EVALUATING INFORMATION COMMUNICATION TECHNOLOGY …

TECHNOLOGY USAGE IN HUMANTARIAN RESPONSE 1

EVALUATING INFORMATION COMMUNICATION

TECHNOLOGY (ICT) USAGE IN HUMANITARIAN

RESPONSE: A SWOT ANALYSIS AND PROPOSAL

Cassandra Thomas

California State University, Maritime Academy

Capstone 900

April 19, 2017


Contents

Abstract ..................................................................................................................................... 5

Technology Usage in Humanitarian Assistance Response ................................................. 6

ICT as “Wicked Solution” .................................................................................................... 16

Attributes of an Effective Humanitarian Response System............................................... 19

UN's View of ICT in in Humanitarian Response and Assistance ...................................... 20

Current State of ICT Usage in Humanitarian Response .................................................. 22

ICT Case Studies................................................................................................................. 23

Key Area 1: Mobile Phone Use ........................................................................................................... 24

Haiti: use of SMS and crowdsourcing............................................................................................. 24

New Orleans: Use of crowdsourced information during Hurricane Katrina ................................... 25

Further developments in Mobile Phone Use ................................................................................... 26

Key Area 2: Open-source cloud based solutions. ................................................................................ 27

Sahana Disaster Management System in the Aftermath of the Indian Ocean Tsunami .................. 27

Oxfam, The Fritz Institute and Helios Disaster Supply Chain Solution.......................................... 28

Further developments in Cloud Software Use ................................................................................ 29

Key Area 3: Remote Sensing and Geographical Information Systems (GIS)...................................... 30

World Vision using Ushahidi Version 2.0 ...................................................................................... 30

African drought mapping using Geographical Information Systems (GIS) and Remote Sensing

data ................................................................................................................................................................ 31

Further developments in GIS use. ................................................................................................... 32

Key Area 4: Big Data and Data Interoperability .................................................................................. 32

Chilean 2010 earthquake and The Analysis of Social Media Data ................................................. 34

The Conflict Early Warning and Response Mechanism (CEWARN) for early detection in man-

made disasters ............................................................................................................................................... 34


Further Developments Concerning Big Data .................................................................................. 36

Strength, Weakness, Opportunity and Threat Analysis (SWOT): An Overview of

Humanitarian Response System’s Readiness to Use ICT ............................................................. 37

Next Steps for ICT in Humanitarian Response: A Proposal ............................................ 42

Blockchain: The Basis for the Proposal ............................................................................. 43

What is a Blockchain ........................................................................................................................... 43

Blockchain Benefits ............................................................................................................................. 44

Building a Source of Truth ................................................................................................. 45

Techniques for analysis of data within Tarikh-Krystal ..................................................... 47

Types of Machine Learning. ................................................................................................................ 47

The Risks of Blockchain ..................................................................................................... 48

Additional Trends ............................................................................................................... 49

Technology can’t be the sole innovation ............................................................................. 50

References .............................................................................................................................. 52


Table of Figures

Figure 1: Disaster Management Cycle (Author Created, 2017) ........................................................ 7

Figure 2: Humanitarian Assistance Management System (Source: UNOCHA) .............................. 9

Figure 3: Digital Humanitarian Network (Digitial Humanitarian Network , 2014) ....................... 18

Figure 4: Strength, Weakness, Opportunities and Threats (SWOT) Analysis, (Author Created

2017) .................................................................................................................................................... 37

Figure 5: Development of a Wicked Solution: An Opportunity (Author Created, 2017) .............. 42

Table of Tables

Table 1: Tarikh-Krystal and Sendai Priorities ................................................................................... 46


Abstract

Disasters both natural and human-caused are becoming more frequent, growing more severe and

affecting more people than ever before. The reasons vary but include climate change, population

growth, and increase in conflict, displacement and shifting habitation patterns. According to a

statement released from the UN, “worldwide in 2015, 376 reported natural disasters caused the

death of 22,765 people, made 110.3 million [people] victims, and caused US$ 70.3 billion [in]

damages” (Guha-Sapir, Hoyois, & Below, 2016).

Increasingly, Information and communications technology are important parts of the

humanitarian logistics arsenal: since the turn of the century Information Communications

Technology (ICT) has been used to increase the volume of data collected, the variety of the data

collected, the velocity at which this data has been collected, and value of the data –low density

data points that nonetheless are crucial to making decision. These efforts to use ICT has been met

with varying degrees of success and these will be examined in the paper. While key areas have

had progress in them, gaps are many, especially those in workforce readiness, readiness, ethical

understanding and funding. A proposal on how to possibly address those gaps will conclude the

paper.

Key Terms: ICT usage, IT in humanitarian response, blockchain and humanitarian

response, technology usage in disaster assistance, digital humanitarian networks, social media

and humanitarian response, big data and humanitarian response,


Technology Usage in Humanitarian Assistance Response

Climate change, population growth, and increase in conflict, displacement and shifting habitation

patterns are all contributing to a spike in disaster and accompanying mobilization of

humanitarian assistance resources. Since 1993, when the UN mobilized the United Nations

Disaster Assessment and Coordination (UNDAC) teams for the first time to handle coordination

of global emergencies, over 268 mission in 100 countries have commenced (UNOCHA, 2017).

According to a statement released from the UN, “worldwide in 2015, 376 reported natural

disasters caused the death of 22,765 people, made 110.3 million [people] victims, and caused

US$ 70.3 billion [in] damages” (Guha-Sapir, Hoyois, & Below, 2016).The US government

reports FEMA spent over $95 billion in federal disaster aid on 650 major disasters between 2004

and 2013 alone (Fugate, 2017). National economies and everyday life are continually disrupted,

causing long-term detrimental impacts as well as short-term loss of life and property damage.

Communications, coordination, data gathering and logistics are all crucial to nation and to global

organizations’ ability to respond quickly in order to reduce impact.

In the scope of this paper, a response is defined as the actions taken to prevent the loss of

human life and reduce property damage as much as possible. Response, in other words, is

mobilizing all the resources of a community, its governments and concerned agencies have

learned during preparation phase (or not) before an event. Today, due to the scale of so many

events including world war and climate change, a complex humanitarian assistance system has

developed. These include United Nations (UN), donor nation organizations, and the major

international non-governmental organizations (NGOs).


Figure 1: Disaster Management Cycle (Author Created, 2017)

New ways of working have developed to deal with the increasing scale, complexity and

cost of disaster. One new development has been the increased use of Information and

Communications Technology (ICT) as part of the response. ICT can be defined formally as the

discipline “concerned with technology and other aspects of managing and processing

information”: in other words, the use of electronic computers and computer software to convert,

store, protect, process, transmit, and retrieve information (Hameed, 2007). The term also reflects

the increasing use of mobile technology and its convergence with data gathering, storage and

transmission; hence, the “C” in ICT. Today Information and Communications Technology (ICT)

is impacting how the United Nations (UN), donor nation organizations, and the major

international non-governmental organizations (NGOs) are delivering humanitarian services as

part of disaster response and recovery. In some instances, ICT is seen as speeding the delivery


and increasing the efficiency of disaster response and aiding in recovery. Furthermore, as the

United Nations and the Humanitarian Response System looks past response to mitigation and to

resilience, ICT skill development on the local level is being viewed as a way to meet the anti-

poverty goals of the UN’s Millennium Development Goals (National Research Council, 2006).

Several case studies have shown that ICT capacity building on local levels tends to increase

income, strengthen communications infrastructure, spread awareness in general and on health

care issues and promotes gender equality, increasing among women (Batchelor, et al., 2003). All

these benefits lead to more local resilience among communities affected by disaster.

The system as it currently exists is hugely complex and comprises of several different

layers of responsibility and coordination from the Global Level at the UN down to the clusters on

the ground that handle different responsibilities. The clusters can be comprised of different types

of participants:

The coordinating bodies include:

1. UN: Emergency Relief Coordinator

2. UN, NGOs, and other bodies: Inter-Agency Standing Committee

3. Resident and Humanitarian Coordinators

4. Humanitarian Country Team

5. Cluster Approach, i.e. Emergency Telecommunications, Water1

6. Office for the Coordination of Humanitarian Affairs (OCHA) (UNOCHA, 2017)

1 Clusters are groups of humanitarian organizations, both UN and non-UN, in each of the main

sectors of humanitarian action, e.g. water, health and logistics. The idea is clustered groups will work

better together with less friction.


Figure 2: Humanitarian Assistance2 Management System (Source: UNOCHA)

2 Humanitarian assistance’s intentions are to prevent the loss of life, alleviate suffering and

maintain human dignity during and after man-made crises and disasters caused by natural hazards. The

mission has evolved to include prevention and mitigation as well as preparation for when these events

occur. Most non-governmental organizations (NGO) involved in the system follow the fundamental

principles of the International Red Cross and Red Crescent Movement (RCRC); these principles have


For example after the response in Haiti, during a Telecommunications Industry

Roundtable on Haiti Relief and Reconstruction Efforts held by the U.S. Department of State,

many private sector and NGO participants voiced a need for greater communication and

coordination in international disaster response and recovery. Information and Communications

Technology (ICT) were referenced as a key missing glue that would have enabled better

communication between “responders from private sector, NGOs and multinational organizations

(such as UN agencies) and between these entities and the multiple agencies of the U.S.

government (USG) who may have a role in international disaster response” (U.S Department of

State: Advisory Committee on International Communications and Information Policy (ACICIP),

International Disaster Response Subcommittee, 2016). The report proceeding stated

unequivocally, “Improved preparedness, communication and information flows”, they reasoned,

“could greatly reduce duplication of effort and allow the private sector and USG to use ICTs to

respond to future international disasters in a faster, more targeted and ultimately more effective,

cost-efficient manner, to support saving lives, the alleviation of suffering, and the protection of

critical infrastructures” (U.S Department of State: Advisory Committee on International

Communications and Information Policy (ACICIP), International Disaster Response

Subcommittee, 2016).

However, the culture of emergency management and humanitarian organizations does not

always lend itself producing an environment conducive to the success of ICT projects: in the US

been adopted by the UN through multiple resolutions. As a result when discussing Humanitarian

assistance the key humanitarian principles of humanity, impartiality, neutrality and independence should

be top of mind.


for instance, the movement of emergency management from a distributed state and local

government model to a US military government model is such a point (Harrald & Jefferson, 3-6

January 2007). A move to a military command model from a distributed model that involves

state and local actors is problematic as humanitarian assistance and ICT projects are both more

effective when the actual users are dictating the requirements and feature. Community

participation (Palen & STARR, 2007) – so key to the success of many of case studies we will be

examining – may be curtailed. The consolidation of decision-making power at FEMA would

potentially hurt design unless collaboration is prioritized. Also, data availability is not the same

as data interoperability and as seen during Hurricane Katrina, data can mean different things to

different people.

There is also the issue of professionalism. Since WWII, the humanitarian response

system placed an emphasis volunteerism but ICT demands professionalism. Can Humanitarian

Assistance organizations develop enough professionalism to achieve excellence in ICT which

requires certain skills? Currently that skill is not currently there. In addition, the readiness for

innovation and proper usage within the response system is lacking (Ben Ramalingam, 2017):

one, many NGOs and/or HROs are volunteer-driven and this can lead to an absence

professionalism as many volunteers lack the skills necessary; two, volunteer-headed agencies

lack sustained capacity building; three, many HROs budgets are constrained and donors

frequently want money spent on direct action and not IT and training; and four, proper

requirements gathering for feature and User Experience (UX)design has either proved difficult or

is non-existent in the absence of a professional workforce. While calls have been made for

centers of excellence around these topics, the UN has only been able to respond recently: this

month a new Humanitarian data center will open in The Hague. The Centre, led by OCHA, will


be an important part of an Innovation Hub established by the city of The Hague. The Emergency

Telecommunications cluster led by the World Food Programme was also formed and tasked with

workforce development and providing infrastructure (UN, 2017). The UN’s efforts in these areas

should be lauded but similar centers had already existed elsewhere such as Qatar and Harvard

and the question remains why the UN is playing catchup.

In fact, due to the higher and higher spending levels on ICT in disaster responses

diverting funding from other possible services, the questions remains should ICT be a

priority area in disaster response for UN at all? The hypothesis of this paper is Information

and Communications Technology increases the effectiveness of disaster response.

Disasters fall into realm of qualifying as wicked problems that is problems that can’t

be solved simply with logic. Due to the complex nature of large-scale problems that involve

many issues cultural, social, financial, economic and political, response can’t be a logical,

one size fits all solution. The multiple stakeholders with competing agendas and at times, in

conflict, the problem proves difficult to define (Roberts, 2000). In other words, the wicked

problem in this case a disaster and how to respond can be different depending on the frame

of reference and the bias of each stakeholder trying to define it. Wicked problems can be

business, economic, social, medical, environmental and political in nature, but share

complexity, an attribute of multiple fronts and the need for research and for solution

forming before the problem can be understood. ICT can help gain insight through data,

increase communication while improving coordination, increase responsiveness to clients

on the ground, increase situational awareness among affected populations and responders

and much more. However, this does make ICT a wicked solution in the sense that new

requirements must be introduced with each new disaster; however, a common IT


infrastructure framework can be standardized during preparation. Development of this

framework will help spur innovation around ICT within the disaster management system

which will help meet the UN’s Millennium Development Goals (MDG), a side motivation

increasingly being tied to immediate disaster response needs.

As stated, the issue of effectiveness concerning ICT use in response is not a lack of

intrinsic worth of ICT to the sector but the maturity of ICT capabilities within the

humanitarian system. Besides the human resource and culture problems already

mentioned, problems of actual tool development, who controls the data and how to use all

the data being generated within the system remains (National Research Council, 2006).

Emergency managers, logistics personnel and relief staff need to be agile and adaptable on

the ground: how to develop software with those attributes will be the issue. These

problems will be discussed in the case studies during in this paper’s ICT review.

IT can prove to be a “wicked solution” to a “wicked problem”. Wicked in that the IT

solutions developed will be need to be as agile, adaptable, and complex as the wicked problems

they are being asked to solve. Just as in the business sector, the tools will need to be evolved and

the data continually flowing. Many questions need to be addressed before the humanitarian

response system implements effectively IT solutions and many questions remain as to the proper

and ethical use and development of these technologies.

Among the questions to be asked in this paper are:

What technology is being used and are the ones currently selected the correct

wicked solutions?


What are the best practices for the use of technology in the field during response,

recovery and ultimately, can the data be used to be used for mitigation,

preparation and development?

How can the United Nations (UN), donor nations, humanitarian response

organizations (HRO), affected communities and other stakeholders in the HRC

productively and safely share the information generated by this technology?

What should technology subject matter experts and ICT professionals know about

creating tools for responders and affected communities?

What should effected populations expect from this activity and what access

should these communities demand to these technologies?

How are effected populations already using ICT and how can these activities be

leveraged?

How effective ultimately is the use of all this technology?

What have been the implications for the UN and its cluster framework for coordinating

Humanitarian Response? The UN has undertaken an effort to begin defining proper use of

technology and the attendant training to go along with it, as part of the Sendai Framework. The

Sendai Framework is a 15-year, voluntary, non-binding agreement between members of the

United Nations. The agreements charges member states with the primary role to reduce disaster

risk but recognizes that responsibility should be shared with other stakeholders including local

government, the private sector and other stakeholders (United Nations Office for Disaster Risk

Reduction (UNISDR), 2017). The goal of the Sendai Framework is the following outcome: The

substantial reduction of disaster risk and losses in lives, livelihoods and health and in the

economic, physical, social, cultural and environmental assets of persons, businesses,


communities and countries (United Nations Office for Disaster Risk Reduction (UNISDR),

2017). Without question any use of technology in the mitigation, preparation, recovery, and

response effort must be people centered and comply with that spirit of the Framework. In fact

this perspective is in line with good software development, which maintains technology should

always be customer focused.

Within the current state of technology in the field several types of technology relevant to

response and recovery will be examined. The types of technologies are currently transforming

the delivery of services and include: social and crowdsourced media, enterprise resource

planning (ERP) software, logistics software, remote sensing and geographical information

systems (GIS). ICT has become so important that many of the larger international organizations

are stepping into the role of venture capitalist and funding research and development in these

areas; for example, the UNICEF Innovation Fund provides investment at the 25k and 100k range

as well as 1million dollar grants for more mature ICT projects (UNICEF, 2017). Oxfam is

another example having funding HELIOS, a supply chain management system the NGO has

given to partners who could never afford such a project (Stephens, 2014; Helios Foundation,

2017)

During initial response crowdsourcing and social media have proved invaluable as

information sharing tools during the events and days following. The implications of the use of

crowdsourced data In Haiti and New Orleans will be looked at as case studies. The effect that

such grassroots efforts has on the UN’s priorities will be part of this discussion.

Tools developed for data gathering, surveying and cloud storage and their current usage

will be discussed as well as the implication of their use in the field. The implications of such

web-based tools will be outlined as SAHANA and Oxfam’s HELIOS are illustrated.


Relatedly, the increased use of Geographical Information Systems (GIS) and the

implication of the visual use of data in dashboards on the web is covered. Well-developed case

studies such as USHAHIDI and its use to give crowdsourced information context, and uses of

imagery to predict African drought are contained in that subject area. Included in this evaluation

will be a review of the issues of the management and the sharing of imagery all the stakeholders

of the Humanitarian Response system.

The explosion of big data and its use in rapid ethnography and the attendant problems of

data verification in crisis situations will also be examined. Governance of big data is a key issue

as the rules of usage of personal data must be established with clients if the integrity of the

humanitarian mission is to be preserved. Technology practitioners will need to be well informed

on the requirements of how that data is to be displayed depending on the user’s role. The use of

big data in response to the 2010 Chilean earthquake and in the CEWARN system will be used to

illustrate these issues.

In all cases, the discussions will be united by the central fact that ICT tools use and

development is as uncertain and ever-changing as the wicked problems these ICT tools are

addressing. In this way, ICT use can be thought of as a Wicked Solution with ever evolving

solutions. What this means and why this state exists, is discussed next.

ICT as “Wicked Solution”

One reason the development of ICT systems for disaster response is such a wicked

solution is the complexity of the system and the multiplicity of stakeholders these tools must

serve. From there, a complex system of response involving the UN and organizations underneath

its umbrella including the World Food Programme (WFP) and United Nations High

Commissioner for Refugees (UNCHR); international organizations (such as the International


Federation of Red Cross and Red Crescent Societies), which operate as a federation with country

offices that are auxiliary to country governments; donor nations, non-governmental organizations

(NGOs) with offices in both donor nations and the field, military actors and local response

organizations has evolved (Balcik, 2008). Each type of organization operates under different

rules. For example, the UN and NGOs are different entities in law (Seaman, 1999).

This complex system of relief is expensive to run and has swelled to 28 billion in funding

(Development Initiatives, Inc., 2016). The system serves 677 million vulnerable people of whom

67 million are displaced persons (Development Initiatives, Inc., 2016). This funding is mostly

being channeled through six major humanitarian-related UN agencies which coordinates

spreading this funding. These organizations have different cultures and different competencies.

ICT helps address these coordination efforts, but the different cultures and competencies between

the groups needed a clearinghouse operation. The United Nations as the central clearinghouse for

standards and funding has taken on being an important stakeholder in ICT development.

The United Nations has at times been pushed into this role unwillingly and unwittingly.

There is a phenomenon in information communications technology where unintended uses are

uncovered by users not anticipated. In UX circles, when users do this it is called “taking the cow

path” and not the marked road set out by the product designers. For a time until about the

earthquake in Haiti, the technology rushed ahead of the UN’s ability to anticipate all the changes.

In fact, the United Nations had to be pushed into formalizing ICT capabilities by informal

civilian groups whose capabilities had leapfrogged the UN’s own knowledge. These actions were


enabled by off-license use of technology for humanitarian action. 3 One reaction was the

formation of the Digital Humanitarian Network (DHN) which serves a bridge between informal

groups and formal humanitarian assistance agencies (Meier, 2015, p. 19).

Figure 3: Digital Humanitarian Network (Digitial Humanitarian Network , 2014)

The founding of DHN signals a change in culture within the United Nations if it were to

incorporate ICT into its culture: movement from a system of command and control to a hybrid

model where centralization of funding and of mission could still exist but where network models

3 A group of academic mappers and volunteers began the field of crisis mapping in response to a

call of action during the Haiti earthquake. This core of volunteers headed by Patrick Meier became known

as the Standby Volunteer Task Force (SBTF). The UN approached SBTF for assistance during the Arab

Spring crisis in understanding how to monitor social media and map the events going on in the Middle

East specifically Libya. Out of these activities other groups started to emerge such as ESRI’s working

group on humanitarian assistance and GIS Corps. DHN was founded in 2011 to deal with this

coordination (Meier, 2015, pp. 57, 63)


could be applied to response and to development of tools for response. Another more recent

response is the Centre for Humanitarian Data in The Hague. The hub will encompass

stakeholders from the UN, NGOs, the private sector and academia. The centre’s mission has

been stated by OCHA to be the following: “The centre will provide support in three areas:

increasing the reach and impact of OCHA and its partners through the provision of data services

such as common standards, open platforms and interactive data visualizations; creating a trusted

environment for data sharing across the sector by promoting good practices in data policy; and

increasing the data literacy of humanitarians” (UN, 2016). The center will be able to be followed

at https://centre.humdata.org/ and is an initial three year project: part of the goals of the centre

will be to develop data standards of interoperability that will allow all of the member

organizations who respond to not only have access to data but know that they are talking the

same language for they possess the same ICT standards. Continuing today, the lessons of agile

project management and product development are still having a profound effect on humanitarian

response organizations.

Attributes of an Effective Humanitarian Response System

For organizations with humanitarian missions, humanitarian response operations are

characterized by high uncertainty and ever changing situations. As a result, humanitarian supply

chains need to first, possess agility so they can respond to ever changing demands and supplies

brought on by disruption brought on by disaster. Agile organizations, for example, have access

to information on what and where help is needed. For example, Typhoon Haiphan damage maps

allowed response organizations to prioritize where and what help would be sent. These maps also

allowed different suppliers to coordinate. In addition, agile aid organizations have learned to

prepare beforehand and stockpile key supplies that are always needed such as water and shelter.

https://centre.humdata.org/


Two, these organizations must adapt to each situation when responding for each situation is

different. This adaptability must include being able to identify new sources and new partners in

each new region response organizations enter (Lee, 2004). For example, Hurricane Katrina led to

a disruption in the transportation system the government had been expecting to use and FEMA

failed to be agile. Food and water could not be delivered for FEMA’s system could not respond

quickly to the ever changing environment. Ultimately, too, the agility within these organizations

must include being able to rapidly identify and collect the requirements of customers on the

ground – a client base which changes depending on location of the disaster and scope of its

causes. Furthermore, and this may be the most challenging aspect for humanitarian

organizations, is the alignment between organizations rushing to respond to the same situation.

As seen in the Haiti Inside disaster video focusing on MSF’s efforts in Haiti, a lack of

coordination and a lack of communication and data transparency between various NGOs,

national organizations, the UN and military teams can lead to confusion and a delay in response

(Lee, 2004).

UN's View of ICT in in Humanitarian Response and Assistance

All this activity has meant that the UN has taken an active role in defining, developing

and supporting activity in ICT usage within the standards of Humanitarian framework itself. To

the UN, digital tools hold the promise of promoting efficiency and speed to disaster while also

promising to potentially strengthen prevention efforts while reducing vulnerability. Prioritization

of ICT is engrained in its own framework, the Sendai Framework, as seen in the following

analysis. The Sendai Framework, the UN's framework for emergency management and reducing

risk, has defined as its path to action four priorities:

Priority 1 Understanding disaster risk


Priority 2 Strengthening disaster risk governance to manage disaster risk

Priority 3 Investing in disaster risk reduction for resilience

Priority 4 Enhancing disaster preparedness for effective response, and to «Build

Back Better» in recovery, rehabilitation and reconstruction (United Nations Office

for Disaster Risk Reduction (UNISDR), 2017)

ICT’s importance as a communication tool, a data collection tool and an enabler for

quicker and more encompassing analysis is implicit within each of these priorities:

Priority 1 Understanding disaster risk: On risk reduction, technologies around space

technology application and GIS for hazard monitoring and risk identification were found

to be key. Access to ICT as a proxy of access to risk information through the use of

mobile cellular network coverage, proportion of households with a radio, a TV, a

computer and internet access at home could as well help address Disaster Risks.

Priority 2 Strengthening disaster risk governance to manage disaster risk: The

development of early-warning systems and the development of processes to get this

information into first-responders hands. Again this involves the development of agile

process and an open culture versus a command and control one.

Priority 3 Investing in disaster risk reduction for resilience: As noted by the Noeleen

Heyzer, Executive Director, United Nations Development Fund for Women (Hameed,

2007), ICT can be treated as a business sector but investment in ICT capability at the

local level is an enabler for growth. Investment in disaster leading to growth can allow

for more economic resiliency and infrastructure resiliency as well as direct gains in

preparation and resilience through access to data and technology that help prevent


Priority 4 Enhancing disaster preparedness for effective response, and to «Build Back

Better» in recovery, rehabilitation and reconstruction: ICT can be used to increase

awareness of disaster potential, inform the creation of better preparation plans through

better data, better analytics techniques and better forecasting. ICT can be a country’s best

mitigation technique.

In general, the argument should also be noted that disaster management must be

incorporated into any development system, incorporated holistically rather than as a single issue.

Since disasters have such impact on countries and their GDPs and communities’ abilities to

achieve growth and resiliency, proper disaster management has been recognized as a key

requirement towards achieving the Millennium Development Goals (Changawonsae, 2017). ICT

itself is a noted enabler by the UN of achieving those goals as well as allowing for better

response, preparation and eventually mitigation.

Current State of ICT Usage in Humanitarian Response

As a result of being a UN priority as well as a grassroots phenomenon in response, an

explosion of ICT activity has occurred within Humanitarian Response operations, scaling with

the increase of disasters within the US and internationally. However, this activity did not begin

until recently – around year 2000 - due to the nature of funding and risk aversion within the

humanitarian system. Unlike within the business sector where speed and failure is everything

(Agile Methodology, 2008; Ries, Minimum Viable Product: a guide, 2009; Ries, The Lean Start-

up, 2011), the Humanitarian Response system is particularly risk averse given that failure can

result in loss of life and human suffering. UNICEF recognizing this, began its own innovation

fund and allows for a “failure rate as high as 90% if there is chance of huge impact that a project

can potentially create” as high-risk projects often are not able to gather funds under current


funding scenarios (UNICEF, 2017). Many major universities and NGOs – in recognition of

increased use – have held conferences as well as well as added working groups in order to cover

this issue (University of Colorado, Colorado Springs Trauma, Health and Hazards Center, 2011;

International Federation of Red Cross and Red Crescent Societies, 2013; NP Tech for Good,

2017). These working groups and conferences in many ways have led to more questions than

answers as much evaluation work is still needed of these nascent developments. All this interest

has meant Public-Private partnerships are not uncommon. Deloitte, for instance, provides pro-

bono assistance, including how to procure funding for non-core functions (Deloitte, 2017).

INSEAD, the university, has created a new Humanitarian Logistics research center in

conjunction with Kuhne Logistics University. This center now involves many formal

humanitarian partners such as World Vision, World Food Programme, as well as Johnson and

Johnson and UPS (INSEAD, 2011). But as Koch discussed in his 2014 thesis, the explosion of

stakeholders involved in the development of ICT for emergency has led to a crisis of

coordination and cooperation among stakeholders (Koch, 2014). Different languages are used,

much of the development is through informal channels and conflicts are not uncommon. We will

see some of these conflicts in play as we review our case studies. The types of ICT having

impact on humanitarian relief organizations is diverse. The following section will review and

detail specific cases in key areas.

ICT Case Studies

There are several areas of existing and of developing ICT not covered here. Certain key

events and their use have been chosen to note key lessons learned in the last 10 years. These

include mobile phone use, GIS and remote sensing technologies, Big Data techniques and the

growth of the cloud.


Key Area 1: Mobile Phone Use. Mobile communication technology has been the most

rapidly adopted technology in recorded human history. Two billion people worldwide now have

access to the Internet, with half a billion of these accessing the Internet by mobile phone number

set to double by 2015. Indeed, mobile data traffic is projected to increase eighteen-fold by 2016,

and the Middle East and Africa are forecasted to have the strongest mobile data traffic growth of

any region in the world, followed by Asia. Meanwhile, the number of Facebook users is rapidly

approaching 1 billion while more than 100 million active Twitter users are sending over 1 billion

tweets every week. Finally, more than 500 million Skype users are now talking for free thanks to

voice-over IP technology. Staggering though these figures may be, the information revolution is

only just getting started (Meier, 2015). Although Western media tend to concentrate on the roles

of foreign relief workers in disaster response, only about 10% of people affected by emergencies

actually receive direct help from relief agencies; the rest are saved by neighbors, friends, and

family and rebuild their lives with the help of local institutions and diaspora networks (Pang,

2014).

Haiti: use of SMS and crowdsourcing. Case study of 2010 earthquake follows:

Situation: Major earthquake in Haiti in 2010 leading to massive death and

destruction. Data was scarce but volunteers begin mapping tweets and SMS

messages containing key messages on GIS maps using Ushahidi, an open source

mapping API. The US Coast Guard, the US military, Medicins Sans Frontiers

(MSF) and the UN all ended up using these maps they found through publicity to

find people and to trace supplies.

https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&uact=8&ved=0ahUKEwjbvMrBy_XSAhVS_mMKHY_BAJUQFggcMAA&url=https%3A%2F%2Fwww.ushahidi.com%2F&usg=AFQjCNGbfQK6d4jprLob_AASwl66jM6ubw&sig2=haxz3Igi3pNzT7PDd_CE9Q&bvm=bv.150729734,d.cGc


Analysis: Taking advantage of SMS networks and crowdsourced information

proved to be an effective way to gather information for response networks when

other more traditional networks had failed.

Lessons Learned: The importance of open sourced mapping allows for more help

and the quick martialing of resources through groups like the SBTF that grew out

of the Haitian mapping effort. The effort was made even more effective when

local people and diasporic populations who knew the local area became involved.

However, all the new information led to information overload and was not

necessarily able to be processed by Humanitarian response teams on the ground.

In terms of tool design, teams in post-operation interviews reported that

fragmentation occurred on two levels: those of the back-end systems and those of

the tools used in the field.

Sources: (Meier, 2015), (ELHRA, 2017), (Harvard Humanitarian Initiative, 2011)

New Orleans: Use of crowdsourced information during Hurricane Katrina. Case study

of Hurricane Katrina and the lessons learned:

Situation: Cellular phone system went down during Hurricane Katrina leaving on

the ground response organizations unable to coordinate and affected populations

unable to contact loved ones.

Analysis: SMS proved able to still be used to coordinate teams and messages

were sent across area code networks to let people know the location of their loved

ones. Information was informally placed on websites still operation such as the

Times-Picayune.


Lessons Learned: Simple technologies can prove to be as effective if not more so

than complex systems that break down. Processes need to be put in place to take

this unstructured information and turn that information into structured

information. No agreed upon source of truth for information.

Sources: (Meier, 2015), (ELHRA, 2017), (MONTANDON, 2006)

Further developments in Mobile Phone Use. The refugee crisis is proving mobile use is

continuing to be as important as a resource as food, water and shelter for responding to disaster.

Refugees in this mobile time do not want to stay put where aid organizations tell them and apps

from ones that tell them of sea conditions to communication apps such as Skype and WhatsApp

let them do that while allowing them to stay in touch with family (Brian Frouws, 2016). The

United Nations High Commissioner for Refugees as a result had to shift policies in 2014

delivering aid where refugees went and not in camps they established (Sancton, 2016). In a more

recent disaster, Somalian emigrants are using the group function in WhatsApp to reach and help

family members with cash as the famine hits before aid groups are even on the ground (Quinn,

2017), another example of informal aid.

While all this movement can prove in some ways a logistical nightmare involving many

jurisdictions, what all this mobile phone use is allowing is the gathering of data which can be

used to do things like predict outbreaks and disease spread as in-crisis populations move through

the use of gathering location data from SIM cards (Bengtsson L, 2011). Cell phones can also be

used to connect populations of the diaspora.

Another development in the use of SMS phone data has been the implementation of

Automatic Interactive Voice Response (ICR) systems. Used in Haiti and in Sri Lanka, AIVR

systems allow two way communication with affected communities who have less familiarity


with SMS or possess lower literacy by sending standard information back to inquiries through

SMS.

Key Area 2: Open-source cloud based solutions. The clients of the humanitarian

response system are not the ones paying for assistance: ICT costs are paid for by donors so there

is added incentive to keep costs down beyond profit. In addition, the complexity and global

nature of disaster mean software that scales is very important. Open-sources cloud based allow

that, i.e. the advantages of the cloud based solutions are:

1. Lower capital expenditures

2. Lower barriers to entry

3. Immediate access to a broad range of application software

4. Real-time scalability

The following are some examples of cloud-based solutions that took advantage of the

cloud’s positives to improve response effectiveness. One used the cloud to allow for greater

access to greater amount of participants and the other system, focused on logistics, created

greater efficiency for Humanitarian Supply Chains.

Sahana Disaster Management System in the Aftermath of the Indian Ocean Tsunami.

Case study and lessons learned follows:

Situation: Sahana4, an open source software -based system developed by Lanka

Software Foundation5 and now run by the Sahana software foundation, is a suite

4 The word “Sahana” means “relief” in Sinhalese, one of the national languages of Sri Lanka.

5 The Mission of the Sahana Software Foundation is to help alleviate human suffering by giving

emergency managers, disaster response professionals and communities’ access to the information that


of web-based applications that provides solutions to the problems arising in a

post-disaster situation (Sahana Software Foundation, 2017) in the immediate

aftermath of the 2004 Indian Ocean earthquake and tsunami. Our community has

since grown to include experts in emergency and disaster management as full

partners in the software development process. This is extremely unique in the

governance of software projects, and a unique strength of the Sahana Software

Foundation.

Analysis: What made Sahana useful is the system was easy to use and focused on

what was needed in response initially.

Lessons Learned: The Sahana system illustrates how effective requirements

gathering can be managed. This includes building local capacity and taking

account the requirements of people on the ground (Changawonsae, 2017). The

Sahana projects also shows that the technology can be free, and training can be

free, which is important to getting less developed countries to consider adoption

by their local capacity. Hence, resilience, can be built through potential for

remuneration through consulting and implementation.

Sources: (Lanka Sofwtare, 2017), (Changawonsae, 2017), (Sahana Software

Foundation, 2017)

Oxfam, The Fritz Institute and Helios Disaster Supply Chain Solution. Case study and

lessons learned follows:

they require to be better prepared for and respond more quickly to disasters through the development and

promotion of free and open source software and open standards (Lanka Sofwtare, 2017).


Situation: Oxfam in 2013 was looking for an accessible and easy to use supply

chain software solution that would allow the organization to automate its supply

chain. Due to the organization’s low IT literacy and inexperience with such

solutions, Oxfam chose HELIOS for its solution based on usability (Blansjaar &

Stephens, 2014, p. 59).

Analysis: Overall time and costs spent on logistics declined. Improved planning

and transparency led to better fulfillment, supply chain was qualitatively found to

have improved and management felt they could make more data driven decisions

(Blansjaar & Stephens, 2014, p. 61). However, benefits were overall not clear for

time spent increased in other areas reflecting the weakness experienced by other

organizations in that processes had not evolved along with the IT infrastructure.

As the open-source solution was rolled out to other organizations, prejudices of a

non-bespoke system had to be overcome with training (Blansjaar & Stephens,

2014, p. 69).

Lessons Learned: Additional training and optimizations have led to better

adoption of the HELIOS system. Paperwork has now been reduced 75% (Fritz

Institute, 2017).

Sources: (ELHRA and OXFAM, 2017), (Blansjaar & Stephens, 2014), (Fritz

Institute, 2017)

Further developments in Cloud Software Use. Helios has been made open to other

organizations and more analysis on its efficacy is being made. Cloud allows for easy access,

lower costs for organizations: this allows easier technology sharing and local skill development

that build resilience.


Key Area 3: Remote Sensing and Geographical Information Systems (GIS). A

geographic information system (or GIS) is a system designed to capture, store, manipulate,

analyze, manage, and present spatial or geographic data (ESRI, 2017). Satellite imagery through

remote sending and geographical information systems technology has become crucial, for as

seen in our Mobile Phone/SMS case studies, the visualization of information on maps give first

responders situational awareness and provide new ways to display and analyze information

(Teutsch, 2010). Virtually all the solutions touched on within this paper incorporate some type of

GIS component within their architecture whether the emphasis is social media collection, client

data collection, logistics and/or response coordination whether in a portal, dashboard or ERP

solution. The follow case studies are illustrations of how GIS have been used in response and

where the technology is going:

World Vision using Ushahidi Version 2.0. Case study and lessons learned follows:

Situation: The Speed Evidence project was envisioned in 2010 By World Vison

after the Haiti Earthquake and Pakistan Flood. World Vision response teams found

the data collection and management tools they were using were not sufficient to

process the large amounts of data being gathered through social media and SMS.

World Vision UK wanted create a platform that allowed responders on the ground

in real time to receive data from SMS, social media, and other websites, and allow

users to filter and process dashboards quickly (USHAHIDI, 2017). WorldVision

chose the Ushahidi platform V2 for this project, and the Ushahidi Solutions Team

customized the existing software to work with a real time SMS gathering platform

in Frontline SMS and created a bespoke dashboard with geographical

information. The Speed Evidence platform was made available for free to any


organization or agency after 2013 to use it. The software has been used by, among

others, a consortium of NGOs called Communicating with Disaster Affected

Communities (CDAC) network working in Somalia, in Haiti, and notably in the

Philippines Typhoon Haiyan response.

Analysis: Placing the SMS data in a geographic context was reported to speed up

data consumption by first responders. The simple input tool and real-time

dashboard allowed the leveraging of volunteers including non-ICT professionals

as the platform did not require technical GIS knowledge to use.

Lessons Learned: Open sourced mapping tools allows GIS to be more effective

and accessible to organizations with low budgets. GIS projects are more effective

when people involved who know the local area are involved. However, privacy

concerns are still an issue.

Sources: (USHAHIDI, 2017)

African drought mapping using Geographical Information Systems (GIS) and Remote

Sensing data. Case study and lessons learned follows:

Situation: In 2011, a severe drought led refugee populations struggling with

conflict to surge to over a half million people in Somalia. In 2014, drought

conditions returned to East Africa and have persisted for three years. Around

11.5MM people are currently classified as food insecure and there are 2.3MM

refugees (UNOCHA Regional Office for Southern and Eastern Africa (ROSEA),

2017). In 2011, a drought map was created to tell the stories of conflict and

famine using GIS software that allowed for the innovative layering of affected


populations stories from social media on top of polygonal base layers from the

UN showing drought information, conflict locations and refugee camp locations.

Analysis: The map proved to be an effective tool in raising awareness and was

used by the press to give voice to the affected in their stories.

Lessons Learned: Initiatives such as the African Drought Map lead to better

engagement on the part of government leaders. The availability of such data has

led to more preparation among affected nations and a 40% less cost per capita for

the 2017 response so far (UNOCHA Regional Office for Southern and Eastern

Africa (ROSEA), 2017).

Sources: (UNOCHA Regional Office for Southern and Eastern Africa (ROSEA),

2017), (ESRI, 2011/2012)

Further developments in GIS use. Current development in GIS are focusing on access.

Satellite data, GPS data and other layers are expensive and missing for many areas of the world.

Current efforts such as Open Street Map and MapSwipe are trying to improve access to data and

improve its accuracy through crowdsourcing. Support of open source tools and the support of the

use of crowdsourced data as part of response will continue to improve all response activities.

Key Area 4: Big Data and Data Interoperability. In 2015 Ms. Gwi-Yeop Son, Director

of Corporate Programmes on behalf of the Under-Secretary-General and Emergency Relief

Coordinator for OCHA, emphasized how essential data analysis and of the optimization of that

data analysis is to emergency response operations globally; however, “worldwide only 0.5% of

the data produced is being analyzed, while an estimated 25% of the data can be of use to

someone”. She posed the question and the challenge: how can the humanitarian sector identify

and analyze data in an effective way and make a difference in humanitarian response, and in

https://www.openstreetmap.org/#map=4/49.95/-1.93


ways that minimize risk (UN General Assembly, 2015)? Part of the answer will come through

big data techniques and in concert, the development of data interoperability standards.

Big data is not one thing but a set of non-traditional databases that have been developed

to deal with data problems that can’t be solved with traditional relational databases due to the

volume of data collected, the velocity or rate at which the data is collected, and the variety of

sources for the data such as social media, mobile/SMS, GPS, etc. that have not been generally

gathered with old techniques (Amazon Web Services, 2017; Prasad, Zakaria, & Altay, 2016). Big

data is relevant to Humanitarian Response Organizations (HRO) because the data gathered by

them shares these characteristics: the data used during response is digitally generated, is varied

and can be analyzed by computers; the data is passively produced at a high volume and velocity

due to being a product of client’s daily lives before, during and after response; the data can be

automatically collected at a great rate such as with APIs as seen in the SMS and GIS case studies

and analyzed in real time (velocity) and with some location information (variety) (UN Global

Pulse, 2012, p. 17)6. The potential of big data is not only one of lower costs and better informed

response, but affects the accuracy of preparedness, of mitigation and of economic development

models as well. The speed of big data and its cost savings will enable the building of better,

6 "Global Pulse is a flagship innovation initiative of the United Nations Secretary-General on big

data. Its vision is a future in which big data is harnessed safely and responsibly as a public good. Its

mission is to accelerate discovery, development and scaled adoption of big data innovation for sustainable

development and humanitarian action. The initiative was established based on a recognition that digital

data offers the opportunity to gain a better understanding of changes in human well-being, and to get real-

time feedback on how well policy responses are working” (UN Global Pulse, 2012, p. 18).


quicker models in line with the ever-changing conditions of disaster planning. Research has

shown that the construction of better models can lead to more resilience among targeted

communities as programs can more accurately programs to the specific needs of that location

(variety), with more dynamism (velocity) while handling more data (Altay, Prasad, & Tata,

2013).

Chilean 2010 earthquake and The Analysis of Social Media Data. Case study and

lessons learned follow:

Situation: 2010 earthquake occurs and crisis mapping volunteers are swamped

with 5 million tweets of disaster data that overwhelmed volunteers.

Analysis: Later natural language processing analysis was able to show that fewer

than 1% of the tweets were invalid as patterns in tweet swarm showed community

responded when false data was presented (Meier, 2015, p. 147).

Lessons learned: Machine learning can help overwhelmed volunteers make sense

of data that ordinary analysis techniques such as frequencies, regressions and

cross tabs cannot.

Sources: (Meier, 2015), (ELHRA, 2017)

The Conflict Early Warning and Response Mechanism (CEWARN) for early detection

in man-made disasters. Case study and lessons learned from this project follow:

Situation: CONFLICT EARLY WARNING AND RESPONSE

MECHANISM, CEWARN, for short, launched in 2002 as a co-operative initiative of

the seven IGAD (Inter-governmental authority on development) member countries on

the African continent: Djibouti, Ethiopia, Kenya, Somalia, Uganda, Sudan and

Eritrea.

http://www.cewarn.org/


The basic underlying mission of CEWARN is to assess situations that could

potentially lead to violence or conflicts and prevent escalation. CEWARN is an

interesting case study for big data techniques being used to gather and to analyze in

real time social media and other types to media such as news reports to identify

patterns in that communication that lead to early warning. The function is carried out

by collecting and discussing information regarding the outburst and elevation of

probable violent conflict in the region occupied by the IGAD countries, analyzing and

processing this data, and coming up with alternative routes of response.

Analysis: National collaboration and culture changes to transparency between several

government and non-governmental stakeholders such as Conflict Early Warning and

Response Units (CEWERUs), National Research Institutes (NRIs), and Field

Monitors (FMs), have been undertaken in three main geographical clusters – clusters

in this context meaning geographic areas designated by the project for analysis. These

clusters were the Karamoja cluster (includes cross-border regions of Ethiopia, Sudan,

Kenya, and Uganda), the Somali cluster (encompassing cross-border regions of

Ethiopia, Kenya and Somalia), and the Dikhil Cluster (cross-border regions of

Djibouti and Ethiopia). The governments and NGOs operating in the areas in

questions were able to take into account climatic situations such as drought, flooding,

food security and famines using the web-based models and the visualized dashboards.

The early warnings from these dashboards been credited by the member countries

with reductions in violence the geographic clusters designated by the project.

Lessons learned: Transparency and data interoperability is crucial to the success of

big data projects. These models could not have been built unless the member nations


in these projects were willing to share information. Self-empowerment of local actors

also speeds implementation as the second generation of the tool was already designed

in 2015 and being released to other geographic areas after the first generation took

year. Early engagement in project design and management also leads to more buy-in

among local actors which leads to more local action and empowerment, all keys to

success.

Sources: (IGASCD, 2017)

Further Developments Concerning Big Data. Big data is not a replacement for other

statistics but add depth and the potential for another level of analysis and outcomes. As

reiterated, these outcomes include:

1. Early warning: early detection of anomalies in populations using digital services and

in digital content such as social media can enable faster response in times of crisis;

2. Real-time awareness: Machine learning in partnership with Big Data can give a better

snapshot of local context at each moment that can inform the design and targeting of

programs and policies;

3. Real-time feedback: the ability to monitor a population in real time enables real-time

feedback as well through techniques such AIVR (ELHRA, 2017) and allow the

Humanitarian Response System to adjust where policies and programs are failing.

(UN Global Pulse, 2012, pp. 36-37)


Strength, Weakness, Opportunity and Threat Analysis (SWOT): An

Overview of Humanitarian Response System’s Readiness to Use

ICT

Currently, as seen in all the interest around the topic, a tremendous amount of awareness

exists around what the possibilities for ICT use in Humanitarian response can be. The

tremendous uptake in mobile use in developing countries and the huge impact humanitarian

response non-professionals have already had through organizations such as SBTF and

OpenStreetMap shows effectiveness current tools can already have within the context of

response.

Figure 4: Strength, Weakness, Opportunities and Threats (SWOT) Analysis, (Author Created 2017)

However, there are many threats and weaknesses in this cluster. Current UN attempts to

establish new centers of excellence around big data, data collection and the incorporation of ICT

goals into its own framework are all different kinds of recognition that more work needs to be

completed (UN Global Pulse, 2012). The system has recognized that ICT will be key to


encouraging cooperation and data sharing, especially as the global system has evolved from a

centralized command centered in the donor nations of the West to a more, distributed, local-

organization based system. However, is the patchwork system of humanitarian assistance

organizations that arose after WWII ready to use ICT? The ability of the system to adapt to a

distributed, multi-polar mode of operation and adopt a more transparent, cooperative culture

when it comes to data sharing is uncertain (Barton, 2009). But ICT is most effective within

operational cultures willing to operate in a distributed fashion (Koch, 2014): the very basis of

social media and communications technology are transparency, security, community, usability

and availability. As these technologies rely on social collaboration, the very nature of the culture

must be open (Asimakopoulou & Bessis, 2010). For example, in our Helios example, each

organization offered wanted its own bespoke system through the software out of the box covered

most needs (Blansjaar & Stephens, 2014), a misunderstanding of the openness that is open-

source software and code sharing.

Security and use of data is another issue. In an age of several ideological wars on terror,

can Humanitarian Response maintain an open culture or risk alienating the IT, libertarian leaning

workforce they need to develop these tools? On one hand, the IT workforce as part of the

military-defense complex has been willing to participate in covert projects – Palantir

(http://www.palantir.com) is a great example - but when humanitarian objectives being the goal

will the temptation to use data to police as well as a help be a threat to projects and endanger the

ability to use needed private sector involvement?

This culture gap is another threat. Part of that cultural change will also require those same

developers to embrace decentralization of their control – in addition to organizational

decentralization - and their own de-emphasis on projects. Humanitarian organizations need to

http://www.palantir.com/


invest in capacity building and awareness raising of how to use data collection and analytical

techniques if one, ICT organizations are to get local buy-in of actors on the ground and two, to

achieve resiliency of these systems, and three, build resiliency in these communities. (Meier,

2015). The process must involve all organization and the quality and definition of the data must

be determined at all levels from designer to client to ensure the data being used to make

decisions in response meets users’ needs. Involving local communities and stakeholders will help

ensure ethics are ensured (Koch, 2014; O'Donnell & Malallah, 2015).

The UN cluster system itself also leads to information management fragmentation. This

is another culture and process gap that will need to be overcome: the cluster system leads to

competition and distrust between groups as well as fragmented back-end systems due to the

siloed system. The development of interagency dataset standards such as the Common

Operational Dataset (COD) is a step forward in building a culture of analytics within UN as well

as the development of centres of excellence around data as discussed earlier, but back-end

systems will need to be integrated if a true source of truth is to be developed (Harvard

Humanitarian Initiative, 2011, p. 21).

The development of a source of truth will also entail the integration into the Sendai

Framework a code of ethics that is standard across the Humanitarian Response System defining

global priorities for emergency response. Currently, the system suffers from a weakness of “No

minimum standards or professional ethics for the provision and use of ICTs in humanitarian

action; An absence of guidelines for navigating an increasing reliance on third party actors,

particularly private sector companies, to provide basic data and infrastructure; and A lack of

identified and agreed legal and human rights standards for the use and provision of ICTs and


critical data” (UN Global Pulse, 2012, p. 16). If the credibility of the humanitarian mission is to

be protected, ICT ethics must be integrated into the framework.

Lack of performance measurement built into the systems as highlighted in many of the

cases shows is an additional weakness. The Humanitarian Response system has exhibited an

overdependence on qualitative measurement ( (Blansjaar & Stephens, 2014, p. 61; ELHRA and

OXFAM, 2017; Digitial Humanitarian Network , 2014). Without performance measures, the

ability to learn and to optimize becomes impossible. However, once in place, the Humanitarian

Response system becomes enabled to measure, test and optimize, a process that has begun as

seen in this paper’s literature review.

Key to testing will be the development of mechanisms from which to gather feedback

from direct clients and affected communities (Smith, 2009). AIVR systems and customer forums

have been initial forays into gathering this data, but more sophisticated systems needs to be

developed. As part of a requirement to receive funding, all ICT projects should provide a way to

gather this feedback, feedback that not only increases the usability of the projects but also

increases transparency, demonstrates the response teams commitment to achieving its goals in

protecting the dignity of users, improve security by allowing users to report abuses, unintended

consequences, and misuse, providing an early indicator that a process or plan is not working, and

provides information that highlights cases of fraud, corruption or other types of abuse (Smith,

2009; Harvard Humanitarian Initiative, 2011; UN Global Pulse, 2012).

The data itself is both a strength and a weakness too: a strength for there are tons of it and

both clients and organizations are asking for it; a weakness for there is so much to analyze. To

reiterate, the data used during response is digitally generated, is varied and can be analyzed by

computers; the data is passively produced at a high volume and velocity due to being a product


of client’s daily lives before, during and after response; the data can automatically collected at a

great rate such as with APIs as seen in the SMS and GIS case studies and analyzed in real time

(velocity) and with some location information (variety) (UN Global Pulse, 2012, p. 17)7.

However, organizations have been challenged in having both the capability to parse through all

the data, analyze it properly and having the staff to make the right choices on how to analyze it

(Harvard Humanitarian Initiative, 2011).

The data currently being collected has huge promise, but the data is best used when the

inherent biases, assumptions, features and lacks of that data is adequately understood and taken

into account when interpreting the data. These decisions take transparency and data science skills

not necessarily present –yet (UN Global Pulse, 2012, p. 36).

Last but not least, the threat of funding being pulled is always a present fear. In coming

years, costs will continue to climb as disasters increase as well as the number of people

impacted. Policymakers will be under pressure to take drastic action to curb skyrocketing

disaster costs in coming years. In so doing, expediency may arise and in the rush at higher levels

on the part of donor nations to find simple solutions that transfer costs (Fugate, 2017), real

7 "Global Pulse is a flagship innovation initiative of the United Nations Secretary-General on big

data. Its vision is a future in which big data is harnessed safely and responsibly as a public good. Its

mission is to accelerate discovery, development and scaled adoption of big data innovation for sustainable

development and humanitarian action. The initiative was established based on a recognition that digital

data offers the opportunity to gain a better understanding of changes in human well-being, and to get real-

time feedback on how well policy responses are working” (UN Global Pulse, 2012, p. 18).


opportunities to gain cost savings through comprehensive programs such as ICT development

may be lost.

These threats identified are all numerous and all important. Open dialogue however can

uncover opportunities to address all these issues while developing new skills in data science,

ICT, and related sectors on the ground. As long as the teams approach the development of ICT

tools with a customer focus, with an agile process, maintaining transparency, while testing and

training, prevention and mitigation could be attained, past response.

Next Steps for ICT in Humanitarian Response: A Proposal

So how to take advantage of the opportunities that these developments in ICT pose? To address

the issues of security, distribution, trust, transparency and agility, a proposal is made to create an

open data warehouse based on current big data concepts and that incorporates machine learning

techniques. This section will make some recommendations as to which technologies will be best

suited for the challenges outlined previously in this paper.

Figure 5: Development of a Wicked Solution: An Opportunity (Author Created, 2017)


Blockchain: The Basis for the Proposal

Any major tool to be developed to allow for effective global response will by necessity need to

be distributed and allow for the building and leveraging of social capacity at a local level. In

order to match the agile culture that has allowed for the Internet to be effective, the UN, its

formal HROs networks, informal NGOs will need to build tools that reflect in their structure the

agile and adaptive nature of best wicked solutions to wicked problems. My proposal is the

investment will be need to be made into an impartial and independent data clearinghouse built on

blockchain technology. For working purposes I have given this endeavor the codename Project

Tarikh-Kristal or Crystal Datum8.

Tarikh-Kristal would be a Customer Relationship Management (CRM) system of all the

recipients that have interacted with any of the participating members of the informal and formal

network. The CRM would be built using blockchain best well-know with its use for Bitcoin.

What is a Blockchain? A blockchain is a distributed ledger database that maintains a

continuously growing list of ordered records called blocks. Each block contains a timestamp and

a link to a previous block (Blockchain, 2017). An organization, let’s say in this case, the Red

Cross, can add a client’s data in the form of a block which is linked to the chain chain. Once that

blockchain is updated, everyone in the network – in this case, the network would be the

Humanitarian response system gets an updated copy. This duplication makes the system robust:

8 The idea is each data crystal will be the seed of a crystal snowflake that will building a strong

crystal palace kind of like Superman’s palace from which the evils of climate change, war, disease,

famine, and other disasters can be fought in a unified manner. Who said a thesis couldn’t be poetic?


if one organization’s network fails, say the Red Cross, other members of the network, say the

UN, Oxfam, MSF, other NGOs, would have copies of the blockchain.

Why the reasons for the multiple copies? Since the blockchain is distributed, each

member organization of the blockchain could verify and audit transactions. The security and

accuracy of the data blocks stored in the blockchain (the ledger) are maintained cryptographically

through the use of customer keys and signatures to control who can do what within the shared ledger

(UK Government Office of Science, 2016). Blockchains are different from other distributed

databases because they have transaction-level encryption that allows transactional rules to be

enforced, more granular than table-level encryption (Morrison, 2017). Entries can also be updated by

one, some or all of the participants, according to rules agreed by the network. Members of the

Humanitarian Response network have the opportunity to set the rules of those keys for various

functions whether they are micropayments, land deeds, good and supply chain transactions, health

records and other types of transactions that need to stay secure. The data in the chain could be

segmented by geography, organization, etc. and the transactions of each organization open or closed

as defined by the network but the data would still be there. This security can help maintain data

neutrality since no one organization would have central control of the data. Tarikh-Krystal when built

would have these rules built in.

Blockchain Benefits. Originally created to track financial transactions without the need

for a central entity, the blockchain additionally is viewed as having the potential to be an efficient

and secure way to transfer or share any type of information or asset. One is also able to layer

applications, such as smart contracts, on top of the blockchain, allowing for just response data

and data around clients to be recorded but services to be disseminated and open for

authentication by the whole network. The openness of blockchain technology allows for any

organization to use it while cutting out banks and this could be a game changer for people living


in low-income countries or fragile states at risk of economic collapse, corruption or conflict

where more traditional financial institutions have broken down. (Ghalib, 2011; Tapscott &

Kirkland, 2016). One example is BitPesa that allows businesses in China to pay their African

employees who then use the blockchain system to send the money back home to their families.

The Kenya-based startup, launched in 2013, uses bitcoin to facilitate low-cost, instant payments

online. (Ghalib, 2011)

Building a Source of Truth

A “Source of Truth” is a data source that gives a complete picture of the data as a whole

including the schema and the metadata. Tarikh-Krystal or similar blockchain systems would

serve as the source of truth for the Humanitarian Response system when it came to the

information of client’s and the resources provided to them whether in an one-time response or

over multiple interventions. What types of data would be stored within Tarikh-Krystal, our

Humanitarian Response blockchain?

1. Data Exhaust and Metadata: baselines can be set using what is known as data exhaust.

Data exhaust is the heart of web analytics and consists of the preferences, events,

clickstreams and transaction that occur through the internet. This information can gleaned

from log files, search indexes, JavaScript calls, and cookies by analytics tools such as

Adobe Analytics, Google Analytics, SEO tools, CMS, packet sniffers and other tools.

Sensors, cameras, GPS data and drones are all adding location and other behavioral data

to the digital archives that can be stored in Tarikh-Krystal and used Humanitarian

Response Organizations (HROs) to set baselines for projects and monitor the behavior of

their projects.


2. Content analysis and engagement analysis: user generated content such as social media

interactions and engagement, comments and virality can be analyzed for intent, behavior

and behavioral changes, and desires. Surveys and other market research can be

supplement this data to give a picture of the behavior of populations before, during and

after disaster. Crowdsourced data would be an important component of this type of data.

3. Sensors and the Internet of Things (IOT): Remote sensing through video, thermal

imaging, drones, and other environmental sensors will provides that sets baselines and

allows for the measurement of changes in human activity as well as the environment, e.g.

for example, detection of drought. Satellite or infrared imagery of changing landscapes,

traffic patterns, light emissions, urban development and topographic changes, water

levels, changes in air quality, changes in land usage and electrical usage would all fall

into this data category.

How do all these data sources tie into the Humanitarian mission and the applications for

the data stored in Tarikh-Krystal? The following table exhibits that:

Table 1

Tarikh-Krystal and Sendai Priorities

Sendai Priorities Data Source Uses

Priority 1. Understanding

disaster risk All Data Sources

Data Sharing and

Collaboration

Priority 2. Strengthening

disaster risk governance to

manage disaster risk

Content analysis and

engagement analysis, Data

Exhaust and Metadata

Supply Chain Tracking and

Shared Logistics

Priority 3. Investing in

disaster risk reduction for

resilience

Content analysis and

engagement analysis;

Sensors and

the Internet of Things (IOT)

Crowdfunding, Financing

Priority 4. Enhancing

disaster preparedness for

effective response and to

Data Exhaust,

Sensors and

the Internet of Things (IOT)

Supply Chain Tracking and

Shared Logistics,


“Build Back Better” in

recovery, rehabilitation and

reconstruction

Crowdfunding and

Humanitarian Financing

Techniques for analysis of data within Tarikh-Krystal

The democratic nature of blockchain granted by its openness also applies to the machine

and deep learning and attendant tools currently being developed and open-sourced. These are

the tools and techniques that will unlock the possibilities held by the data within the blockchain.

Machine learning is “a type of artificial intelligence (AI) that provides computers with the ability

to learn without being explicitly programmed. Machine learning focuses on the development of

computer programs that can change when exposed to new data” (WhatIs, 2017). These

techniques can be applied using standard tools such as R and Python. The implication for the

Humanitarian Response system is organizations will be to take advantage of Machine Learning

and AI techniques without spending years and tons of money in R&D as long as the right

personnel can be identified. A great democratizing effect is gained from this, allowing

individuals all types of organizations to build powerful applications. For example, WhatsApp –

an application touched on in our case studies - was able to build a global messaging system that

served 900M users with just 50 engineers, compared to the thousands of engineers that were

needed for prior generations of messaging systems (Mauro, 2017).

Types of Machine Learning.

1. Supervised Machine Learning Algorithms: Machine learning algorithms that make

predictions on given set of samples. Supervised machine learning algorithm searches for

patterns within the value labels assigned to data points.


2. Unsupervised Machine Learning Algorithms: There are no labels associated with data points.

These machine learning algorithms organize the data into a group of clusters to describe its

structure and make complex data look simple and organized for analysis.

3. Reinforcement Machine Learning Algorithms: These algorithms choose an action, based on

each data point and later learn how good the decision was. Over time, the algorithm changes

its strategy to learn better and achieve the best reward.

The Risks of Blockchain

1. Reduced control: Blockchain is attractive for its unmatched level of security. However, that

security means less control. Mistakes instantly becomes part of the blockchain. Contracts,

legal clauses, language, and rules but be checked and double-checked before they become

part of the blockchain.

2. Latency: Blocks take time to be added to the blockchain. Real-time applications may be

slowed down if the network attempts to add too many blocks at the same time. Currently

latency is about 15 seconds per block (Morrison, 2017).

3. Storage costs: One of the fundamental properties of the blockchain is that it has to conserve

the full history of the transactions and thus will forever grow. In addition, its distributed

nature requires thousands of nodes to make copies of the entire blockchain. As different types

of data are added to the blockchain such as videos, photos and sensor data – beyond simple

texts – storage costs could soar

4. Sybil attacks: Another less discussed vulnerability of the blockchain is its full nodes. If

copies of the entire blockchain are not stored on enough computers, attackers can potentially

fill the network with clients with false chains controlled by them. This is what is called a

Sybil attack. Malicious nodes are only problematic if they are so prominent that finding


honest nodes becomes too time consuming during authentications. Estimates say more than

half a network must be controlled for this to happen.

5. Forking: While vulnerability to attacks and to human mistakes are a major weakness of the

blockchain, recent events have shown that possibilities of mitigation play a huge role in the

credibility of the system, in particular with regards to forking. A fork occurs when a

communication failure between nodes occurs or when only part of the nodes update their

core script. Hence, the blockchain may split Most of the time, forks are only temporary and

disappear once communication is reestablished, and all the nodes are synchronized.

However, if conflict occurs, and a member of the Humanitarian blockchain were to split off,

two copies of the blockchain could occur and this could cause confusion and inefficiencies.

Additional Trends

Tarikh-Kristal or applications like it will not be happening in a vacuum. Progress will

continue in other sectors of ICT. The main key areas I predict will be the following:

The continuing evolution of logistics: logistics providers will continue to

innovate. Improvements will include improved tracking, data integration with

NGOs ERP systems such as HELIOS and improve features such as need analysis

and cost management.

3d printing: 3d printing as it improves will allow for the agile production of

needed supplies and materials on site, reducing some of the issues of materials

convergence and the need for just-in-time delivery. 3d printing will enable

production in areas where other forms of manufacturing and supply chains have

been wiped out.


GIS evolution: Next generation GIS will embrace open standards, better

visualization and interoperability with other systems.

Drones: drones will help improve data collection and supply delivery in areas

where other form of transportation and communications have been knocked out.

Internet of things (IoT): sensors from cars, containers, other forms of

transportation, smart cities will begin to gather more information that can be used

for response, recovery, preparation and mitigation activities.

Open data standards and collaboration: open data will allow for more cooperation.

Big data: Data storage techniques such as AWS’ redshift and blockchain will

continuing to change how data is stored, the speed at which IT can be accessed

and how secure the data is.

Machine Learning: a lot of meeting the goals of the Sendai framework will be

meeting using Machine learning techniques to build predictive models that will

allow better logistics forecasting and disaster forecasting. All of these data being

generated and stored in the blockchain will need to be analyzed. Big data

analytics requires finding patterns in data. Traditional analytics tools are not

designed to handle that much data or equipped with the algorithms needed to

perform pattern recognition. Big data applications such as image processing and

text analytics are still being developed.

Technology can’t be the sole innovation

What is going on in innovation is very exciting. However, the agencies involved need to

start tracking the funding and performing return on investment analysis. Performance

measurement will be critical to the success of these programs if donors are to continue funding.


Currently after exhaustive research and reaching out, the author of this paper has not been able to

secure a discrete breakdown of current ICT funding for Humanitarian response even for FEMA.

Until the analysis of spending and effectiveness, the Humanitarian response system risks chasing

after every new technological trends without learning.

Institutional innovation and a will to change the process and mindset of how the

humanitarian system is implemented will need to occur in parallel with the technological

developments. These changes will also be needed to allow the ICT network to grow in a secure

and open fashion. A blockchain system overlapped with a smart application infrastructure can

help bridge the gap between civil society organizations and government structures in situations

of weak or nonexistent civil institutions and communications infrastructure. Actors on the ground

can be empowered through the openness of the blockchain in a form like proposed in Tarikh-

Krystal. Such a system will help strengthen the horizontal linkages that exist between

stakeholders who need the ability to respond quickly, effectively, and appropriately in times of

disaster. The promise of technology is not as a solution to everything but as an enabler:

technology can’t be the sole answer to the problem or as Terry Vietor recently said at South by

Southwest (SXSW) and retweeted on twitter "If I hear someone say we’re going to hack the

refugee crisis I'm going to lose my fucking mind (Lapowsky, 2017)." Process, culture, and

technological change need to occur hand in hand.


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