Innovating in the midst of crisis: A case study of Ushahidi

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Abstract

Ushahidi is an open source collaborative mapping platform that has been developed

in an iterative form since 2008, with innovations and upgrades generated during its

intensive use in resourced constrained, time limited and dynamic crisis situations.

This article describes the origin and evolution of the platform as well as the

philosophical principles that underlie its design such as openness, participation and

democratization of information access. As a crowdsourced-mapping tool it allows

the synthesis of otherwise scattered information into concise situational maps built

from social media and SMS’s contributed by the general public. Three

representative examples of the use of Ushahidi are reviewed. In the first one it is

possible to observe how the crowdsourcing model is applied in different instances of

the deployment of the platform during the Haiti earthquake in 2010. Another

example shows how Ushahidi served as a social participation tool to help

communities get organized during the Russian wildfires. In the last example, the

crowdsourcing and open source paradigms are combined to design software to

improve the platform during the Christchurch (N.Z.) earthquake. Finally some

ideas about the importance of Ushahidi as an innovative social participation

technology are considered, especially in relation to the Kenyan and African IT

community.

Key Words: Crowdsourcing, crowdmapping, disaster information management,

social media, crisis management, innovation

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Introduction

Today, people are able to create and share digital content, which facilitates open

participation, collaboration and collective knowledge creation throughout the Internet.

Through these means, communities and groups can record, analyze, and discover a

variety of patterns that are important in their lives. By means of messages, blogs, micro-

blogs (tweets), pictures, videos, audio recordings, SMS’s, GPS’s and other ways of

conveying information, it is possible that communities and individuals can actively

participate in sensing, communicating and analyzing aspects of their lives in an on going

basis, acting less and less as passive consumers of information.

This new collective approach to knowledge creation has been termed

Crowdsourcing, which refers to the idea of outsourcing a specific task through the open

participation of a large group of individuals (Howe, 2006), mainly volunteers or

amateurs, that contribute to its accomplishment in many different ways. The advent of

crowdsourcing has changed the way some complex commercial, technical, health or

social activities are viewed nowadays. Functions that were originally performed by small

number of people, under very hierarchical organizational structures, are now being

transferred to open self-organizing communities that work collaboratively to tackle very

complex problems.

Until recently during political crisis, natural disasters or large-scale emergencies,

the flow of information was very predictable, going through regular channels, following

pre-established protocols to reach the centralized response efforts and to the traditional

media (Yates & Paquette, 2011). However, in latter years there has been a massive

change in how the population affected share their knowledge and impressions about the

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situation they’re facing. In this regard, people become sensors that generate a data stream

about the current crisis. These crowd-generated data can be used as a form of

Participatory Sensing (Goldman et al., 2009), where citizens and community groups

sense, detect and document what is happening in the particular crisis that they are facing.

The analysis of this information can reveal patterns across an entire region in terms of

types of events, locations, people involved and times of occurrences, which serves to

guide the response efforts.

For example, during the Haiti earthquake in January 12th of 2010, the

humanitarian field staff that first arrived there found themselves without reliable sources

of information about location and size of health facilities, demographics, roads and

besides that, the situation was changing constantly generating new dynamic data that had

to be processed in order to get a real picture of what was going on (Harvard Humanitarian

Initiative, 2011). In other words, the disaster encompassed a series of critical events that

were constantly changing the overall picture, the flow of information and the decision-

making processes. Moreover, by the time of the earthquake, approximately 85 % of

Haitian homes had access to mobile phones, and with the cell antennas quickly repaired,

a large number of SMS messages started to be sent to families, in the country and abroad,

to relief agencies, and to the media and also relayed to the world via Twitter, Facebook,

e-mail and other social media, thereby creating a large pool of data that required

appropriate processing to produce effective responses.

With the development and widespread use of social media, the availability of

powerful mobile phones armed with cameras and sensors, and the increased bandwidth

for data communications, the possibility that individuals record information about their

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situation and their surroundings during crisis situations has been increasingly present in a

number of critical events that have occurred in the period 2010-2011. As demonstrated in

Haiti, the affected citizens themselves, acting as sensors, convey an overwhelming

amount of data that, if properly processed, becomes a crowdsourced alternative to

information gathered through traditional channels. This new pattern has repeated lately in

earthquakes in Chile, New Zealand and Japan; floods in Pakistan and Australia; wild fires

in Russia; demonstrations in Egypt; civil war in Libya; election monitoring in several

countries and in many different critical instances. The question then is how to collect,

process, classify and display all this people generated data in a meaningful way. This is

where a small organization from Kenya comes out with an alternative for crowdsourced

mapping that has impacted the world and has changed the way crisis information is

managed.

Ushahidi Origins

Ory Okolloh is a young Kenyan lawyer who at the end of 2007 and the beginning

of 2008 was blogging intensively from South Africa (she had returned there due to threats

to her life) about the fraudulent elections that had taken place in Kenya and the resulting

consequences in terms of rumors, violence, riots, rapes, and the like. In view of the fierce

control by the government of the traditional media sources, Okolloh took the bold move

of asking people to post comments and send emails to her blog describing those events

that were not being reported elsewhere. The capabilities of the blog were quickly

overflowed by the number of reports and at that point she was prompted with the idea of

creating a website that collected reports, sent on-line on the site or either via SMS, and

then map them for easier visualization.

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On January 3rd of 2008, she shared her idea in the blog and asked the Kenyan IT

community to begin cooperating to build the site. Her request was simple: “…any techies

out there willing to do a mashup of where the violence and destruction is occurring using

Google Maps?” (Usahidi, 2009) That original idea wouldn't have gone anywhere if David

Kobia and Erik Hersman had not seen that post and gone ahead and start building the

application. Less than one week later, on January 9 th, the website was launched with the

cooperation of other African software developers. Volunteers did all the work during

those first two months: programming, data gathering, report checking (calling or emailing

reports, comparing with media information), maintenance, software upgrades and

promotion of the site. The created site gave citizens an alternative to traditional,

government censored media, because it was able to obtain reports as soon as the event

happened, covered a broader geography than traditional reporting and included a larger

number of reports from a varied source of informants.

Regarding that first implementation Okolloh states: “the idea behind

crowdsourcing is that with enough volume, a ‘truth’ emerges that diminishes any false

reports” (Okolloh, 2009). This has been a basic philosophy of Ushahidi, which means

“testimony” in Kiswahili since its inception. This emerging ‘truth’ comes from the

bottom up, generated by the accumulation of the testimonies of common people that are

the key witnesses of the particular situation, event or crisis, which is seen and perceived

almost in real-time through their SMS’s, tweets, Facebook messages, mobile camera

photos, Skype chat logs, and even voice recordings using a call-to-report feature that is

still under development.

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Due to the large and varied volume of data gathered, the ‘truth’ about the situation

is often buried and therefore needs to be mined in order to give meaning to the

information acquired. This characteristic of crowdsourced information must be kept in

mind when it is compared with other sources such as institutional surveys, which require

specialized personnel and are performed days or weeks after the event. It is the currency

of data, its density and availability, which give its power to crowdsourcing. Table I was

developed by Jackson, Rahemtulla & Morley (2010) to compare the paradigms of

crowdsourced and institutionally acquired data, showing the differences in nature, quality

and use that crowdsourced information. The table allows better understanding of the

importance of Ushahidi as a simple, near real-time, multichannel crisis data collection

and analysis platform. However, at the same time points to some of the possible

constraints that need to be taken care of by proper methodological design, or additional

processing steps in the form of machine or human intelligence, to resolve issues related to

high data volume, noisy or unreliable sources, lack of structure and protocols, and

incompleteness of information.

In its current form, Ushahidi is a collaborative mapping platform that enables

real-time aggregation of SMS’s, tweets, emails, photos, videos, comments and also voice

recordings, with location, time and date marks. After an initial categorization, reported

events or incidents are accumulated or clustered graphically on a map. The result is a

dynamic situational map updated through participatory sensing from the grass roots as

events unfold. In the aftermath of the crisis the resulting map becomes a searchable

repository or memory of an event, something that has extraordinary implications for

future evaluations, legal purposes or historical accounts.

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As a 2010 article in the New York Times put it, Ushahidi is an innovation that

comes from a world where entrepreneurship is born from hardship and survival and

innovators constantly improvise in order to do more with less (Giridharadas, 2010). The

political vulnerability and dangerous situation that prevailed at the time of Ushahidi

development and first deployment where such that the characteristics of simple, near real-

time, high density, high sampling frequency, unstructured and unconstrained data

acquisition were very important. As such, Ushahidi, a free open source platform (FOSS),

became part of a new kind of technologies that empower individuals, facilitate

communications, and foster mobilization, enabling citizens to provide humanitarian

response, to expose abuse, to protest, and to act as social auditors (Diamond, 2010).

It is undeniable that the crowdsourcing concept has been around for quite some

time, that is why Erik Hersman, one of the Ushahidi’s creators, is surprised that this

technology had not been attempted in the humanitarian field before. However, the

problem is that open access, a philosophy that permeates Ushahidi design, operates in

direct contrast to the underlying ideas in the humanitarian and crisis response

organizational world where knowledge silos seem to be prevalent (Yates & Paquette,

2011). In a critical tone, Hersman believes that aid organizations hold on to information

very tightly because it is a commodity that enables funding (De Waal, 2010).

Ushahidi disrupted the established informational paradigm by providing a

platform that allowed free, open and easy data entry by the general population and open

downloads of all the available information for free by whoever needed it. By eliminating

privileged access, it has provided an innovative first experience in the democratization of

crisis information access, the possibility of auditing a response effort, of discovering

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where aid is needed and how to distribute it. The receptivity of communities of

entrepreneurs in different countries that have implemented the platform has been

astonishing, which demonstrates that the old wineskin needed to be changed.

Due to the high demand for this crowdmapping tool, Ushahidi Inc, a non-profit

organization was established as a technology company specialized in developing free

open-source software for information collection, visualization and interactive mapping.

This assures the continuous improvement of the Ushahidi platform and the development

of new products such as Crowdmap, an “in the cloud” version of Ushahidi aimed at

smaller projects not expecting high load, and SwiftRiver, which is used as an intelligent

crowdsourced information filter that classifies messages from Twitter, email, RSS feeds,

and SMS using semantic analysis.

Ushahidi won the NetSquared 2008 Mashup Challenge that provided a seed

funding of US$ 25000. Additional funding started to pour in from Humanity United,

Cisco, Knight and MacArthur foundations, and the Open Society Institute. At the end of

2009 the organization secured a grant of 1.4 million US$ from the Omidyar Network for

the following two and a half years. The Omydiar Network was established in 2004 by

eBay founder Pierre Omidyar and his wife Pam, investing in innovative organizations

with projects that can foster economic and social change. This large grant together with

another from the Hivos Foundation, a Dutch non-governmental organization that

promotes projects that lead to fair, free and sustainable world, allowed Ushahidi to

establish a physical presence in Kenya, under the leadership of Erik Hersman. As such,

Ushahidi became a private non-profit company, totally independent of governmental

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organizations, something that is fundamental in the developing world where paternalism

and corruption destroy initiatives and entrepreneurship.

For the most part Ushahidi is a virtual organization whose staff is spread all over

the world. The Nairobi headquarters is seen as hub that connects the international tech

community with the growing Kenyan innovation community through the iHub

Community which they define as an “open innovation space for technologists, investors,

tech companies and hackers in Nairobi with a focus on young entrepreneurs, web and

mobile phone programmers, designers and researchers.”1 Recently, Technology Review,

an MIT publication, voted Ushahidi among the 50 most innovative companies of 20112.

Crowdsourcing crisis mapping

The old adage: “a picture is worth a thousand words” applies well to the field of

crisis mapping. Based on the idea that the use of visual information, rather than text or

numbers, is conducive to more powerful reasoning, understanding and learning, specially

in complex and stressful situations, geographic visualization allows an individual to see

complex relationships, understand better a phenomenon, and reduce the search time of

particular events (Dodge, McDerby and Turner, 2008). Geographic visualization helps to

discover unknowns and to obtain new insights that are not apparent by other means of

data representation. This is the basic idea of mapping in general, and especially when it is

necessary to extract meaning from complex and incomplete data in situations of crisis.

Basically, the idea of enhancing our perception of events through the help of

mapping is certainly not new. A classic and illustrative example that is often cited refers

1 http://ihub.co.ke/pages/home.php2 http://www.technologyreview.com/tr50/

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to the outbreak of cholera in London in 18543. John Snow, a physician and scientist, took

data collected by the government during an extended period of time, about where those

that died from cholera had lived and where they were at the time of death, and plotted it

over a city map. After careful and patient analysis it was discovered that most of the

deaths belonged to a neighborhood that drew their water from a contaminated supply,

which lead to its closure and the subsequent neutralization of the epidemic.

Until a few years ago, most maps and atlases were quite static and their

development and distribution was very slow and regarded as the function of specialized

individuals, researchers and officials. With the advent of the Internet, and specially Web

2.0 technologies, it became feasible for any layperson to make maps at affordable costs

and with the aid of powerful tools such as GPS technology and mapping software

(Goodchild and Glennon, 2010). The emerging field of volunteered geographic

information (VGI) or neogeography is based on the possibility of creating geographic

mashups that combine web-mapping services such as Google Maps with data provided by

non-expert individuals. These amateur geographers use their own acquisition tools in

order to create and document maps that serve very specific interests or that describe

unique events or circumstances (Haklay, Singleton and Parker, 2008). The word mashup

was originally coined to describe the mixing or blending of hip-hop musical tracks to

create a new one. In Web 2.0 terminology it now refers to websites that weave data from

different sources into new integrated applications without the need for intensive

programming tasks, something which has become specially appealing for the

development of the field of neogeography (Batty, et al., 2010).

3 http://en.wikipedia.org/wiki/John_Snow_(physician)

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This participatory way of web based mapping introduces a number of questions,

which are at the heart of crowdsourcing such as: What is the type of information

collected from volunteers? What are the characteristics of the input methods and how is

data structured? Is there any quality assessment of incoming data? What information

should be displayed or represented on the map? Can it be combined with institutional or

authoritative data? Who are the volunteers and how are they recruited? And, how the new

mashup service affects response in the event of crisis?

Two hours after the first quake hit Haiti on January 12th of 2010, Patrick Meier

who was Ushahidi’s Operations Manager and also headed The International Network of

Crisis Mappers4, and Kenyan Ushahidi’s lead developer David Kobia started to work on a

version of Ushahidi aimed at crowdmapping the crisis that was starting in Haiti. The

question that Meier posed was how to produce a “live map” of the crisis in Haiti, a map

that was recording the events, the incidents and the progress of the situation and that

could help the responders to act accordingly. It was a completely different set up as the

one that had been attempted in the post-election period in Kenya. Therefore, the

aforementioned questions did not have any clear answers, many things had to be learned

in real-time as the deployment was adapted to the situation. In the words of Erik

Hersman, one of the co-founders of Ushahidi, “it was like modifying the engine of a plane

at 30000 feet of altitude.” Thus innovation, creation and improvisation had to be

combined to adapt Ushahidi to the new conditions that were being faced in the response

to the earthquake. New challenges surfaced, human intelligence had to be combined with

new technology to improve the response time of the mapping system and the quality of

the information that it displayed.

4 http://www.crisismappers.net

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Once the information began to flow through the Ushahidi Haiti site, it became

clear that the initial small team did not have the capacity to handle the magnitude of the

data that was streaming through the site. More volunteers had to be recruited to continue

the monitoring and a number of students from the Fletcher School of Law and Diplomacy

at Tufts University were involved in the process. Starting from the people in need, it was

also necessary to access the social networks that existed within the Haitian society in

order to gather those volunteers that could feed the map with information. As the vast

majority of the messages would come in Haitian Creole, there was also a need to

crowdsource the translation efforts. Then the messages had to be geotagged, by finding

the GPS coordinates using Google Earth, classified according to pre-established

categories, confirmed and approved before plotting on Google Map or Open Street Map

and finally, report the event to those that were in the position to help. Just a few of the

tasks mentioned were fully automated, by far they were done by people located in

different countries connected through social networks on the Internet.

Besides Ushahidi, there were several other crowdsourced mapping efforts in place

at the time of the Haitian crisis, but the main difference in the model used by Usahahidi

was the possibility of aggregating SMS reports. However, another open source platform

known as FrontlineSMS was necessary for that purpose, which was set up by January

16th. Additionally, web-based submissions, email, monitored twitter messages that used

the #Haiti hashtag5, as well as the review of blogs, media and other websites were used as

data entries. The SMS functionality was called Mission4636 and was a joint effort

between Fletcher, FrontlineSMS, US State Department and Digicel a Caribbean cell

phone company. As Zook et al. (2010) points out, the ability of Ushahidi to collect on-the

5 Twitter terminology referring to a way of tagging messages that point to a particular subject or theme.

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ground knowledge via standard cell phones and then structure, categorize, map and share

it, was the main difference to other efforts that employed only the Internet as a way of

input and distribution.

Nevertheless, the availability of the 4636 number produced an input flow of 1000

to 2000 text messages per day (Heinzelman and Walters, 2010) which required both,

translation and geolocation. Machine translation engines for Haitian Creole was not

available at the time and resources to develop one within a very short time were limited

(Lewis, 2010; Lewis, Munro and Vogel, 2011). Only 12 million people, of whom 9

million live in Haiti, speak Haitian Creole in the world, therefore, linguistic resources and

knowledge about the language for the design of automatic translators were scarce. Due to

the pressing need to respond to the incoming messages in Haitian Creole, the Ushahidi

team was faced with the need of crowdsourcing translation also in near real-time (Meier,

2010). Volunteers from the Haitian diaspora were recruited as translators through an

Internet based dedicated interface organized by Brian Herbert of Ushahidi and Robert

Munro from Energy for Opportunity of Stanford University (Nelson, Sigal and

Zambrano, 2010). Munro was involved in researching the processing of large number of

text messages, and also was working in collaboration with FrontLineSMS (Biewald,

2010). Dozens of motivated ex-patriate Haitian volunteers participated in the translation,

categorization and geo-location of every message. Over 30000 text messages went

through Mission3636 during the first month after the earthquake (Harvard Humanitarian

Initiative, 2011), which speaks of the overwhelming amount of translation work that took

place.

Later on, to make the translation service more scalable it evolved through the use

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of CrowdFlower (Hester, Shaw & Biewald, 2010), a platform for managing tasks

outsourced to a distributed digital workforce on demand. The translation of each message

was a microtask offered to the pool of translators that had been recruited through social

media among Haitian Creole speakers around the world and to bilingual Haitian residents

who received an income for the translation work to alleviate their difficult situation as

survivors of the disaster. The vast majority of the workers that contributed through

CrowdFlower were located in the U.S.A. (89%) and the rest mostly in Canada, Haiti and

Switzerland (Hester, Shaw & Biewald, 2010). Figure 1 shows some of the reports

collected during a particular time window, in this case most of them are text messages

that had already been translated into English.

___________

Insert Figure 1 about here

____________

More Ushahidi’s deployments mean new challenges

As can be seen from the Haitian experience, Ushahidi can be counted among the

first participatory platforms that successfully combine collective human intelligence and

automatic methods to provide information during dynamic and time-constrained events

such as in crisis. As a matter of fact, in an evaluation of the Ushahidi Haitian deployment

the report states that: “(it) represents an impressive proof of concept for the applications

of crisis mapping and crowdsourcing to large scale catastrophes and a novel approach

to the rapidly evolving field of crisis informatics” (Morrow et al., 2011, p. 4).

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Nevertheless, as Ushahidi developers like to say, “Ushahidi the platform is a

piece of software, not a methodology” (Meier, 2010). As a platform it allows mapping

according to the interest of those implementing it. However, it is up to the users to

determine the methodology for data collection and the characteristics of the collected

data. As such, Ushahidi is not exclusively a platform for crowdsourcing, neither it is

restricted to crisis mapping alone.

This is somewhat better exemplified by looking at some of the deployments that

stand out from the reported installations done from 2009 until March of 2011 (George,

Gosier and Kaurin, 2011). Ushahidi products (Ushahidi, Crowdmapping and SwiftRiver)

have been deployed in many different scenarios ranging from social and political crisis,

natural disasters, observation of elections, tracking crime and civil unrest, promoting

human rights, documenting the impact of environmental disasters like oil-spills,

coordinating citizen response during wildfires, environmental monitoring, mapping the

disruptions in urban transportation systems, up to participatory epidemiology and

community health. Table II shows some selected Ushahidi implementations and some of

their main characteristics.

These deployments have been done under many different conditions and

methodologies affecting the quality and quantity of information required in a

crowdsourcing application such as Ushahidi. The lack of an adequate reporting structure,

such that data can be processed faster, can affect the quality of the implementation. This

makes the design phase of the deployment methodology a very important step. Also,

besides the general public that can access the platform in its different input modalities, it

is important to have trusted reporters in the field and somehow give more weight to this

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information in the processing stages. For example, in the evaluation of the Ushahidi

Haitian deployment there was some kind of “suspicion of the crowd”, fear about the

possibility of data manipulation, and questions about the representativeness and

exactitude of the data gathered (Morrow et al., 2011). Another critical part of data quality

assurance are the moderation, verification and analysis phases where a second step of

crowdsourcing is performed and which requires another group of volunteers typically for

translation of reports, geolocation, and the verification and analysis loop.

The quantity of the information also affects the deployment. On one hand,

underreporting can yield insufficient data for a meaningful analysis. Societies where

social activism is present will be more prone to use a crowdsourcing platform such as

Ushahidi, while in those where censorship and repression prevails, the public will be less

inclined. Underreporting can also happen when the primary sources of crowdsourced data

use a technology that is too complex or expensive for general use, this makes the use of

SMS’s a very important feature of this platform. Also voice messaging and more

rudimentary methods of reporting have been considered, allowing illiterate populations to

share their reports via short voicemail reports that can then be transcribed and then

mapped. The volume of work undertaken by the recruited volunteers during the aftermath

of Haiti earthquake demonstrates the immense potential of SMS enabled crowdsourcing

approaches to the management of information during crisis (Morrow et al., 2011).

Although many new things are learned with every new deployments of Ushahidi,

Erik Hersman (2011) thinks that HELP MAP in Russia and CHRISTCHURCH

RECOVERY MAP (CRM) in New Zealand are pretty much in tune with both the idea of

crowdsourcing from the general public to collect and process information from the

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bottom up, and with Ushahidi’s open source philosophy that allows continuous

innovation in the platform. HELP MAP was implemented during the Russian wildfires

that followed an unprecedented heat wave towards the end of July and beginning of 2010.

Its availability was publicized through newspapers, radio programs, Facebook, the

Russian social network Vkontakte, TV and in the portal of Yandex the main Russian ISP.

On the other hand, CRM was implemented to collect information for the general public

of what was happening near the disaster area via various media feeds in the aftermath of

the earthquake in February 22nd of 2011. The deployment was quite fast, just one hour

after the earthquake when still the response systems were not in place. It was started

using Crowdmap but later migrated to the Ushahidi platform (Leson, 2011).

HELP MAP is an excellent example of how technology can be a catalyst for

activism to go beyond computers and networks and move into practical action (Mora and

Flores, 2011). The deployment of Ushahidi during the Russian wildfires came about as a

response of bloggers, social networks and IT community in order to expand the number

of reporters and information beyond that of regular blogs and social networks. It was

basically implemented to aggregate the reports from those in need responding to the basic

question: “What is needed?” and the reports from those that were in the capacity of

providing help, by responding: “I wish to help”. Offers of help included transportation,

food, clothing, homes and many others and they were connected to those having specific

needs stated in the platform. The implementation of HELP MAP revealed the altruistic

potential of the Russian society, especially because of the timid or ineffective official

response. In this process, on-line communities and Internet users in general took a lot of

responsibilities in their shoulders in a critical moment where they felt that the Russian

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government was failing to provide the required coordination and the help needed to the

population (Asmolov, 2010).

For the crew implementing CRM the question was how to provide “information

that was relevant to people using information” (McNamara, 2011). There was interest in

knowing about local schools, water distribution and quality, availability of gasoline or

diesel in gas stations, open pharmacies, supermarket hours, location of free BBQs hosted

by neighbors, bus routes, location of free laundry services, sewage collection tanks,

recovery assistance centers, parks for children, availability of ATMs in the disaster area,

location of Wi-Fi hot spots, as well as official information about the disaster from the

government. Those interested in keeping fresh the aggregated information like banks,

stores, coffee shops, supermarkets, did the update of CRM when needed. Messages

contained in tweets, emails, SMSs and web form submissions were analyzed, and as in

other Ushahidi implementations they were categorized, geolocated, verified, and mapped.

Besides submitting the reports, users were also encouraged to find their location on a map

for more precise localization.

At the beginning, the information came from the organizations through some

social media, typically a twitter message that was read by volunteers, classified and

plotted. As the project advanced, organizations interested began to input information

directly into the map, which made the data of high quality and therefore important for the

community. In addition to this, third parties did mashups of Ushahidi collected data with

their own maps. The site for CRM was complemented with the Google’s Person Finder

application and information about other networking and community projects. During the

time that the Ushahidi crowdsourced map for Christchurch recovery was active, the site

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received 284829 page views, 127993 unique visitors and 1729 reports (George, Gosier

and Kaurin, 2011).

Many improvements were made to Ushahidi during the development of CRM,

which have been already incorporated in the deployments in Lybia and Japan. Changes

were introduced in the individual reports clustering algorithms to make them more

efficient. Also, the ability to see the full information of the individual reports over the

map with click-overs has also been added (See figure 2). The open source model was

essential for these changes in the platform. Basically what was occurring during the time

that CRM was being deployed and making it operational, is that its development was also

being crowdsourced, just as intensively as the crowdsourced map information that it

delivered. Volunteers participating in the development came from well-known and

respected technological institutions such as engineers from Google and the Apache

Foundation, but also students from local colleges and high schools were involved in the

process.

___________

Insert Figure 2 about here

____________

All of this is due to the philosophy behind the OSS paradigm in which volunteers

work at the technical level they are comfortable with, be it testing a feature as active

users, solving bugs found along the way or redesigning the user interface, creating new

algorithms or data management structures. One example of these improvements had to do

with the navigation speed on the displayed map. Users were taken a lot of time when they

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zoomed in and out in the broadband connection, even worse in the 3G links that people

where using in the city. The program was taken up to five seconds to recalculate and

display the report cluster when moving to a new zoom level and programmers worked

quickly to improve this feature (McNie, 2011). Another developer (Singh, 2011) created

a viewer to show each of the reports along with the trends over time. The viewer also

provides hotspot analysis of reports, which can be filtered down by categories if required.

These new features are especially useful for analysis of the repository of reports obtained

during the peak of the crisis to better understand the situation and improve disaster

preparedness and information management.

Tim McNamara (2011), one of the main participants in the project attributes the

success of CRM to the high network capital present in the New Zealand technological

community. This networked social capital fostered this collective software improvement

based on the OSS paradigm of collaboration by relying on social media in an intensive

way to generate new improvements, to innovate, to share ideas, problems, fears, creating

a positive and secure social environment on-line. Moreover, social networking extended

to the users of the technology and third parties, which allowed for an active interaction

and feedback about the end-user requirements. Although more technically oriented than

the HELP MAP experience, there are similar insights and questions that come out of both

events. One of them has to do with the long-term sustainability of the social capital

created during the realization of these projects.

Future of crowdsourcing crisis mapping

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Crowdsourcing crisis information has been a “big thing” since the Haiti

earthquake in 2010, all the way until May 2011. Besides Ushahidi, different other

products are starting to become available as the “wisdom of crowds” is brought forward

to play a fundamental role in crisis response. In this short period of time, several different

aspects of what could be called the crowdsourcing business model have been attempted

using the Ushahidi platform in a resource-constrained situation such as a crisis.

Massive gathering of social media that can fill the crisis maps with relevant

information; adoption of SMS interfaces for data collection in situations were

accessibility to the Internet is limited; use of volunteer force to crowdsource report

classification, verification and geolocation; use of methods to automatically manage

micro-payments for crowdsourced translation tasks; and the crowdsourcing of software

innovation and maintenance by means of the open source software paradigm employed

since the original software design, have been some of the experiences that have resulted

from an impressive number of deployments of the platform in just over a year. Figure 3

attempts to describe the different instances of Ushahidi and the complex interaction

between human and machine intelligence that is established for crowdsourced crisis

information management.

___________

Insert Figure 3 about here

____________

Most of the experiences expressed above are new in the field of crisis

management and they have generated a lot of enthusiasm and also some criticisms. Gao,

22

Barbier & Goolsby (2011) present concerns on the usefulness of crowdsourcing mapping

applications such as Ushahidi. According to them, one of the weaknesses is the lack of a

coordination instance within the platform to allow better collaboration between different

crisis responders. Also, integration of Usahidi with other platforms may require the

possibility of the resulting maps and data streams to be read or blended with other

sources of information available about the crisis being monitored (Hereema-Agostino et

al., 2011). Accuracy of geotagging has also been mentioned as a major drawback of the

system. However, new error reducing procedures have been experimented in some of

Ushahidi’s implementations. Shaw and Hester (2011) described the use of several

volunteers geotagging the same report and then using an algorithm based on the weight

the relative trust of volunteers to calculate the centroid of the points. Also, geotagging

accuracy depends upon the reporting method used whether it is manual entry of the

geographic description, which requires finding the coordinates using Google Maps or

OpenStreet Maps, or via 3G Internet. In addition to this, there are also concerns with

spurious, fraudulent and redundant reports (Gao, Barbier & Goolsby, 2011), and with the

lack of quality of the information, especially in SMS messages which are quite noisy

because of the extensive use of shorthand notations, lack of accents, punctuation and so

on, making things even more complicated when translation is needed (Lewis, 2010).

Research on crowdmapping for crisis situations has just begun after the large

number of deployments of the Ushahidi over the last two years. Experiments with new

social computing for increasing the trust factor of reports and improve validation,

development of textual analysis to tag, classify and cluster the large stream of data

coming from tweets, SMS’s, RSS feeds, web entries and so on, using real time social

23

media scanning, monitoring and curation are under way. Also, as in the case of the CRM

platform in Christchurch (See figure 2), new interfaces are being designed to allow better

representation of maps and the collected database of trusted reports, which would permit

the creation of specific reports for different agencies according to their scope in the

response effort. The application of artificial intelligence and modeling techniques in

conjunction with crowdsourced information is another frontier that would require a more

active participation of the research community in a long-term basis. In the relatively short

time in which Ushahidi has been developed, innovation has happened basically in the

midst of disasters, with time constrains, minimal resources and in the shadow of the more

traditional roles of relief agencies and geographic professionals.

According to Peter Drucker (1998) innovation occurs as a result of seven possible

sources, namely, unexpected occurrences, incongruities, process needs, industry and

market changes, demographic changes, changes in perception and the availability of new

knowledge. Many of these sources have been present in the innovative approaches taken

by the Ushahidi team and the community of users involved in the many deployments.

Crisis, in spite of the difficulties, time constraints and lack of resources usually present,

has been considered as a catalyst for creative solutions and innovation. Relief

organizations, responders, humanitarian aid NGO’s, communities and individuals learn

from each new situation and develop innovative solutions that improve their approach to

new disasters or critical events. However, as has been expressed before in this article,

there has been a huge change in how individuals, in the society at large, manage

information and how organizations have adapted to these new conditions. Demographic

changes account for a new global generational cohort of digital natives that are familiar

24

with new technology, especially social media and mobile devices of different kinds

(Balda & Mora, 2011). There are then many changes that are rocking the traditional

means of managing information during crisis, new ways of understanding the world, a

youth culture completely immersed in the digital realm, a culture of openness and

participation, a networked society where information flows freely, all of these factors are

driving technological innovations such as Ushahidi. Erik Hersman (De Waal, 2010) is

convinced that centralization of crisis information management is a concept that will soon

disappear or at least will be completely reengineered to provide access to collective

intelligence into the humanitarian sector.

Using Gartner terminology for innovation6, Ushahidi’s “trigger” or breakthrough

occurred during the Kenyan elections in 2008. Following the Haitian deployment, the

expectations for this new technology have been on the rise as the media has given to it a

lot of coverage. However, the number of implementations in real life situations that

followed under very heterogeneous circumstances, where different benefits and

challenges of this technology have been experimented, has created yet neither over-

enthusiasm nor disillusionment. For the most part, the field of crisis crowdmapping is

still at its infancy. As a one researcher has put it, perhaps “Crowdmap, Ushahidi’s hosted

cloud service, may do for Ushahidi what Blogger did for blogging” (Keay, 2010). That is,

by minimizing the technical barriers for implementing a crowdmapping project, the

technology would be quickly popularized and adopted. Some people may fear that the

technology will be used for applications completely out of the scope of crisis information

management, but Ushahidi Inc has repeatedly said that their products are not restricted to

disaster or crisis response alone.

6 http://www.gartner.com/technology/research/methodologies/hype-cycle.jsp

25

The recent launching of Universities for Ushahidi (U4U) project together with the

United States Institute for Peace (USIP) will help to create a broader social network of

proactive, next-generation innovators in the field of crowdsourcing and crowdmapping in

particular. U4U will allow students from developing countries to learn how to use the

Ushahidi platform and related tools in their own countries; they will work together with

experts from USIP to identify applications of Ushahidi for their home countries. The

extension of the base of participants will certainly extend the life of this technology and

allow for a steady path into maturity.

Finally, it is important not to forget that Ushahidi was originated in an African

nation and therefore it has impacted technological development in countries that were out

of the radar screen in terms of innovation and new technologies. According to Erik

Hersman (2011), what Ushahidi has done to the African IT community is to “change the

belief structure, just as the Kenyan runners did in the Olympic games when they won

their first gold medal”. In other words, through Ushahidi, Africans have demonstrated

that they “can do” sophisticated software developments. It is interesting to read in this

regard the comments of Steven Livinsgston (2011) when describing his visits to iHub in

Nairobi and others IT development centers in Africa:

There is ownership and commitment and a palpable sense of ambition in these

places. There is a sense that, “We did this.” The fact that international analysts

and academics come to these groups to learn about their ongoing

accomplishments is itself a significant indicator of the depth of the changes at

hand. In the past, these international experts came to offer advice and lecture, not

26

learn about the latest innovation in the application of technology for positive

social change (P. 37-38).

Another mental stronghold that needs to be transformed is the dependence of

Africans from foreign charity, which destroys creativity, fosters laziness and corruption

and makes people parasites of the aid organizations. That is why David Kobia, who won

the prize as Humanitarian Innovator under the age of 35 from the Massachusetts Institute

of Technology, Technology Review, thinks that some Ushahidi’s projects must ultimately

generate revenue. For example, larger organizations might pay for Crowdmap's services

or license parts of the Ushahidi technology (Grenwald, 2010).

In the long term Ushahidi’s efforts will create a fairly large innovation ecosystem

in Kenya that could probably make Nairobi the Silicon Valley of Africa, some kind of

technology park for the development of advanced systems that originate from the real

needs of those that are left out by the traditional markets, and which are typically

forgotten by technology developers. Ushahidi is one the first steps towards a sustainable

African society by providing open access and democratization of information, fostering

social responsibility and the kind of change of paradigm that could truly make a

difference in their continent.

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33

Table I. Data collection paradigms during crisis

Crowdsourcing Institutional or authoritative data

Simple means for data collection using

standard social media communication

channels.

Complex protocol driven methods for data

collection.

Near real-time data collection and

streaming which allows trend plotting and

analysis.

Historic or snapshot data reflecting a

particular time window.

Un-calibrated data with high density and

high sampling frequency acquired from

free-lance volunteers.

Quality assured expensive data generated

by experts on the field.

Unstructured data with user generated tags

and categorization.

Structured data following pre-defined

ontologies and taxonomies.

Unconstrained capture of data from

different locations, through different means

and channels.

Controlled methodology, policies and

rights for data gathering.

Non-systematic and incomplete coverage. Systematic and comprehensive coverage.

34

Table II. Selected Key Ushahidi Deployments

Name Location Date Objective Brief description

Ushahidi Haiti Port au

Prince,

Haiti

January

2010

Disaster

response

Provision of up to date

situational information in

the very early period of

response with good

geographic precision

Ushahidi Chile Central

Chile

February

2010

Disaster

response

Initial support of

emergency responders

which shifted to long-term

reconstruction efforts

Louisiana

Bucket Brigade

Louisiana,

USA

April

2010

Environmental

advocacy

A transparent,

participatory, localized

source of information

about human and

ecological impacts of the

oil spill for Gulf Coast

residents

HELP MAP Moscow,

Russia

August

2010

Disaster

response

To serve as a bridge

between those in need and

those needing help during

the Russian wildfires.

TUBESTRIKE London,

UK

September

2010

Transportation

information

BBC London plotted text

reports, tweets and audio

updates from listeners and

viewers about their

problems with transport

during the Tube strikes

Christchurch Christchurc 2011 Disaster Provision of up to date

35

recovery map h, New

Zealand

response situational information

with improved protocols

for information

submission and better

geographic precision

Libya Crisis

Map

Libya 2011 Tracking of

civil unrest

The map reflects social

media, mainstream news

and situation reports

crowdsourced from a

network of informers

36

37

Figure 1. Screen Shot of Ushahidi-Haiti typical reports.

38

Fig. 2 Example of Christchurch Recovery Map (CRM) after the activation period was over. Reports are still available for investigative

purposes.

39

Figure 3. Block diagram of Ushahidi and interactions between human intelligence and machine intelligence and data sources.

40