BUILDING A VOLUNTEERED GEOGRAPHIC INFORMATION SYSTEM

(VGIS): A MOBILE APPLICATION FOR DISASTER MANAGEMENT

A THESIS

Presented to the Department of Geography

California State University, Long Beach

In Partial Fulfillment

of the Requirements for the Degree

Master of Arts in Geography

Committee Members:

Linna Li, Ph.D. (Chair)

Hyowon Ban, Ph.D.

Deborah Thien, Ph.D.

College Designee:

Beth Manke, Ph.D.

By Manju Narmada Ulaganathan

M.A., 2012, University of Madras, Chennai

August 2016

ii

ABSTRACT

BUILDING A VOLUNTEERED GEOGRAPHIC INFORMATION SYSTEM

(VGIS): A MOBILE APPLICATION FOR DISASTER MANAGEMENT

By

Manju Narmada Ulaganathan

August 2016

The explosion of web-based GIS technologies and the opening up of mapping

technologies to common citizens in the past decade have resulted in a whole range of VGI

communities like OpenStreetMap, Ushahidi and Wikimapia, that are used to assist emergency

management operations on a large scale. However, most crowd sourced systems currently being

used for disaster recovery have multiple obstacles like accessibility, ease of use, dependency on

social media and requirement of special skill sets on the part of the public participants that serve

as limitations to the fulfillment of the democratization potential of VGI.

Hence an improved Android mobile application was developed which is much more

accessible, usable, reliable without any dependency on social media like Facebook to collect and

transmit data, thus not only ensuring participation equality but also universal accessibility to

quality and timely geographic information during emergency situations.

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TABLE OF CONTENTS

ABSTRACT .................................................................................................................................. ii

LIST OF TABLES ........................................................................................................................ iv

LIST OF FIGURES ...................................................................................................................... v

1. INTRODUCTION AND RESEARCH RATIONALE ..................................................... 1

2. METHODOLOGY ........................................................................................................... 18

3. RESULTS AND DISCUSSION ....................................................................................... 42

APPENDICES .............................................................................................................................. 58

A. INSTALLATION INSTRUCTIONS................................................................................ 59

B. USER MANUAL .............................................................................................................. 63

C. INSTRUCTIONS TO CARRY OUT A SET OF TASKS USING

THE ANDROID APP ........................................................................................... 68

D. SURVEY QUESTIONNAIRE ......................................................................................... 71

BIBLIOGRAPHY ......................................................................................................................... 75

iv

LIST OF TABLES

1. Categories for User Input (Adapted from Camponovo and Freundschuh 2014) .............. 21

2. Comparison of Current VGIS Platforms and the VGIS Android App ............................. 24

v

LIST OF FIGURES

1. Distribution of 192,000 members of OpenStreetMap by continents ............................... 14

2. Distribution of active contributors per day and per population in million

per area (1000 km2) .............................................................................................. 14

3. Distribution of active contributors per day and per population from 1 August -

31 October ............................................................................................................. 15

4. Global distribution of Twitter users .................................................................................. 16

5. Schematic to represent components of VGI prototype ..................................................... 27

6. Flowchart representing onboarding flow for mobile app ................................................. 28

7. Flowchart representing data submission (left), data retrieval (right) ................................ 29

8. Schematic explaining the self-correcting feature design of the system ............................ 30

9. Schematic explaining the bi-directional communication feature of the system ............... 31

10. Schematic explaining the architecture of the backend component of the system ............. 32

11. Data submission using Android app ................................................................................. 43

12. Data visualization using Android app ............................................................................... 45

13. Up-voting and down-voting using Android app ............................................................... 46

14. Web interface for VGIS service ........................................................................................ 47

15. Sample CSV data file as obtained from VGIS web service.............................................. 48

16. Bidirectional communication between web service and Android app.............................. 49

17. Graph showing participant experience in the field of disaster management .................... 49

18. Graph representing Participant Experience/Awareness in the Field of GIS ..................... 50

19. Graph representing Participant Experience/Awareness in the Field of VGIS .................. 51

20. Graph representing percentage break-up indicating the successful completion

of the four tasks ..................................................................................................... 51

21. Graph representing percentage break-up for the ratings indicating the

'ease of use' feature ............................................................................................... 52

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22. Graph representing percentage break-up for the ratings indicating the

'ease of access' feature ........................................................................................... 53

23. Graph representing percentage break-up for the ratings indicating the

'reliability and timeliness' feature ......................................................................... 53

24. Graph representing percentage break-up for the ratings indicating the

'data accuracy' feature ........................................................................................... 54

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CHAPTER 1

INTRODUCTION AND RESEARCH RATIONALE

A disaster is defined “a serious disruption of the functioning of a community or a

society involving widespread human, material, economic or environmental losses and

impacts, which exceeds the ability of the affected community or society to cope using its own

resources” (ISDR - International Strategy for Disaster Reduction 2009, 9). Whether human-

made or natural, disasters can have devastating effects on the human society by claiming

lives and disrupting normal life and also inflicting severe damage to the environment

(Mansourian et al. 2006). During such times, effective organization and management of

resources and responsibilities for dealing with all dimensions of emergencies, in particular

mitigation, “preparedness, response and initial recovery steps” (ISDR - International Strategy

for Disaster Reduction 2009, 13) become a necessity. Emergency management calls for well-

rounded and extensive arrangements to employ the efforts of not only the government but

also the non-government, voluntary and private agencies in comprehensive and coordinated

ways to respond to the entire extent of emergency needs (ISDR - International Strategy for

Disaster Reduction 2009, 13). In case of a disaster, speedy access to accurate, timely and

complete information is not only helpful to facilitate efficient distribution of resources but

also a necessity because a slow response based on erroneous data can lead to terrible

consequences (Ostermann and Spinsanti 2011; Erskine and Gregg 2012). According to Von

Lubitz, Beakley, and Patricelli (2008), the availability of updated information and well-

organized knowledge management during crises and disasters significantly enhances the

prospects of successful disaster containment. It is in this light that geospatial data and

geospatial technologies have proved to be an integral part of planning effective disaster

management efforts (Amdahl 2002; Al-Khudhairy 2010; Cutter, Richardson, and Wilbanks

2014). Geospatial data play a major role in providing the exact location of an object or event

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when a disaster has struck. In fact, these data are much more significant than many other

types of data because they enable information to be tagged along with a particular location

thus facilitating efficient planning operations for recovery and rehabilitation by the

emergency workers.

Background

To provide for the context and setting for this research project, this section includes

describing the importance of spatial data in disaster management, an overview of the

evolution of volunteered GIS (Geographic Information Systems), and the shortcomings of the

current VGI (Volunteered Geographic Information) systems.

When a disaster strikes, geospatial data and tools have an essential role in the most

efficient collection and dissemination of data. They are very useful in making damage

assessments, directing supplies, and in guiding recovery efforts (Goodchild and Glennon

2010), thereby facilitating accelerated decision-making (Neuvel, Scholten, and van den Brink

2012). More specifically, spatial data infrastructure can be used to develop logistic support

systems by deducing the most optimal evacuation routes (Lee and Cheon 2007;

Saadatseresht, Mansourian, and Taleai 2009), locating and assessing the damage to buildings

and structures (Gokon and Koshimura 2012) and assisting in communication between search

and rescue personnel (Giardino et al. 2012). Also, the experiences of the disaster management

activities in response to the attacks on the World Trade Center and the Pentagon on

September 11, 2001 in USA, established that spatial data are the most required component to

facilitate efficient disaster management (Thomas et al. 2002; Cutter 2003; Mansourian et al.

2006). In fact, efficient and effective disaster management is unthinkable without spatial data

(Amdahl 2002; Cutter, Richardson, and Wilbanks 2014). However, in spite of widespread

usefulness of GIS in disaster planning efforts there are still significant problems with the

collection, access, dissemination and technical know-how (Jain and McLean 2003).

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The explosion of web-based GIS technologies and the opening up of mapping

technologies to common citizens in the past decade have resulted in a whole range of

websites and VGI communities like OpenStreetMaps (https://www.openstreetmap.org),

Twitter (https://twitter.com/), Ushahidi (https://www.ushahidi.com/) and Wikimaps

(http://wikimapia.org/), that are used to assist emergency management operations on a large

scale, thus bringing a sweeping change to emergency management efforts. However, most of

the crowd sourced volunteered geographic information systems currently being used for

disaster recovery have multiple obstacles like accessibility, ease of use, dependency on

external data sources such as social media and requirement of special skill sets on the part of

the public participants that serve as limitations to the fulfillment of the democratization

potential of VGI. When it comes to universal accessibility of volunteered Geographic

Information Systems, there is a clear distinction between the technology-savvy elite and an

uninformed group of participants who still lack the means or the required skill set to use or

contribute information to the current technology.

My research examines the inherent shortcomings from a pool of the currently

available disaster response tools in terms of certain variables like ease of use, accessibility,

accuracy, reliability and timeliness. I propose to develop an improved Volunteered

Geographic Information System (VGIS) prototype - an Android mobile application, with the

goal of overcoming the inherent limitations in the current systems in order to effectively

generate, collect, transmit and manage location based information on a real-time basis, thus

not only ensuring participation equality but also universal accessibility to quality and timely

geographic information during emergency situations.

Within the broad framework of the overall research aim of developing a smartphone

Android VGIS mobile application, certain key research questions are set to meet the research

needs.

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1. What are the inherent shortcomings in the current VGI systems deployed during the

emergency response phase of disaster situations that serve as limitations to the

universal adoptability of VGIS in disaster response scenarios?

2. To what extent will volunteered, crowd sourced GIS for disaster situations, running on

a mobile device serve a better purpose in terms of accuracy, accessibility, usability,

timeliness and reliability than a system running on a website?

3. How relevant is it to have pre-configured system input options describing various user

inputs for a particular location in a disaster response tool?

4. What is the relevance of a bi-directional communication design feature for the victim

as well as the responders in a disaster response effort?

Emergence and Evolution of VGI

In the 1990s, new computing technologies in terms of hardware and software started

emerging which started to change the face of geographic information production. Firstly,

common citizens were able to determine position accurately by means of a simple GPS or by

finding location using one of a number of services that became available on the Internet – a

geocoding service, reading a cursor position from an accurately registered map (Google

Maps), or converting the name of a place to its respective coordinates using gazetteer services

(Goodchild and Glennon 2010). Secondly, the expertise needed in terms of cartographic skills

or the knowledge needed to contribute towards creating geospatial content started to diminish

(Goodchild and Glennon 2010). Thus by the turn of the century, the part of the expert was

being replaced by common citizens who now possessed GPS, mapping software, and other

technologies. The term that was used to describe the breaking down of the conventional

distinctions between expert and non-expert, in the specific context of reference to creation of

geographic information is referred to as neogeography. This transformation was often

referred to as the renaissance of geography (Hudson-Smith and Crooks 2008). It is that realm

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of geography that falls beyond the traditional Geographic Information Systems. Turner

(2006) describes neogeography as “a set of techniques and tools that fall outside the realm of

traditional GIS” (3). More specifically, it is about “people using and creating their own maps,

on their own terms, by combining elements of an existing toolset” (Turner 2006, 3).

The evolution of GIS into adopting new trends in data and technology was made

possible by Web 2.0. Web 2.0 has made it possible for the web to turn into a participatory

platform, in which users not only consume content (via downloading) but also contribute and

produce new content (via uploading) (O’Reilly 2005; Bugs et al. 2010). By integrating new

techniques like tagging, social networks, blogs, wikis and mashups, Web 2.0 made it possible

to break the barriers between experts and non-experts by creating new and useful links among

the web (Hudson-Smith and Crooks 2008; Bugs et al. 2010). The content so generated in

Web 2.0 created and distributed in the web is known as “ user generated content” (Stephens

2013, 983) and since these websites also incorporate a geospatial component to their content

they encompass “The Geographic World Wide Web” or “the GeoWeb” (Haklay, Singleton,

and Parker 2008).

In addition to becoming more interactive and participatory, the web has become a

programmable platform (Programmable Web 2015). This has been made possible by the

“externalization of Web application interactions through application programming interfaces

(APIs)”. At present, the fundamental manifestations of the Programmable Web are the

mashups (Maximilien, Ranabahu, and Gomadam 2008). By exposing these openly available

APIs (around 13,875) according to Programmable Web (2015), programmers combine

services and resources from existing websites to create novel applications, also called

mashups that are suited to specific user needs (Maximilien, Ranabahu, and Gomadam 2008;

Bugs et al. 2010).

The concept of mashups lies at the very heart of Web 2.0. The term, originally, was

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used to describe the mixing together of musical tracks and is seen in its classic form in DJ

DangerMouse’s The Grey Album (Hudson-Smith and Crooks 2008; Hudson-Smith et al.

2009; Batty et al. 2010). The term now refers to taking information published from multiple

sources and concocting it into a new information stream (Li and Gong 2008). This

arrangement enabled citizens without dedicated training to provide data and contribute the

GeoWeb or what Goodchild (2007) termed as “Volunteered Geographic Information” (212).

Volunteered geographic information refers to the generation of location based

information by amateur citizens by means of handheld devices and fed into the crowdsourced

data sets using web-based mapping tools and interfaces (Elwood, Goodchild, and Sui 2012).

According to Goodchild (2007), humans can be thought of as mobile sensors equipped with

an innate intelligence in contributing information to the cloud of big data. The VGI

phenomenon has created a paradigm shift in the manner in which geographic information is

generated, collected and distributed, thereby facilitating a reinvention of geography. It has

opened up avenues in which the distinction between an expert producer of geographic

information and an amateur user has started to diminish with the amateur user becoming both

the producer and consumer (Goodchild 2009).

One of the most interesting aspects of Web 2.0 has been the emergence of

crowdsourcing. The term crowdsourcing came from the concept of outsourcing where

business functions are relocated to remote, cheaper locations. The term crowdsourcing was

coined by Howe (2006), who used it to define how scores of well-connected users perform

laborious functions or ones that are cost intensive. Enabled by Internet connectivity, tasks

were accomplished by “crowd brainstorming, crowd voting, collaborative creation, division

of complex tasks into micro-tasks for geographically dispersed workers, citizen science,

collaborative filters and more” (Starbird 2012, 2). Haklay (2010) describes the development

of crowdsourcing as one of the most significant as well as contentious for two reasons.

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Firstly, for the exploitative potential that encourages to contribute to the so-called greater

good when, in reality, this whole design only serves to contribute to an enterprise reaping

profit. Secondly, most of the crowdsourcing activities are voluntary and non-monetary.

Hence in most cases, even in those which do not entail technological barriers for

participation, the numbers of contributors are very small compared to the number of users.

The author cites the example of Wikipedia, in which more than 99.8% of users do not

contribute to the information pool in the web.

VGI for Emergency Response

It has been many times shown by the sociologists of disaster that, in the immediate

aftermath of a disaster it is the impulsive volunteers that are the first to respond (Palen and

Liu 2007; Vieweg et al. 2008; Starbird 2012). Propelled by the popularity and ubiquitousness

of information and communication technologies, people now use the web to meet digitally

during and after the course of disaster events (Vieweg et al. 2008; Qu, Wu, and Wang 2009;

Palen et al. 2009), and this digital confluence has led to what is known as “digital

volunteerism” (Starbird 2012, 5). VGI is very much related to the concept of crowdsourcing

(Howe 2008).

In the past decade, geographic data and tools have emerged as integral components of

emergency management: preparedness, response, recovery, and mitigation, providing an

interesting alternative to the traditional authoritative information from mapping agencies and

corporations (Goodchild 2009). The proliferation of web-based geographic information

technologies and the opening up of the mapping enterprise to amateur citizens (Leszczynski

2014), in recent times have resulted in a whole range of web sites, social media and VGIS

communities like OpenStreetMaps, Twitter, Ushahidi and Wikimaps, that are used to assist

emergency management operations on a large scale, thus bringing a sweeping change to

emergency management efforts. The so-called “wikification” of GIS has opened up an entire

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new realm of public behavior towards the contributing and sharing of spatial information

online (Sui 2008). Gao et al. (2011) describe the threefold advantages of using crowdsourcing

for disaster relief. First, crowdsourcing enables almost immediate data, real-time data

collection. Second, crowdsourcing tools facilitate data collection from a wide information

pool, perform rudimentary analysis and plan relief work. Third, geo-tagged information

gathered via platforms like Ushahidi makes it possible for effective data visualization and

consequent planning for relief and recovery operations.

There have been many instances where VGI has been used for disaster relief efforts in

the past decade. Consider the Santa Barbara fires of 2008/2009 that burned for days, bringing

down hundreds of homes. During one of the fire episodes – the Jesusita Fire, individuals

volunteered geographic information, providing information and updates on the location of the

points of fire, evacuation orders and emergency shelters constantly. At the end of the fire, one

of the most popular maps had 600,000 hits (Goodchild 2009). In addition, VGI provides an

avenue for channeling the emotional needs of the affected people thereby transforming them

from helpless citizens to empowered citizens (Elwood 2008a, 2008b).

OpenStreetMap (OSM), another VGI platform, was founded at University College

London (UCL) in July 2004 by Steve Coast with an aim of creating a free vector based map

of the world (Haklay and Weber 2008; Haklay et al. 2010). By being free to use and easily

available, a community of contributors map the roads and other geographical data by means

of GPS devices or by digitizing the locations from aerial imagery (Haklay et al. 2010). One of

the primary reasons for the development of this project was to facilitate free access to

updated geographical information especially in European countries where accurate

geographical information is beyond the reach of common citizens, small business enterprises,

and community establishments. However, the project has acquired widespread popularity and

OSM platform is becoming widely used in most disaster recovery planning efforts in recent

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times (Zook et al. 2010; Shanley et al. 2013; Soden and Palen 2014). By enlisting a group of

widely distributed contributors, it offers an inexpensive alternative and might be the only

available option in certain areas (Goodchild 2007).

Ushahidi is another VGI platform developed in 2008 in Kenya to facilitate

information sharing during a time of heightened post-election violence. Ushahidi in Kiswahili

means “testimony” (Okolloh 2009). It was possible for citizens to anonymously report

incidents of violence on the website or via mobile text messages (SMS). Soon the popularity

of the application grew and its possible applicability in crisis situations was realized. The

platform was further improvised to produce dynamic maps for crisis situations. It is a free

open-source platform that operates according to the logic of mash-ups, which combine

several web services, such as mapping, databases, data manipulation tools, and visual

functionality, among others (Manfré et al. 2012; Camponovo and Freundschuh 2014). Zook

et al. (2010), by examining the case study of the Haitian earthquake of 2010, demonstrate the

remarkable potential of VGI and crowd sourced information to address disaster relief

challenges. Ushahidi has also been used in other disaster relief efforts such as the

Christchurch earthquake in February 2011 to provide support to victims, volunteer workers

and authorities (Manfré et al. 2012; Roche, Propeck-Zimmermann, and Mericskay 2013).

However, Camponovo and Freundschuh (2014), while assessing the uncertainties of the

geographic data produced by volunteers via the Ushahidi web platform in response to the

Haitian earthquake of 2010, point out that although the usefulness of Ushahidi cannot be

denied in saving precious lives during times of emergency, there could be gross discrepancies

in the quality of attribute data submitted by the volunteers through this system. In the

Ushahidi platform, when the disaster strikes the emergency response action begins with the

volunteer submitting a text message to the platform, which is then categorized, geocoded and

then placed on a dynamic web-map interface by volunteers. What happens in reality is that in

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most cases the guidelines or documentation for attribute classification of the raw text

messages from victims do not exist, resulting in ambiguities and uncertainties in classifying

the contents of the message (Camponovo and Freundschuh 2014). In their independent

analysis of the categorized data from the Ushahidi database, it was found that 50% of the

messages in the main category were miscategorized by volunteers and at the subcategory

level, about 73% of the messages were not in sync with the main category classification.

They also suggest that in order to reduce the errors because of the ambiguities in classifying

raw data, the system could be improvised to include pre-defined categories and sub-

categories in the training materials.

In addition to standalone VGI platforms, popularity, ease of use and efficiency of

social media have proliferated the integration of social media sites with VGI platforms for

planning disaster recovery efforts (Abbasi et al. 2012). Such platforms are designed to

harvest data from social media sites like Facebook, Twitter, Flickr, etc. by sifting through

information from a huge data feed to collect relevant data. The process is called crowd

harvesting. Liu (2014) defines crowd-harvesting as “a passive, one-way information flow that

does not direct the crowd to perform a task, but rather harvests or mines the crowd’s data or

services sometimes without their direct knowledge or consent. Many projects use data mining

techniques to passively collect and process social media data from the online crowd by

utilizing existing networking platforms to collect this crowdsourced data” (416). Because of

the huge number of Twitter users and overwhelming popularity in most countries, it is

proposed that Twitter has the potential to become a primary tool for crisis management

organizations, municipal, state and federal government agencies and other organizations

involved in disaster response and recovery (Mills et al. 2009). The extraordinary impact of

Twitter as a tool for sharing crisis information was realized during events such the

Californian fires, New England ice storm, Gulf of Mexico hurricane, cyclone Nargis in

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Myanmar and Mississippi hurricane (Mills et al. 2009; Sinnappan, Farrell, and Stewart 2010).

However, the process of harvesting data presents a substantial challenge needing new

skillsets as it resides at the crossroads of disciplines like geography, computational social

sciences, linguistics, and computer science (Stefanidis, Crooks, and Radzikowski 2013). In

the domain of crisis management when speed of response is the key, much time is lost in

collecting, filtering and analyzing VGI and integrating the assessed data into the allocated

information flow. It must also be noted that, most humanitarian organizations lack the

“organizational will” to try out new technologies as they receive minimal or no support from

the upper management due to lack of resources and time (Tapia et al. 2011). Microblogged

data are viewed as trivial, time consuming and requiring technical skills (Tapia et al. 2011).

According to Mills et al. (2009), the variability and the sheer quantum of data available with

Twitter makes it a difficult task to administer and harness relevant, accurate and useful

information for crisis management purposes. Also many questions have been raised about the

network safety and privacy concerns of the users of Twitter. In their study of the applicability

of Twitter for the information needs of emergency response efforts, they categorically

conclude that Twitter is “nowhere near a complete emergency communications system and is

not particularly useful for management purposes” (Mills et al. 2009, 18) and must be

supplemented by other mediums and communication tools to provide support to emergency

management operations.

Other Issues in VGI Systems for Disaster Response

One of the main issues that has long dominated academic discussions on the

suitability of VGI for planning disaster recovery efforts is that of data quality (Chrisman

1984). Several studies have focused their attention on identifying the inherent data quality

issues as well as in coming up with a clear cut solution to those issues (Goodchild and

Glennon 2010; Zook et al. 2010; Sui and Goodchild 2011). The credibility and quality of

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geographic information is of paramount importance because of the important role it provides

in the decision-making process (Foody 2003). According to Oort, (2006), cited in

Camponovo and Freundschuh (2014), in addition to positional accuracy of geospatial

information there are many different aspects of data quality. They include, attribute accuracy,

logical consistency, completeness, semantic accuracy, usage, purpose and constraints, and

temporal quality. In terms of attribute accuracy, Girres and Touya (2010) list three distinct

components of attribute accuracy: quantitative accuracy, non-quantitative attributes, and

classification of features. Many of these quality concerns arise because of two factors. First,

the number of participants who contribute geographic information is very small even when

technological barriers to contribution are fairly insignificant (Haklay 2010). Haklay (2010)

cites the example of Wikipedia, in which more than 99.8% of visitors to the site do not

contribute information at all. Second, there has been a proliferation of web content and

information abundance after the advent of Web 2.0, which has made it difficult for

gatekeeping and quality control. Hence data is poorly organized, obsolete, incomplete or

inaccurate (Flanagin and Metzger 2008). Haklay (2010) also alludes to this when he says that

in the context of crowdsourcing activities, due to the sheer volume of information available

and the absence of any regulating standards in terms of data collected, verified and used, it is

increasingly difficult to create reliable sources of information.

However, Goodchild (2009) argues that despite issues of data quality, the publicly

available localized information, due to the richness in context and timeliness of the

geographic information produced, can be leveraged and laid out in parallel with authoritative

information sources to deliver information and services to the affected people in a disaster

situation. There are two types of error that may arise in a crisis situation: a false positive,

indicating a false rumor of a crisis, or a false negative, implying no information about the

crisis. In that case, decision makers always face the dilemma of whether to wait for the

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information available to be cross-checked in order to reduce the possibility of error or

whether to act on less reliable information. Goodchild and Glennon (2010) argue that even

though each of the situations have their own costs, responding to a false positive alarm is

likely to have smaller costs than not having responded at all, had the alarm been positive. In

crisis situations, the very fact that geospatial data is available is much more important than

the availability of quality data (Goodchild and Glennon 2010).

Issues with respect to universal adoptability. Besides the core issues discussed

above, it has been argued in academic circles that VGI and other web-based GIS platforms

have deeply democratized the process of production and use of geospatial information

(Elwood 2008a, 2008b; Tulloch 2008; Stephens 2013). Benkler and Nissenbaum (2006) echo

the same view when they say that VGI systems have allowed for the conception and

distribution of geospatial content in an egalitarian form. Butler (2006), in his commentary on

the Google Earth phenomenon, remarks that Google Earth as a geographic information

platform “has opened the eyes of millions to the possibilities of digital geography” (776).

VGI was also seen as chance to meet the emotional needs of the victims thereby transforming

them from helpless people in a disaster to empowered citizens (Elwood 2008a, 2008b).

However, Haklay (2013) argues that it is not entirely true. Even Goodchild (2007) asserts that

in spite of the seemingly open nature of VGI, it has largely remained the realm of the elite

and those fortunate enough to have access to web-based technologies. He further goes on to

say that the digital divide has allowed only a small segment of citizens in the developed

countries have access to VGI but has kept it away from the mainstream population in rest of

world. Neis and Zipf (2012, 2014), with regard to the areal distribution of the contributor

activity of OpenStreetMap, found that almost three quarters of the participants were from

Europe and the remaining quarter was distributed over North America and Asia. Another

interesting result was that when considering the user contribution in terms of population

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density, USA, China and India have considerably a small number of contributors. Figure 1,

adapted from Neis and Zipf ( 2012) shows the distribution of the 192,000 members by

continents. Almost three-quarters of the total members of the project are from Europe.

FIGURE1. Distribution of 192,000 members of OpenStreetMap by continents. Adapted

from Neis and Zipf (2012).

FIGURE 2. Distribution of active contributors per day and per population in million

per area (1000 km2). Adapted from Neis and Zielstra (2014).

The figures 2 and 3, adapted from Neis and Zielstra (2014), show the distribution of

OSM contributors per day related to population in millions (a) per area (b) for each country,

indicating a strong concentration of OSM contributors in Europe.

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Even among those who have access to web-based technologies, the reach of VGI has

been limited because of various language issues and problems that arise because of it

(Graham 2010). Figure 4 shows the worldwide distribution of Twitter users adapted from

Java et al. (2007). Hong, Convertino, and Chi (2011), in examining the users of the top ten

languages of the popular microblogging platform Twitter, remark that it may be erroneous to

assume that the behaviors of users of different languages are the same. They remark that

further research is needed to study the differences in cross-cultural communication practices

and the purpose and language specific inclinations of different tweeting communities.

FIGURE 3. Distribution of active contributors per day and per population from 1

August – 31 October. Adapted from Neis and Zielstra (2014).

In addition to the inequalities created and put in place by the VGI technologies, they

are further reinforced and perpetuated to further deepen the digital divide because of social,

political and economic reasons, causing further political and social marginalization of those

under-represented in the GeoWeb (Elwood 2006, 2008a; Crutcher and Zook 2009). Elwood

(2008a) says, “when the epistemologies, vocabularies, and categories of data structures do

not or cannot encompass the experiences, knowledge claims, and identities of some social

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groups or places, this produces their under-representation in digital data” (178).

In a study on the issue of spatial data quality, Haklay et al. (2010), with respect to the

completeness of data, showed that it is closely linked with socioeconomic factors since OSM

participants do not contribute geographic information in the poor and marginalized areas.

Haklay (2013) suggests that the current VGI technologies in order to fulfill its potential must

take into account social and political aspects into its design considerations. It becomes quite

evident that there are not many studies pertaining to the relevance, applicability and universal

adoptability of current VGI systems. The reach of VGI has not been as much as it is intended

and it has its relevance in the developed economies. These issues by themselves require

further studies and research in order to reinvent and remodel VGI systems that accommodate

the needs and aspirations of the people. Although the social and political aspects of VGIS are

significant, they are not the primary focus of my work. However, I have chosen to note them

here, keeping in view the future research potential these aspects hold for the research

community.

FIGURE 4. Global distribution of Twitter users. Adapted from Java et al. (2007).

17

In the following thesis, I detail my research work to build a crowd sourced

volunteered geographic information system prototype for the purposes of emergency

management that is much more usable, accessible and easier to adopt than the current VGI

systems.

18

CHAPTER 2

METHODOLOGY

The main objective of the research is to develop an improved Volunteered Geographic

Information System (VGIS) mobile application with the goal of overcoming certain inherent

limitations in the current systems in order to effectively generate, collect, transmit and

manage geo location based information on a real-time basis. The project design involved

three stages in order to accomplish the research objective. The three stages are briefly

described below:

1. Content analysis and literature review of popular platforms to examine and identify

the parameters on which to base the design considerations.

2. Model Design based on results from the content analysis and literature review.

3. Usability study to evaluate if the design model meets the intended research objective.

Evaluation of Current Systems for Emergency Response

As the first step, this research involved literature survey and content analysis of the

popular VGI platforms like OpenStreetMap, Twitter, and Ushahidi currently used for disaster

management purposes to assess their inherent shortcomings. This gave a fair idea of the

intricate details of design shortcomings of the current VGI systems and helped with design

strategies for the proposed VGIS model.

Based on literature research it was identified that ease of use, ease of access,

accuracy, reliability and timeliness were important variables that needed consideration and

study while designing a VGIS system. The following section describes the criteria and the

thought process that went into the assessment of design variables.

Ease of Access

For the purposes of this research, it is assumed that a smartphone mobile application

running on an open source platform will have a greater reach of audience in terms of

19

accessibility. In the study of research approaches to the usage of mobile phones, Donner

(2008) documents a series of studies on the profound impacts of the mobile phone in the

developing world. It is a well-known fact that there are more mobile phone users in most

parts of the world than those using desktop computers. Even though there are a number of

mobile developer environments, the Android platform created by the Open Handset Alliance

is the most popular because of the open and flexible nature it offers for both the developer as

well as the user.

As of 2015, there are more than 7 billion mobile cellular subscriptions, corresponding

to a penetration rate of 97% (International Telecommunication Union 2015). Also, the mobile

broadband market segment has shown the greatest progress as the mobile broadband

penetration has reached 47% in 2015, a value that increased 12 times since 2007

(International Telecommunication Union 2015). Although the cellular phones with broadband

connection are useful in certain respects when it comes to the utilizing their potential for

disaster management applications, smartphones are better suited for the job because of their

ability to collect messages, images, videos as well as geospatial information using cameras

and GPS sensors. The idea of deploying mobile GIS applications for disaster management is

not new. It has been suggested to deploy ad-hoc wireless networks in disaster areas to ensure

that communication channels between responders and victims are kept up and running

(Killeen et al. 2006). There are many commercially available mobile GIS solutions from Esri

like ArcPad, ArcGIS for Windows Mobile and Windows Tablet and ArcGIS for Smartphones

and Tablets that enable organizations to have access to up-to-the minute, real-time

information (Esri - Environmental Systems Research Institute 2016). These applications offer

a multitude of mobile field mapping applications to collect, store, edit, visualize and analyze

geospatial data. ArcGIS for Windows Mobile and the ArcGIS for Smartphones offer runtime

software development kits (SDKs) for developers that lets them build custom applications to

20

perform GIS analysis by executing complex geoprocessing tasks. However, these

applications are mainly suited to the needs of GIS professionals and software professionals

with GIS skills who can create stand-alone GIS mobile applications with embedded GIS

functionalities.

Ease of Use/Usability

ISO standard 9241:11 defines user friendliness of a system as the degree to which a

group of users are able to achieve specific goals using it, within a specific context (ISO -

International Organization for Standardization 2013). It will be assessed in terms of

learnability aspect, i.e., the time and effort required to learn how to use the system (Jeng

2005). A successful VGIS design will depend on the ease and the comfort of the end-user

towards effectively using the system. Easy installation, quick, adaptive and easy to grasp user

interface are some of the important features that must be kept in mind while modeling the

prototype. Another design consideration is to do away with asking for extensive written input

from the end-user. The idea is to design a system that asks for users to choose from a drop

down menu. It does not mandate the user to type out their input information.

Camponovo and Freundschuh (2014) in their article on assessing the uncertainties in

the crowdsourced data obtained from a popular VGI platform, Ushahidi assert that there were

significant inconsistencies that arose when the volunteers manually reclassified the text

messages into relevant categories of information that were to be stored and processed in the

geospatial database. Therefore, a good design consideration might be to incorporate only

relevant and necessary pre-configured inputs into the design model to reduce the errors and

inconsistencies that may arise due to any ambiguity or vagueness in the information input

submitted by the user. The user friendliness component is not only in terms of ease of use for

the victim but also for the relief worker thereby eliminating mistakes arising due to human

error. It is assumed that such a design will enhance the usability appeal to a wider audience

21

who are not tech savvy or computer literate. Another design feature is not asking for the user

to register with the application. Ensuring the anonymity of the user as well not mandating the

user to register their information with the app adds a new dimension to the user friendliness

aspect of design. Sometimes asking for registration is a huge hassle on the part of the user

that shuns them away from participating in the information collection.

An important step in that direction will be to identify the vital data that would come

necessary in planning the disaster recovery operations. After review of relevant literature

(Erskine and Gregg 2012; Camponovo and Freundschuh 2014), it was identified that a set of

46 categories of input information could be used for this project (refer Table1). Information

thus obtained from these categories in combination with other relevant data such as the

census data and base map imagery would offer the greatest benefit during times of crisis.

TABLE 1. Categories for User Input (Adapted from Camponovo and Freundschuh,

2014)

Category

Number Category

Category

Number Category

1a Highly vulnerable 5a Collapsed structure

1b Medical emergency 5b Unstable structure

1c People trapped 5c Road blocked

1d Fire 5d Compromised bridge

2a Food shortage 5e Communication lines down

2b Water shortage 6a Floods

2c Contaminated water 6b Landslides

2d Shelter needed 6c Earthquakes and aftershocks

2e Fuel shortage 7a Food distribution point

2f Power Shortage 7b Water distribution point

3a Infectious human disease 7c Non-food distribution point

22

TABLE 1. Continued

Category

Number

Category Category

Number

Category

3b Chronic care needs 7d Hospitals/clinics operating

3c Medical equipment and supply

needs

7e Feeding centers available

3d OBGYN/Women’s health 7f Shelter offered

3e Psychiatric need 7g Human remains management

3f Water sanitation and hygiene

promotion

7h Rubble removal

3g Deaths 8a IDP concentration

4a Looting 8b Aid manipulation

4b Theft of aid 8c Price gouging

4c Group violence 8d Search and Rescue

4d Riot 8e Person news

4e Security concern 8f Other

8g Missing persons

8h Asking to forward a message

Reliability and Timeliness

The proposed VGIS will need to have the feature to include offline field data

collection system that will be resilient during relief work after a major disaster. In addition,

the design must also accommodate real time flow of information from the user to the

authorities and vice versa at all times to enable real time analysis of planning the relief

efforts. It is my belief that a stand-alone VGIS design will be better suited for our purpose of

disaster management because complete reliance on other social networks and web platforms

may result in loss of crucial time, data accuracy and effort involved in mining for relevant

23

information relating to the disaster. In addition, they also eliminate the complications such as

intellectual property infringement and copyright issues that arise while relying on sources

from external websites.

Data Accuracy

A key problem to crowd sourced systems is the credibility of data received from end

points. A simple input filter could potentially weed out incoming data packets based on

combination of words that indicate profanity, but the system would need to be more

intelligent than that.

For the purposes of ensuring the ‘quality of data’, the design of the VGIS will be of a

self-correcting nature by making use of the crowd sourced feed to validate the data as well,

thereby creating a closed "trusted" system. This variable is designed on the lines of the

‘Linus’ Law, according to which the accuracy and the quality of geospatial information

increases significantly with the increase in the number of individual contributors or users of

the system (Haklay et al. 2010). Table 2. provides a comprehensive comparison of the

existing systems currently used for disaster response purposes against the VGIS Android App

design based on the design variables.

Prototype Design

After extensive study and literature review, the following points came to be

considered as relevant and important for the prototype design.

Requirements

1. User friendliness – easy to install and operate, application designed with pre-

configured input options for the user to enter.

2. User anonymity – ensures privacy as well as makes it easy for users to contribute to

the VGI platform.

3. Easily accessible in terms of technology.

24

TABLE 2. Comparison of Current VGIS Platforms and the VGIS Android App

Assess-

ment

Variabl

es

Points for

design

consideration

Twitter/Facebook Ushahidi

ArcGIS for

Mobile-

ArcPad,

ArcGIS for

smartphones

VGIS

Android App

Ease of

access

Device needed

to access the

application

Desktop,

Smartphone.

Cellular phone,

Desktop Smartphone

Is the device

easily available

Desktop not as

easily available as

a smartphone

Desktop not as easily

available as a cellular

phone

Not everyone

owns a

smartphone.

However,

smartphones

are more

common than

a desktop

computer.

Not everyone

owns a

smartphone.

However,

smartphones

are more

common than

a desktop

computer.

Is the

application

available free of

cost

Yes Yes No Yes

Ease of

Use

Time and effort

to learn to use

for a people

with non-

technical skills

Somewhat difficult

in the sense not all

people may have

the technical

knowhow or

skillset to install,

register and login

to access and

contribute

geographical

information

Very simple and easy

to use. The user only

has to send an sms

containing geospatial

input. However, some

users may find it

difficult to send out

sms as they may not

know how to type

messages in a cellular

phone.

This

application is

mainly geared

to the needs of

GIS

professionals.

Hence only

people with

GIS skills can

use it.

Very easy to

learn to install

and use for

people with

little or no

computer

skills.

Ease of use for

the emergency

workers

The relief workers

must mine for

meaningful

geographical

information from a

huge data pool.

The time and effort

involved is huge.

The emergency

workers must

possess the

relevant technical

skills for data

mining.

Not really. The

emergency workers

have to manually

process all the sms

received to categorize

the data into

meaningful

geographical

information.

Easy for the

GIS

professionals.

Yes. No need

for data

mining or

categorization.

25

TABLE 2. Continued

Assess-

ment

Variables

Points for

design

consideration

Twitter/ Facebook Ushahidi

ArcGIS for

Mobile-

ArcPad,

ArcGIS for

smartphones

VGIS

Android App

Reliability

and

Timeliness

Real-time flow

of information

Data from these

sites must be mined

and harvested for

meaningful

geographical

information. The

effort thus required

may result in loss

of crucial time and

data accuracy.

Not really. The sms

sent to the

emergency workers

is manually

reclassified,

processed and then

made useful for

planning relief

operations.

Yes Yes

Off-line data

collection No Yes Yes Yes

Dependency

on external

websites to

plan relief

work.

Yes. It may give

rise to the

complications such

as intellectual

property

infringement and

copyright issues

that arise while

relying on sources

from external

websites.

No No No

Two-way

communicatio

n channel

between users

and relief

workers

No No No Yes

Data

Accuracy

Truthfulness

of the

information

Cannot say as the

information is

harvested from

tweets and posts.

Good. But the

downside is that the

sms containing

geographical input

needs to be re-

categorized thus

making it prone to

human error in

handling ambiguity.

Good

Good.

Ambiguity in

the messages

are avoided in

the system

database

because the

users are only

asked to

choose their

input from a

drop-down

menu.

26

TABLE 2. Continued

Assess-

ment

Variables

Points for

design

consideration

Twitter/ Facebook Ushahidi

ArcGIS for

Mobile-

ArcPad,

ArcGIS for

smartphones

VGIS

Android App

Self-

Correcting

design

No No No

Yes. The

system is

designed to

weed out

redundant,

faulty/erroneo

us data by

involving the

users

themselves to

validate data.

4. Designed to be a stand-alone system with minimal intervention.

5. Ensure data accuracy – self-correcting system.

6. Real-time updating as well as viewing of posted geographic information.

7. Off-line data collection capabilities.

8. Bi-directional communication between users and emergency responders.

9. Simplicity of design with features to show maps, fetch the users location, and update

information to the server.

10. Works both on the Android devices as well as on website.

11. The information generated must have the ability to be extended to other GIS

processing applications by the emergency aid agencies and workers. The information

generated is tabulated and available for download as a comma separated value (csv)

file for further geoprocessing and analysis.

Prototype Architecture

Prototype Components

Based on the above said prototype requirements in the previous section an Android

mobile application was designed and integrated into a single crowd sourced volunteered

27

geographic information system for the purpose of information management during disaster

situations. Figure 5 explains briefly the interconnections between the components of the

mobile application thus designed.

FIGURE 5. Schematic to represent components of VGI prototype.

The system consists of four essential components namely, the frontend, backend,

connection medium and a visual model. The frontend represents a unique data source. It

could come to represent an Android App, IOS App or custom made device for a particular

purpose. For the purpose of this research it was chosen to be an Android application because

of the availability of ample documentation and online material to aid in app development.

The front end submits information to the backend. Each packet of information

submitted to the backend is time stamped and tagged with the geographic location of its

origin. The backend refers to a single or a collection of servers that receives and stores

information from multiple front-ends/clients. The server implements algorithms to efficiently

store and retrieve data. The connection medium is one that connects the frontend and the

28

backend. For all practical purposes it is assumed to be the Internet.

The basic workflow representing the data submission as well as data retrieval by the

users of the disaster recovery smartphone app is illustrated in Figures 6 and 7.

FIGURE 6. Flowchart representing onboarding flow for mobile app.

Self-Correcting System

In any VGIS application it becomes essential to weed out redundant, faulty/erroneous

data into the pool of information in the database. It is also required to design a system that

removes information with malicious content. For our application, it was proposed to use the

principle of the ‘Linus’ Law as a method of ensuring attribute accuracy, the logical

consistency and the completeness of information in the geospatial content posted by the

users. Attribute accuracy of geospatial information in our case refers to the values or qualities

associated with the submitted information. The authenticity of VGIS data is ensured by a

simple self-correcting mechanism that involves the crowd to validate data. The VGIS

29

application designed provides APIs in the backend that can be used to up-vote or down-vote a

previously sent user message. This functionality exposes the end user via the user interface

on the Android application.

FIGURE 7. Flowchart representing data submission (left), data retrieval (right).

The user has the option to up-vote or down-vote erroneous or faulty data that are

submitted by other users into the system. Once a particular message has received a

considerable number of down-votes say 100, the system treats that message as erroneous and

discards it. This feedback loop ensures that when data is fed into the system by a part of the

crowd, it is also validated by another segment of the crowd thereby maintaining a credible

data set as explained in Figure 8.

Bi-Directional Communication

Bi-directional communication is a mechanism that enables rescue and relief agencies

30

FIGURE 8. Schematic explaining the self-correcting feature design of the system.

to communicate with the victims. The system provides APIs for use by rescue agencies that

enable them to communicate relevant information regarding rescue efforts that can be

delivered to a targeted group of individuals in a particular area. If a particular user is not

connected to the Internet, the message will be delivered once the Internet connection is

established (Figure 9).

Overview of Backend Architecture

This section is a brief overview of the architecture of the backend component of the

VGIS design (refer Figure 10).

The server component is implemented as a web service created using Microsoft

Active Server Page (ASP) technology. This web service was created using .NET (also known

as C# - CSharp) programming language. The web service provides functionality to the clients

by exposing web APIs. The web APIs accept and return data in the form of JSON (JavaScript

Object Notation) objects. The web server is hosted on a machine running Microsoft Windows

31

Server Operating System with IIS (Internet Information Services).

FIGURE 9. Schematic explaining the bi-directional communication feature of the

system. Base map from https://maps.google.com/.

The following section briefly describes the terms associated with server side

architecture.

Web Service: A web service is a standardized mechanism by which web-based

applications are integrated by using Internet protocols. It represents a service that receives

input, processes it and returns the relevant output (Alonso et al. 2004; Newcomer and Lomow

2004). One of the distinguishing factors about web services is that it has done away with the

need for clients or customers to have appropriate knowledge of the server side of the platform

to access and use the web service. Most modern programming languages provide a library of

functions for Internet based communication and this can be used to communicate and

exchange data with any web service. As such many protocols have already been established

32

for creation of web services and this research project makes use of REST protocol to create

the service. The protocols may be considered as the language for communication.

FIGURE 10. Schematic explaining the architecture of the backend component of the

system.

REST: REST, RESTful services, or Representational State Transfer services is a

subset of web API services. It refers to an architectural style of designing web applications

(Aho, Sethi, and Ullman 1986; He 2003).

Web API: Web API is a type of web service. A web API (Application Programming

Interface) represents the basic operation that can be performed on the web service and

conforms to the REST protocol standards. For instance, a submission API that is exposed by

the backend may be used by the clients to submit information. Data in the web API services

are commonly sent and received in XML (Extensible Markup Language) or JSON but there

are a number of other formats that are supported as well. This prototype uses JSON for

33

sending and receiving data.

The web APIs may be considered as the commands that are used to control the web

service. The web service listens for incoming commands and acts accordingly. Every

functionality that needs to be exposed by the web service must have an associated web API.

Web APIs are configured in order to support several services to be combined to a single

application. It makes it possible to create mashup applications where data from a variety of

Web API services are taken to create an individual application.

A web API also has an associated data payload. For instance, in case of the

submission API, the payload is the submission data and in case of the query API, the payload

is the query parameters (such as the geo location to obtain data from).

The web API design of the prototype accepts data encapsulated as a JSON Object. A

JSON object is an envelope in which the data required by the web APIs are packaged.

Web APIs Exposed by the Server Component

Data exchange between the server and client components are accomplished using

JSON. The JSON package sent from the client contains “command” and “payload” child

nodes, the syntax of which is shown below:

{

‘command’: ‘<command_string>’,

‘payload’: ‘<stringified_json_payload>’

}

The command field identifies the specific type of command that the client intends to

invoke using the web service and payload carries the parameters (inputs) required for the

server to process this command. The server then returns the results of the operation back to

the client as a JSON object.

Submit alert API. The client to submit a message uses the submit-alert API. The API

34

requires the client to provide the following parameters in the payload.

1. “origin” – The unique identifier of the device that identifies the source of the

message.

2. “content” – A string containing the message description.

3. “title” – A string containing the message title.

4. “category” – An integer value representing the category for the alert.

5. “longitude” – The longitude of the device location at the time of message generation.

6. “latitude” – The latitude of the device location at the time of message generation.

7. “ttl” – The expiration time of the message. After this time has elapsed the server

removes the message from the database.

8. “timestamp” – The time stamp at the time of message generation.

Upon receiving the command, the server validates the payload and stores the

information in the spatial database.

Get alerts API. The client uses the get-alerts API to retrieve alerts from the server.

This API requires the client to provide the following parameters in the payload.

1. “latitude” – The latitude of the epicenter surrounding which the alerts are to be

retrieved

2. “longitude” – The longitude of the epicenter surrounding which the alerts are to be

retrieved

3. “accuracy” – The radius around the epicenter to retrieve the alerts.

4. “category” – An integer value representing the category for the alert.

Upon receiving the command, the server validates the payload and retrieves all the

alerts matching the specified criteria.

Submit message API. The client uses the submit-message API to submit messages to

a target group of other clients. By making use of the submit-message API to send messages to

35

victims, the relief agencies are able to establish a two-way communication (bi-directional)

between them and the victims.

This API requires the client to provide the following parameters in the payload.

1. “latitude” – The latitude of the epicenter surrounding which the message is to be

broadcasted.

2. “longitude” – The longitude of the epicenter surrounding which the message is to be

broadcasted.

3. “accuracy” – The radius around the epicenter to which the message is to be

broadcasted.

4. “message” – The message content that is to be broadcasted.

Upon receiving a submit message command from a client, the server computes all the

other clients that are located in the geo location provided in the payload and relays the

message to these clients.

Get message API. The clients use the get message API to retrieve messages

addressed to them. For instance, messages sent by the relief agencies are stored in the server

and the client may query the server at regular intervals to retrieve the stored messages by

making use of the get message API. This API requires the client to provide the following

parameter in the payload: “origin” – the ID of the client requesting for messages.

Server Database

The current implementation of the server uses a custom in memory database for the

purposes of this VGIS prototype. The database makes use of the Range-trees and Interval-

trees to store and retrieve data. An interval tree is a data structure to hold intervals.

Specifically, it allows one to find all intervals that overlap with any given point. Range-tree

refers to a data structure that allows the user to query for a set of points that lie inside a given

interval. The term "points" is an abstract term and in our case refers to the messages

36

submitted by the user. The geolocation of the messages received are used as keys to index

data. Simply put, it enables us to query for all the messages originating from a particular

epicenter within a given radius. An interval tree stores this information. The architecture of

the server enables easy transitioning between different spatial databases. This custom

implementation may be replaced with robust spatial databases such as Microsoft SQL Server

(with support for spatial types), Esri geo-databases and IBM DB2 Spatial Extender.

Choice of Technology

There are several reasons for the choice of technology used to implement the project.

Microsoft ASP.Net is robust, relatively easy to learn with abundant documentation and has a

large user base. Creating web services with ASP.Net is relative simple. RESTful services for

web APIs are now regarded as the standard for implementing web APIs. Most languages such

as JAVA, C# have well-established libraries that implement REST protocols and they are

relatively easy to use. Microsoft Visual Studio (IDE) is very robust and convenient to work

with. JSON is again the industry standard for data encapsulation for web APIs.

Architecture of the Client Side

Overview

Clients are entities that interact with the web service by invoking web APIs. As a

prerequisite, client applications will need to communicate with the backend using REST

protocols. Most modern operating systems are equipped with libraries for REST protocol

based communication.

The client application provides the following functionalities:

1. Enables an end user to contribute information to the VGIS database.

2. Enables an end user to read and visualize information from the VGIS database.

3. Enables an end user to provide feedback for information in the VGIS database by

means of up-voting or down-voting.

37

4. Enables an end user to receive and displays bidirectional messages (such as those sent

from relief agencies) from the backend

The client side consists of an Android application written in JAVA programming

language. When the client application is first installed on the system, it generates a unique

identifier that is then stored on the client device.

Messages posted by the client application are tagged with the following details.

1. Unique identifier

2. Time stamp of message creation

3. Expiration time for the message. This refers to the time period for which the backend

stores the message in the system.

4. Device location. This refers to the latitude and longitude obtained from the GPS

sensors of the device from which the message is sent.

The client provides the user with pre-configured/pre-defined text inputs that identify

the various possible scenarios in disaster situations that the user may be subject to. The users

only need to choose from an array of pre-structured text inputs from a drop-down menu to

submit their geo-tagged information in the system. However, if the user wishes, the system

has an optional provision for them to include a brief description about the event that they are

submitting along with their submitted pre-defined input.

The advantages of such a design are three-fold. One, asking for extensive written

input from the users only shuns them away from contributing effectively to the information

cloud because of various reasons like lack of skill, time or interest on their part. Hence users

will participate more willingly if there is reduced effort on their end to contribute

information. Second, such a design helps in reducing vagueness or ambiguity in the data

posted by the users. The information submitted by the users can be easily categorized and

analyzed by the relief agencies and used for further geo-processing operations without any

38

delays because of confusion caused by vagueness or lack of clarity on the data submitted by

users. Third, it makes it relatively easy for the relief agencies to process huge amounts of

geographic data without having to spend too much time in going through the text inputs and

weeding out erroneous, inaccurate and faulty messages.

The client application also supports removal of submitted messages from the backend.

Messages can only be deleted from the same device from which the message was originally

generated and posted. On all other devices, the same message appears as a read-only item.

The client application permits the user to view the geo-events posted in the system.

The application procures the data (geo-events) from the backend and overlays the information

on a map. The client implementation for the data-visualization feature of the system

(including both the Android application and the web portal) makes use of Google Maps API.

The use of Google maps may be replaced with any Open Source map implementation also.

Web Interface

The web interface for the VGIS system provides an interactive means for users to

interact with the backend using a web browser. The primary purpose of the web interface is

for relief agencies to query and visualize information and to broadcast messages for

bidirectional communication. The web interface is built using HTML and JavaScript and

makes use of the same set of REST API’s exposed by the backend to provide the required

functionalities.

Prototype Evaluation

The next stage of the research work involved conducting a usability study of the

VGIS prototype that has been designed by means of a user survey from among a group of

participants. Although, it is difficult to engage a wide group of participants in the survey, it

was believed that the results of the evaluation would still come useful as practical

demonstration and proof of concept.

39

Around 300 invitations were sent out to potential respondents to evaluate the app. The

survey participants were chosen from amongst the faculty, staff and students of the

geography department at California State University, Long Beach. The reason for choosing

them was because the faculty, staff and students participating in the survey on account of

their academic background and knowledge in the field of geography will aid in the evaluation

of smartphone mobile application that has been developed for the purposes of disaster

management. The only pre-requisite for participating in the survey was that they must have

an Android Device with Internet connection. The Android app that was designed and used for

the purposes of this research work is made available to the participants free of cost.

The manner in which the usability study survey was conducted is described in the

section below. Subsequent to the IRB approval an invitation was sent out via email to

prospective survey participants (faculty/staff and students of the geography department at

California State University, Long Beach). The email contained information about the

description of the thesis work, an informed consent document for the participants, the link to

download the Android app along with instructions for installation, a user manual, instructions

for a set of tasks that the participants need to accomplish using the app and the online survey

link. The consent form contains information about the purpose of the study, the procedures

involved in participating, the potential risks as well as benefits, confidentiality and the rights

of the research subjects.

Before obtaining the informed consent, the materials required for the survey such as

the Android client application to evaluate the thesis along with the installation instructions

and user guide will be uploaded at the bitbucket.org. A write-up containing instructions to the

participants using the app as well as the link to the survey were also uploaded at the same

site. After setting up the survey questionnaire at the SurveyMonkey website, a link to the

survey was generated and uploaded at the bitbucket.org website. The survey was accessed at

40

the following links https://www.surveymonkey.com/r/XLSK5YN and https://www.survey

monkey.com/r/9MKWGZ8.

There are several reasons for choosing SurveyMonkey to conduct the web-based

online survey. The SurveyMonkey website guarantees secure transmission (via https), secure

storage of collected information and server security. The information collected is stored in the

SurveyMonkey database for only as long as the research requires. The survey is anonymous

and identifying information such as name, email address, and the Internet Protocol (IP)

address of the computer do not need to be and were not asked or made available to the

researchers.

The participants read through the consent form and if interested in participating,

navigated the various links provided to them in the recruitment email that took them to the

online site (http://bitbucket.org/) containing the following:

1. Android App (.APK file)

2. Installation Instructions for downloading and installing the app in the Android devices

(see Appendix A for Installation Instructions).

3. User Guide for the Android App (see Appendix B for User Manual).

4. Instructions containing a set of tasks that the participants need to accomplish by using

the App (see Appendix C for Set of tasks to be performed by the user using the App)

5. Link to the web-based online survey on Survey Monkey (see Appendix D for survey

questionnaire).

After installing the App, the participants were asked to complete a set of tasks that

were assigned to them using the app. The tasks were so designed in a manner in which the

participants could get a grasp of the design features and functions of the Android client

application that has been developed for this research project. First, the participants were

asked to post/ submit geospatial information in the data submission interface of the VGIS

41

Android app. Second, the participants were asked to view the data that were submitted in the

data visualization interface. Third, the participants were asked to familiarize themselves with

the credibility rating feature of the VGIS app and assign a credibility rating for an event of

their choice by up-voting or down voting. Finally, they were required to familiarize

themselves with the web interface (available @ http://linqs-thesis.apphb.com/) by viewing

/visualizing the geographic information collected using the mobile app and downloading the

data in the form of a comma separated values (csv) file.

The participants were asked to contribute in the data submission panel and view

information in the data visualization panel arbitrarily. After completing the set of tasks

assigned, the survey participants were asked to complete a short questionnaire about their

experience of using the app. It included questions regarding the usability of the VGIS

application for disaster management purposes and whether or not the assignment was

completed successfully. The participants were given 2 weeks to respond to the questionnaire.

The estimated time for completing the set of assigned tasks was about 10-15 minutes

and the web-based online survey took about 10 – 15 minutes. On the whole, participants

spent around 20-30 minutes on this assignment. The survey was made available for the

participants for a time period of 30 days on the SurveyMonkey website. The bitbucket.org

website link was activated once the participants read through informed consent document and

agreed to participate in the survey. Once the informed consent was obtained, the participants

were able to access the links that enabled them to evaluate the app and participate in the

survey.

42

CHAPTER 3

RESULTS AND DISCUSSION

The overall aim of this research project was to build a crowd sourced volunteered

geographic information system prototype for the purposes of emergency management that is

much more usable, accessible and easier to adopt than the current VGI systems. In this

regard, a system architecture was designed and implemented based on the content analysis

and literature review of popular VGI platforms that are currently being used for disaster relief

efforts and a usability study carried out to ascertain how well the design model meets the

intended research purpose.

The following section discusses the implementation of the system architecture that

was elaborated in the previous chapter followed by the results and discussion of the survey

carried out to assess the app in terms of the design features.

App Design

The app design can be discussed under the following heads namely, the client side

data submission interface, data visualization interface and online web interface.

Client Side Data Submission

Using the Android application’s data submission interface, numerous sample data

points can be collected and stored in the server. Data collection is governed by user

discretion. The Android application presents the user with a simplified data collection

interface that permits the user to indicate if the user is safe or not. Further information about

the situation can be obtained from the user from the preconfigured input options if the user

has indicated that he/she is “not safe”. The user also has the option to provide a brief textual

description of the event (not exceeding 160 characters).

The Android application provides the user with status feedback in the form of

Android dialog boxes indicating if the submission was successfully made or not. The

43

application also alerts the user in the event of an error such as inability to latch on to the users

current location, inability to connect to the Internet and inability to communicate with the

backend server. Data that was successfully submitted to the backend can be viewed on the

data visualization pane immediately (refer Figure 11).

FIGURE 11. Data submissions using Android app.

Client Side Data Visualization

Data collected previously is visualized using the Android application’s data

44

visualization interface. To query and view the data collected at a certain location, the user is

required to provide the location by means of entering the address or by selecting a point of

interest on the map within the Android application’s location selection screen. Subsequent to

this, the user sets a perimeter around the point of interest (by means of using the slider

provided in the user interface) to establish an area of interest. Upon clicking the data retrieval

button (on the user interface) the Android application communicates with the web API to

retrieve all events recorded in this area of interest. These points are then overlaid on the map

for easy visualization. The same information is also displayed in a list view format.

The data visualization view provides the following information for each event:

1. Location of the event on the map

2. Category of the event

3. Timestamp when the event was recorded in the backend

4. A brief textual description of the event (if available)

5. Credibility rating of the event based on crowd sourced feedback

In addition to efficient visualization, the data visualization interface allows the user to

delete a message previously generated by the same user and also provide credibility feedback

for a message by up-voting or down-voting a message (refer Figure 12).

The Android application’s data visualization user interface enables the user to provide

credibility rating for a message by either up-voting or down-voting a message once as can be

seen from Figure 13.

The feedback loop thus created establishes an overall credibility rating for the

messages that are posted and shared with other users accessing the app. The Android

application provides the user with status feedback in the form of Android alerts to indicate if

the voting operation was successfully captured by the backend. The user is notified of any

error condition. Once the vote is successfully submitted to the backend, the data visualization

45

interface updates the view to reflect the change in credibility rating.

FIGURE 12. Data visualization using Android app.

46

FIGURE 13. Up-voting and down-voting using Android app.

Online Data Retrieval and Visualization

The online web interface makes it possible for users to query for event occurrences in

real time (refer Figure 14). For doing so, the user is required to provide the target location

either by clicking a point on the map or by providing a valid address. Subsequent to

providing an address, the user defines an area of interest by establishing a perimeter around

the target location after which the system then queries for all the events reported in that area

(refer Figure 14). To enhance the user interface experience each event is color coded and then

displayed on the map provided on the web interface.

The web interface also allows for the data to be exported as a comma separated (.csv)

file for further geo processing applications (refer Figure 15). The online web interface was

mainly intended for the use of rescue and relief agencies to view the events posted by the

victims on a real time basis, thereby making it possible to plan and coordinate relief efforts

47

more efficiently.

FIGURE 14. Web interface for VGIS service.

Another interesting feature of the VGI system design is the ability to broadcast

messages to the victims from authoritative sources. By invoking the broadcast message API,

relief agencies will be able to broadcast relevant messages to the intended victims in a timely

and efficient manner (refer Figure 16). The two-way connection between the victims and

relief agencies is aimed at enhancing the user’s confidence in the system as well as maintain

an open communication channel between them.

Survey Results

The app evaluation study was conducted by means of an online web-survey setup at

http://surveymonkey.com/. The potential respondents included those from amongst the

faculty, staff and students of the geography department at California State University, Long

Beach. From a total of 300 invitations that were sent out, only 22 invitations received

responses. A number of respondents could not take up the survey because they did not own

48

Android devices. The survey was designed in such a manner that the participants could

respond to the survey after completing a set of tasks that would aid them in getting a grasp of

the design features of the Android client application. Among the 22 participants, it can be

inferred that the participants had very minimal knowledge or experience in the field of

disaster management (refer Figure 17). However, when asked to indicate their awareness in

the field of GIS and VGIS, the charts showed a balanced profile (refer Figures 18 and 19).

The respondents were asked to indicate their level of expertise in the survey response with a

value from a range of 1 to 5, with 1 indicating the lowest value and 5 indicating the highest

value.

FIGURE 15. Sample CSV data file as obtained from VGIS web service.

With regard to the completion of tasks assigned to the participants, the majority of the

participants indicated that they were able to complete the tasks assigned to them successfully.

The percentage break-up indicating the successful completion of the four tasks assigned to

the participants are shown in Figure 20.

The primary purpose of the survey was to conduct a usability study to ascertain if the

designed app meets the intended research objective. Hence it was decided to evaluate the app

based on the four variables identified as important in chapter 2. They are: ease of use, ease of

access, accuracy, and reliability and timeliness. Questions 1 to 6 in the survey questionnaire,

49

regarding the ‘ease of use’ aspect show that more than half the number of participants gave a

FIGURE 16. Bi-directional communication between web service and android app.

FIGURE 17. Graph showing participant experience in the field of disaster management.

rating of 5 for the various design features intended to enhance the ease of use aspect. The

individual percentage breakup for each of the questions against the ratings indicated by the

47.62%

23.81% 23.81%

0.00%4.76%

0.00%

10.00%

20.00%

30.00%

40.00%

50.00%

60.00%

1 2 3 4 5

Participant Experience in the Field of Disaster Management

50

respondents is shown in the figures below (refer Figure 21).

FIGURE 18. Graph representing Participant Experience/Awareness in the Field of GIS.

Questions 7 in the survey questionnaire regarding the ‘ease of access’ aspect that

majority of the participants gave a rating of either 4 or 5 for different parameters associated

with the ‘ease of access’ feature (refer Figure 22).

The participants were asked to indicate if VGIS app for the purpose of disaster

management, designed to run on a mobile device served a better purpose in terms of the

certain parameters like accuracy, accessibility, usability, timeliness and trustworthiness, than

a system running on a website.

In a similar fashion, answers to question 8 in the survey questionnaire regarding the

‘reliability and timeliness’ aspect show that more than half the number of participants gave a

rating of 5 for the various design features intended to enhance the ‘reliability and timeliness’

aspect. The participants were asked to rate the bi-directional communication link feature

between the official sources and victims aimed to increase the ‘reliability and timeliness’

aspect. The individual percentage breakup against the ratings indicated by the respondents is

shown in the figures below (refer Figure 23). Likewise, the individual percentage breakup for

each of the questions to evaluate the ‘data accuracy’ aspect shows that more than half the

33.33%

9.52%

14.29%

23.81%

19.05%

0.00%

5.00%

10.00%

15.00%

20.00%

25.00%

30.00%

35.00%

1 2 3 4 5

Participant Experience/Awareness in the Field of GIS

51

number of respondents gave a rating of either 4 or 5 for the credibility rating feature designed

to enhance the ‘reliability and timeliness’ aspect (refer Figure 24).

FIGURE 19. Graph representing participant Experience/Awareness in the Field of

VGIS.

FIGURE 20. Graph representing percentage break-up indicating the successful

completion of the four tasks.

In one question, the respondents were asked to indicate if the credibility rating design

feature would help in reducing administrative effort required on the part of aid agencies/relief

23.81%

9.52% 9.52%

33.33%

23.81%

0.00%

5.00%

10.00%

15.00%

20.00%

25.00%

30.00%

35.00%

1 2 3 4 5

Participant Experience/Awareness in the Field of VGIS

0.00%

10.00%

20.00%

30.00%

40.00%

50.00%

60.00%

70.00%

80.00%

90.00%

100.00%

Task 1 Task 2 Task 3 Task 4

Percentage break-up indicating the successful completion of the four tasks

NO

PARTIALLY

YES

52

organizations in maintaining the credibility of information posted into the data pool. In

another question, the respondents were asked to indicate if the credibility rating design

feature would help in keeping a check on faulty or erroneous data from being entered into the

data pool.

It must be noted that the usability study thus conducted can only be treated as a proof

of concept due to the very small number of responses received for the web-based survey.

That only 22 responses were received in total does not come as a total surprise because of the

FIGURE 21. Graph representing percentage break-up for the ratings indicating the

'ease of use' feature.

fact that not many of the respondents owned a smartphone or an Android device. The poor

The poor response was partly due to the near end-of-semester season and a near majority of

the students were busy with the academic workload. Perhaps if the survey links for

participation were kept open longer then there is chance that there could have been more

survey responses. Or had the survey been conducted during another part of the year,

alternatively during the mid-semester, the survey might have received more responses.

The percentage numbers indicating participant awareness in fields of disaster

0.00%

10.00%

20.00%

30.00%

40.00%

50.00%

60.00%

70.00%

80.00%

Userinterfacesimplicity

Designsimplicity

Registrationnot required

Lack of socialmedia

integration

Inputmechanism

CSV Export

Percentage break-up for the ratings indicating the 'ease of use' feature

1 2 3 4 5

53

FIGURE 22. Graph representing percentage break-up for the ratings indicating the

'ease of access' feature.

FIGURE 23. Graph representing percentage break-up for the ratings indicating the

'reliability and timeliness' feature.

management, GIS and VGIS shows a more or less balanced profile. Also the survey

responses indicating the completion of assigned tasks showed that a near majority of

respondents were able to finish the tasks successfully irrespective of whether or not they had

a GIS/VGIS and disaster management background. Hence it could be interpreted that survey

0.00%

10.00%

20.00%

30.00%

40.00%

50.00%

60.00%

70.00%

80.00%

Accuracy Accessibility Usability Timeliness Reliability/Trustworthiness

Percentage break-up for the ratings indicating the 'ease of access' feature

1 2 3 4 5

0.00%

10.00%

20.00%

30.00%

40.00%

50.00%

60.00%

1 2 3 4 5

Percentage break-up for the ratings indicating the 'reliability and timeliness' feature

Bidirectionalcommunication

54

FIGURE 24. Graph representing percentage break-up for the ratings indicating the

'data accuracy' feature.

responses would not be skewed or biased.

The main aim of the usability study is to ascertain how well the design model meets

the intended research purpose. To this end the system architecture was designed to meet a set

of requirements based on four design variables namely, ease of use, ease of access, accuracy,

and reliability and timeliness. The survey questions were designed to assess the system

design implementation on the aforesaid parameters. Based on the survey results it could be

inferred that the implemented system design matches the intended research objective well.

The survey results showed that the more than 50% of the participants found the app features

easy to use. The ease of access feature was evaluated based on the assumption that a mobile

smartphone was more easily accessible than desktop computers and laptops. The participants

were asked to evaluate if a VGIS application for disaster management running on a

smartphone device was better suited for the purpose in terms of parameters like accuracy,

accessibility, usability, timelines and trustworthiness. The survey results indicated that such

an idea was received well amongst the participants. However, it should also be noted that the

participants were all geography students and hence the survey was perhaps biased towards

0.00%

10.00%

20.00%

30.00%

40.00%

50.00%

60.00%

70.00%

1 2 3 4 5

Percentage break-up for the ratings indicating the 'data accuracy' feature

Reduction inadministrative effort

Reduction in erroneousdata

55

people who have some familiarity with these techniques and the value of these kind of data

When asked to evaluate the bi-directional communication link feature as an indicator of the

reliability and timeliness feature, more than half the participants gave a rating of 5 for the

design feature. The credibility rating feature aimed to enhance the data accuracy aspect of

mobile app was also received well amongst the survey participants.

Future Work

Literature study, survey implementation and experience gained during the design and

development of system architecture, a number of ideas and suggestions on how to further

improve the app in the future have come to notice. One of the major challenges for the app to

be a success will be to enable a large number of participants to download and use the app.

This could be one of the long-term research goals of the project. To implement the data input

techniques in vernacular languages is one way to attract more number of users. The server is

language-agnostic. It is capable of storing data in any language. However, the Android

application currently available for collecting and viewing data needs to be updated to support

multiple languages.

Another idea is to incorporate speech-input techniques as well as make it possible to

post pictures and videos of the disaster site. The app could be further extended to a number of

other scenarios like epidemic management, management of public safety etc. Much research

is needed to ascertain the input options that will need to be incorporated in the drop-down

menus to cater to a particular scenario. Another design extension to this app that needs to be

considered is to embed geoprocessing analysis like spatial statistics and network analysis

(routing) into the app itself.

However, the server systems must be revamped to handle the strain of such a large

user base in such a scenario. The current implementation of the server uses a custom in-

memory database for the purposes of this app. The database makes use of the Range-trees and

56

Interval-trees to store and retrieve data. The architecture of the server enables easy

transitioning between different spatial databases. One major problem with an in-memory

database is that if the server were to crash or reboot, all existing data would be lost. Hence in

the future, this custom implementation could be replaced with robust spatial databases such

as Microsoft SQL Server (with support for spatial types), Esri geo-databases and IBM DB2

Spatial Extender. The reason for choosing an in-memory database was due to cost concerns,

as the commercially available databases are not available for free and tend to be very

expensive.

There are many server side improvements that could be made to improve functionality

and performance of the system. To improve the app performance, the server code can be run

on faster, powerful machines or on online hosting platforms such as Amazon AWS that

guarantee a high level of reliability and stability. Such online platforms enable a large

number of concurrent connections to the server, which implies that a huge number of clients

can communicate with the server at the same time to submit and retrieve data. The online

hosting gateway automatically takes care of data duplication and load balancing by spawning

concurrent parallel instances of the server and routing the clients appropriately. To improve

the functionality provided to the clients, the server APIs can be upgraded to accept different

data types such as audio, video and images. These additional data types will provide more

contextual information for the geospatial information submitted.

Currently the data collection and retrieval (front end) application is available only for

the Android platform. To support other platforms such as IOS and blackberry the front-end

application needs to be re-written making use of all the provided REST APIs to retrieve and

submit data. The problem with introducing multiple platforms is that all these front-end

applications will need to be maintained independently. Another possibility is to use

applications such as Xamarin Studio to generate multiplatform code. Using Xamarin,

57

developers write code for one platform and the tool automatically generates the required code

to support the app on different platforms.

Conclusions

The aim of this thesis was to build a crowd sourced volunteered geographic

information system prototype for the purposes of emergency management that is much more

usable, accessible and easier to adopt than the current VGI systems. The Android VGIS

prototype was designed after considering certain key design variables like ease of access,

ease of use, reliability and timeliness and data accuracy. Based on the four design variables as

broad parameters, the app was extended to include specific nuances and features that were

evaluated through a usability study to see if the research design met the intended objective.

Although the number of participants in the usability study was limited, it could be inferred

that the implemented system design matches the intended research objective well. It was

evident that current research on VGI has not given importance to the relevance, applicability

and universal adoptability of current VGI systems. The reach of the VGI systems has not

been as much as it was intended and has only served to further deepen the digital divide. This

research aims at accommodating and reinventing VGI systems that reflect the needs and

aspirations of people, thus making it universally adoptable. This research project holds

significance because the VGI system developed will give scope for further avenues of studies

and research on ushering in a democratization of digital technology. It is my hope that this

mobile app as an emergency response tool will serve to make a beginning towards that end.

58

APPENDICES

59

APPENDIX A

INSTALLATION INSTRUCTIONS

60

INSTALLATION INSTRUCTIONS

Step 1 - Enable installation from unknown sources

To install the application "Installation from Unknown Sources" needs to be enabled on the

Android device. The instructions are shown below.

From your smartphone or tablet running Android 4.0 or higher, go to Settings, scroll down to

Security, and select Unknown sources. Selecting this option will allow you to install apps

outside of the Google Play store. Depending on your device, you can also choose to be

warned before installing harmful apps. This can be enabled by selecting the Verify apps

option in the Security settings. The app is secure in terms of viruses and Google issues a

certificate vouching for its security. The certificate contains the information of the publisher

61

and cannot be duplicated. The app and server communicate using HTTPS protocol ensuring

that information transmitted is secure and cannot be intercepted. Another important aspect is

the type of asset that we are trying to protect. As the database does not contain any user

specific information such as name or address the interceptor may not be interested in this

information to begin with. All commercially available spatial database solutions encrypt data

to keep it secure.

On devices running an earlier version of Android, go to Settings, open the Applications

option, select Unknown sources, and click OK on the popup alert.

Step 2 - Download the app installer (.apk) file into the Android device

The installation file can be directly downloaded to the Android device from here.

Open this link from the Android device.

Once the download is complete, launch the installer.

Step 3 - Install the app

Complete installation by clicking on the install button

After successful installation, a confirmation dialog is displayed.

Launch the app once the installation is complete.

62

63

APPENDIX B

USER MANUAL

64

USER MANUAL

Please follow the set of instructions in the given sections below to get to know the app.

Viewing events:

To view an event in a particular area, a target location must first be selected. To select a

target location, click on the "View Event" button on the landing page of the app as shown

below and select a point on the map around which you are interested and hit "Get Events".

The app then retrieves all the events from the back-end and is displayed on the user interface

Illustration explaining data viewing.

65

Posting events

1. To post an event, click the "Post an event" button on the user interface

2. Select "Yes" or "No" as appropriate on the next page to indicate if you are Safe or

Not.

3. Clicking "Yes" to indicate that you are safe will prompt the app to submit a "safe"

event.

4. Clicking "No" to indicate that you are not safe will allow the user to provide more

details.

5. Hit Submit when done.

Illustration explaining data posting.

66

Deleting events

Only the person who has posted the geo-event is allowed to delete the information from the

app. Others may only up-vote or down-vote the event to indicate their approval/disapproval.

To delete an event, press the delete button against the appropriate event on the list.

Illustration explaining event deletion

Up-Voting or Down-Voting an event

The app permits the user to provide feedback for an event using the up-vote/down-vote

buttons as shown below. Feedback for an event can only be provided from a device where the

event did not originate.

67

Illustration explaining up-voting and down-voting.

68

APPENDIX C

INSTRUCTIONS TO CARRY OUT A SET OF TASKS USING THE ANDROID APP

69

INSTRUCTIONS TO CARRY OUT A SET OF TASKS USING THE ANDROID APP

A hypothetical emergency situation is described in the section below in which you will be

assigned to complete a set of three tasks, following which you will be required to complete a

questionnaire about the experience.

Required:

Smartphone Android Device equipped with GPS sensor and Internet connection.

Hypothetical Disaster Situation.

An earthquake has struck in the place at your location causing damage to structures and

establishments. The earthquake has caused a huge loss of human life and property. The

authorities are assessing the damage that has occurred in the area and are in need of

crowdsourced information relating to the disaster to effectively plan rescue and relief efforts.

In such a situation you are required to perform a set of three tasks using the disaster

management application that you have just installed from your Android Device.

Task 1

You are required to post/ submit geospatial information in the data submission interface of

the VGIS application from your Android device.

Task 2

You are required to view the data that you just submitted in the data visualization interface of

the mobile application in your Android device.

Task 3

You are required familiarize yourself with the credibility rating feature in the VGIS app.

Please assign a credibility rating for an event of your choice. For example, if you think the

event posted/submitted is false or erroneous, assign a low credibility rating.

Task 4

You are required to familiarize yourself with the web interface (available @ http://linqs-

70

thesis.apphb.com/) by viewing /visualizing the geographic information collected using the

mobile app and download the data in the form of a comma separated values (csv) file.

71

APPENDIX D

SURVEY QUESTIONNAIRE

72

SURVEY QUESTIONNAIRE

For the following questions please indicate your response with a value from a range of 1 to 5,

with 1 indicating the lowest value and 5 indicating the highest value.

1. Do you have prior experience in working with GIS (academic/ work/ general)?

2. Do you have any prior knowledge or working experience in the field of disaster

management?

3. Do you have prior knowledge about the field of Volunteered Geographic Information

Systems or crowd sourcing?

Fill out the following questions:

1. Were you able to complete Task 1 (post/ submit geospatial information in the data

submission interface of the VGIS application) YES NO PARTIALLY

2. Were you able to complete Task 2(view the data that you have just submitted in the

data visualization interface of the mobile application) YES NO PARTIALLY

3. Were you able to complete Task 3(assign a credibility rating to an event of your

choice)? YES NO PARTIALLY

4. Were you able to complete Task 4(download the data from the web interface in the

form of a comma separated values (csv) file) YES NO PARTIALLY

For the questions listed below, please indicate your response with a value from a range of 1 to

5, with 1 indicating the lowest value and 5 indicating the highest value.

Ease of use:

1. Did you find the application’s user interface intuitive and simple to use?

2. How do you rate the application for its design simplicity?

3. The application does not ask for the users to register themselves with the application.

Do you think this feature makes the application more user friendly?

73

4. The application is not integrated with any of the social media websites like Facebook

or Twitter. Do you think this feature adds to the simplicity of the design?

5. The application does not require from the users extensive text input while posting

information about an event at a particular location. It has in-built system designed

drop-down options describing a wide variety of events for the users to choose from.

How do you rate this design feature in terms of usability?

6. The application allows for further geoprocessing by providing an option for

information to be downloaded easily in the form of a comma separated value (csv)

file. How do you rate this feature?

Ease of access:

7. Do you think that the aforesaid VGIS application for the purpose of disaster

management designed to run on a mobile device serves a better purpose in terms of

the following parameters than a system running on a website?

a) Accuracy

b) Accessibility

c) Usability

d) Timeliness

e) Reliability/ Trustworthiness

Reliability and timeliness:

8. The application design facilitates a bi-directional communication link between the

official sources and victims. Will this feature enhance the reliability and

trustworthiness of the information feed in the application?

Data accuracy:

9. Do you think that the credibility rating feature will help in reducing administrative

effort in maintaining the credibility of information posted into the data pool?

74

10. Do you think that the credibility rating feature will serve to effectively keep a check

on faulty or erroneous data?

75

BIBLIOGRAPHY

76

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