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

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.

Full text

1"
Innovating in the midst of crisis: A case study of Ushahidi
Fernando Mora, PhD
Dept. of Business and Management
St. George’s University, Grenada
West Indies

2"
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

3"
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 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

4"
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 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

5"
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.
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 9th, 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

6"
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.
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

7"
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.
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

8"
(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 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

9"
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 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.
""""""""""""""""""""""""""""""""""""""""""""""""""""""""
1 http://ihub.co.ke/pages/home.php
2 http://www.technologyreview.com/tr50/

10"
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 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).
This participatory way of web based mapping introduces a number of questions, which are
""""""""""""""""""""""""""""""""""""""""""""""""""""""""
3 http://en.wikipedia.org/wiki/John_Snow_(physician)

11"
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.
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
""""""""""""""""""""""""""""""""""""""""""""""""""""""""
4 http://www.crisismappers.net

12"
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 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
""""""""""""""""""""""""""""""""""""""""""""""""""""""""
5 Twitter terminology referring to a way of tagging messages that point to a particular subject or theme.

13"
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 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.

14"
___________
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).
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

15"
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 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

16"
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 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

17"
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 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

18"
recovery was active, the site 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 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,

19"
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
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.

20"
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, 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

21"
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 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

22"
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 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
""""""""""""""""""""""""""""""""""""""""""""""""""""""""
6 http://www.gartner.com/technology/research/methodologies/hype-cycle.jsp

23"
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.
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

24"
the depth of the changes at hand. In the past, these international experts came to offer
advice and lecture, not 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.
References

25"
Asmolov G (2010). Online Cooperation as an alternative for government? Global Voices. August
30th. http://globalvoicesonline.org/2010/08/30/russia-online-cooperation-as-an-alternative-for-
government. Last visit May 1st, 2011
Batty M, Hudson-Smith A, Milton R and Crooks A (2010). Map mashups, Web 2.0 and the GIS
revolution. Annals of GIS 16(1): 1-13
Balda J, Mora F (2011). Adapting leadership theory and practice for the networked millennial
generation. Accepted for publication in Journal of Leadership Studies.
Biegald L (20100. Crowdsourcing the Haiti Relief. The Crowdflower Blog. January 29th.
http://blog.crowdflower.com/2010/01/crowdsourcing-the-haiti-relief/. Last Visit April 29th, 2011.
De Waal M (2010). The technology that's seriously upsetting the aid sector, and the man behind it.
Daily Maverick. http://www.thedailymaverick.co.za/article/2010-06-22-the-man-whos-seriously-
upsetting-the-aid-sector. June 22nd. Last visit May 2nd, 2011.
Diamond L (2010) Liberation Technology. Journal of Democracy. 21(3): 69-83
Dodge M, McDerby M, Turner M (2008). The power of geographical visualizations. In Dodge M,
McDerby M, Turner M (eds) Geographic Visualization: Concepts, tools and applications. New
Jersey: John Wiley and Sons, 1-10.
Drucker P (1985). The Discipline of Innovation. Harvard Business Review. May-June, 67-72.
Gao H, Barbier G, Goolsby R (2011). Harnessing the crowdsourcing power of social media for
disaster relief. IEEE Intelligent Systems. 26 (3): 10-14.

26"
Gartner (2011). Gartner Hype Cycle. Last visit September 6th, 2011.
http://www.gartner.com/technology/research/methodologies/hype-cycle.jsp
George S, Gosier J, and Kaurin D (2011). Key deployment record- March 2011. Ushahidi Inc.,
http://www.slideshare.net/Ushahidi/ushahidi-key-deployments-q1-2011/download. Retrieved April
25th 2011.
Giridharadas A (2010). Africa’s Gift to Sillicon Valley: How to track a crisis. The New York Times.
Retrieved April 26th, 2011
http://www.nytimes.com/2010/03/14/weekinreview/14giridharadas.html?_r=1
Goldman J, Shilton K, Estrin D et al. (2009). Participatory Sensing: A citizen-powered approach to
illuminating the patterns that shape our world, UCLA Center for Embedded Networking Sensing
(CENS), White Paper, Los Angeles, May.
Goodchild M, and Glennon JA (2010). Crowdsourcing geographic information for disaster
response: a research frontier. International Journal of Digital Earth. 3 (3): 231-241
Greenwald T (2010). David Kobia 32: Ushahidi, software that helps populations cope with crisis.
Technology Review, MIT. 2010 Young Innovators under 35 Award, last visit May 3rd, 2011.
http://www.technologyreview.com/TR35/Profile.aspx?TRID=947
Haklai M, Singleton A and Parker C (2008). Web Mapping 2.0: The neogeography of the GeoWeb.
Geography Compass, 2 (6): 2011-2039.
Harvard Humanitarian Initiative (2011). Disaster Relief 2.0: The Future of Information Sharing in
Humanitarian Emergencies. Washington, D.C. and Berkshire, UK: UN Foundation & Vodafone
Foundation Technology Partnership.

27"
Heerema-Agostino S, Lekkerkerk H-J, Pepping R (2011). Crisis mapping 2.0: Publishing and
finding crisis data on the web. Utrecht University, Utretch (Netherlands). Retrieved September 10th,
2011. http://www.findinggeo.com/Ushahidi/ushahidi/media/uploads/Gima6-crowdsourcing-gr1-
Final%20paper.pdf
Heinzelman J and Walters C (2010). Crowdsourcing Crisis Information in Disaster Affected Haiti.
Washington: United States Institute of Peace. Special Report 252. http://www.usip.org/publications/
October. Retrieved April 28th, 2011.
Hersman E (2011). Phone interview. April 18th.
Hester V, Shaw A and Biewald L (2010). Scalable crisis relief: Crowdsourced SMS translation and
categorization with Mission 4636. ACM DEV’ 10, December 17-18th, London (UK).
Howe J (2008). Crowdsourcing: Why the power of the crowd is driving the future of business. New
York: Crown Business.
Jackson MJ, Rahemtulla HA, and Morley J (2010). The synergistic use of authenticated and
crowdsourced data for emergency response. 2nd International Workshop on Validation of geo-
information products for crisis management. Ispra-Italy, October 11th-13th, 91-98.
Keay A (2010). Ushahidi and Crowdmap: micro-streaming as time binding media. 3PM Journal of
Digital Research and Publishing. 1 (2):116-125
Leson H (2011). How the Eq.org.nz site came about to help with the Christchurch earthquake.
Crisis Commons. http://crisiscommons.org/2011/02/24/how-the-eq-org-nz-site-came-about-to-help-
with-the-christchurch-earthquake. Last visit May 1st, 2011.

28"
Livingston S (2011). African Infosystems: a pathway to security and stability. Africa Center for
Strategic Studies Research Paper No. 2. Washington: National Defense University Press. March.
Lewis W D (2010). Haitian Creole: How to build and ship an MT engine from scratch in 4 days, 17
hours & 30 minutes. Proceedings of the 14th Annual conference of the European Association for
Machine Translation, May, Saint-Raphaël (France): 27-28.
Lewis W D, Munro R, and Vogel S (2011). Crisis MT: developing a cookbook for MT in crisis
situations. Proceedings of the 6th Workshop on Statistical Machine Translation, Edinburgh
(Scotland, UK), July 30th -31st , 501-511.
McNamara T (2011). The power of Ushahidi. NZCS Newsline. March 18th. Last visit May 2nd, 2011.
http://www.nzcs.org.nz/newsletter/article/94
McNie N (2011). Fixing website performance issues III: whack-a-mole. Nigel McNie Blog, March
28th, 2011. Last visited May 2nd, 2011. http://nigel.mcnie.name/blog/fixing-website-performance-
issues-whack-a-mole
Meier P (2010a). Ushahidi and the unprecedented role of SMS in disaster response. IRevolution
blog. February 20th. http://irevolution.net/2010/02/20/sms-disaster-response. Retrieved April 29th,
2011.
Meier P (2010b). Think you know what Ushahidi is? Think again. IRevolution blog. June 16th.
http://irevolution.net/2010/06/16/think-again/. Retrieved April 29th, 2011.
Mora F and Flores R (2011). Social interaction and crowd engagement in emergent leadership
around the world. Accepted for presentation at International Leadership Association Annual
Conference, London, October 26th to 29th.

29"
Morrow N, Mock N, Papendieck A and Kocmich N (2011). Independent evaluation of the Ushahidi
Haiti Project. Development Information Systems International (DISI). Retrieved April 30th, 2011.
https://sites.google.com/site/haitiushahidieval/news/finalreportindependentevaluationoftheushahidih
aitiproject
Nelson A, Sigal I and Zambrano D (2010). Media, information systems and communities: Lessons
from Haiti. CDAC (Communicating with Disaster Affected Communities) and Knight Foundation.
Retrieved on April 28th, 2011.
http://www.pbs.org/mediashift/Haiti%20Report%20English%2001.10.11-4.pdf.
Okolloh O (2009). Ushahidi or “testimony”: Web 2.0 tools for crowdsourcing disaster response.
Participatory learning and action 59: 65-70. http://pubs.iied.org/pdfs/14563IIED.pdf, retrieved on
May 1st, 2011
Shaw A and Hester V (2011). Human Computing as a horizon of SM4D: Crowdsourced crisis
response and beyond. CSCW 2011, Social Media for Development Workshop, March 19-23,
Hangzhou, China. Retrieved September 10th, 2011. https://sites.google.com/site/sm4dev/file-cabinet
Singh J (2011). Ushahidi trends for the Christchurch earthquake. Geogeek New Zealand. March
16th, 2011. http:// geo.geek.nz/esri-new-zealand/ushahidi-trends-for-the-christchurch-earthquake.
Last visit May 2nd, 2011.
Ushahidi (2009). Building Ushahidi. retrieved April 27th, 2011
http://wiki.ushahidi.com/doku.php?id=building_ushahidi

30"
Yates D and Paquette S (2011). Emergency knowledge management and social media technologies:
A case study of the 2010 Haitian earthquake. International Journal of Information Management. 31
(1): 6-13
Zook M, Graham M, Shelton T and Gorman S (2010). Volunteered Geographic Information and
Crowdsourcing disaster relief: A case study of the Haitian earthquake. World Medical & Health
Policy. 2 (2): Article 2. www.psocommons.org/wmhp. Retrieved April 28th, 2011.

31"
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.

32"
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

33"
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

34"
Figure 1. Screen Shot of Ushahidi-Haiti typical reports.

35"
Fig. 2 Example of Christchurch Recovery Map (CRM) after the activation period was over. Reports
are still available for investigative purposes.

36"
Figure 3. Block diagram of Ushahidi and interactions between human intelligence and machine
intelligence and data sources.