference Paper

Jan 2015

Fatemeh Ahmadi Zeleti

Open Data initiatives are increasingly considered as defining elements of emerging smart cities. However, few studies have attempted to provide a better understanding of the nature of this convergence and the impact on both domains. This paper presents findings from a detailed study of 18 open data initiatives across five smart cities – Barcelona, Chicago, Manchester, Amsterdam, and Helsinki. Specifically, the study sought to understand how open data initiatives are shaped by the different smart cities contexts and concomitantly what kinds of innovations are enabled by open data in these cities. The findings highlight the specific impacts of open data innovation on the different smart cities domains, governance of the cities, and the nature of datasets available in the open data ecosystem.

Toward Energy Efficient Big Data Gathering in Densely Distributed Sensor Networks

Article

Sep 2014

Recently, the big data emerged as a hot topic because of the tremendous growth of the information and communication technology. One of the highly anticipated key contributors of the big data in the future networks is the distributed wireless sensor networks (WSNs). Although the data generated by an individual sensor may not appear to be significant, the overall data generated across numerous sensors in the densely distributed WSNs can produce a significant portion of the big data. Energy-efficient big data gathering in the densely distributed sensor networks is, therefore, a challenging research area. One of the most effective solutions to address this challenge is to utilize the sink node's mobility to facilitate the data gathering. While this technique can reduce energy consumption of the sensor nodes, the use of mobile sink presents additional challenges such as determining the sink node's trajectory and cluster formation prior to data collection. In this paper, we propose a new mobile sink routing and data gathering method through network clustering based on modified expectation-maximization technique. In addition, we derive an optimal number of clusters to minimize the energy consumption. The effectiveness of our proposal is verified through numerical results.

Vita: A Crowdsensing-Oriented Mobile Cyber-Physical System

Article

Jun 2013

As a prominent subcategory of cyber-physical systems, mobile cyber-physical systems could take advantage of widely used mobile devices, such as smartphones, as a convenient and economical platform that facilitates sophisticated and ubiquitous mobile sensing applications between humans and the surrounding physical world. This paper presents Vita, a novel mobile cyber-physical system for crowdsensing applications, which enables mobile users to perform mobile crowdsensing tasks in an efficient manner through mobile devices. Vita provides a flexible and universal architecture across mobile devices and cloud computing platforms by integrating the service-oriented architecture with resource optimization mechanism for crowdsensing, with extensive supports to application developers and end users. The customized platform of Vita enables intelligent deployments of tasks between humans in the physical world, and dynamic collaborations of services between mobile devices and cloud computing platform during run-time of mobile devices with service failure handling support. Our practical experiments show that Vita performs its tasks efficiently with a low computation and communication overhead on mobile devices, and eases the development of multiple mobile crowdsensing applications and services. In addition, we present a mobile crowdsensing application, Smart City, developed on Vita to demonstrate the functionalities and practical usage of Vita.

Open Data-Set of Seven Canadian Cities

Abstract and Figures

Recommended publications

Privacy concerns in smart cities

Requirement engineering for open government information network development to support digital start...

An architecture proposal for the creation of a database to open data related to ITS in smart cities

Impact of open data on innovation activities of enterprises

A Comparative Study of Tools for Smart Cities Open Data Publication and Management