Supporting Group Decision Making and
Coordination in Urban Disasters Relief
Efforts
Sergio F. Ochoa* — Andrés Neyem* — José A. Pino* —
Marcos R.S. Borges**
* Department of Computer Science, Universidad de Chile
Blanco Encalada 2120, Santiago 6511224, Chile
{sochoa, aneyem, jpino}@dcc.uchile.cl
** Graduate Program in Informatics
Núcleo de Computação Eletrônica and Instituto de Matemática
Universidade Federal do Rio de Janeiro, Brazil
mborges@nce.ufrj.br
ABSTRACT. When extreme events affect urban areas the response process should be fast and effective because the
population and civil infrastructure densities potentially increase the impact of such events. These situations have shown
the need to improve the group decision-making process and the coordination of relief activities carried out by
organizations inside and outside de disaster area. Most research initiatives do not address these challenges considering
the first responders working in the disaster area as decision makers. This paper presents a proposal to include first
responders as decision makers and it describes a technological platform to support decision making and coordination
activities among these first responders and the command post. The supporting platform provides digital communication
and information recording, representation and dissemination capabilities among the mobile workers participating in the
relief efforts. The platform could also be used to support activities in scenarios similar to this one, such as police and
military operations, and security operatives during massive social events.
KEYWORDS: Group Decision Support, Coordination, Emergency Management, Contextual Information, Software
Platform.
pages 1 to 16
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Journal of Decision Systems
1. Introduction
At the global level, average number of annual deaths caused by extreme events in
the period 1999-2003 was 59,000 people. For the same period, the average number
of affected people was 303 million per year (International Federation of Red Cross,
2004). About 97,490 people were killed in disasters globally from January to
October 2005 (World Health Organization, 2006). Furthermore, the corresponding
economical losses were estimated at $ 159 billion.
More than half the world’s population (3.4 billion people), live in areas where at
least one large scale hazard could significantly impact them. Billions of people in
more than 100 countries are periodically exposed to at least one event of earthquake,
tropical cyclone, flood or drought. As a result of disasters triggered by these natural
hazards, more than 184 deaths per day are recorded in different parts of the world
(World Health Organization, 2006).
These eXtreme Events (XEs) not only include natural hazards, but also
accidental and intentional disasters such as fires and terrorist attacks. However,
natural hazards are the most harmful. In 2005, four natural hazard types (earthquake,
tropical cyclone, flood and drought) were responsible for 94 percent of deaths due to
XEs (World Health Organization, 2006).
When these XEs affect urban areas their potential impact on society increases
due to the high population and civil infrastructure densities. In addition, XE
responding process becomes more complex and critical. Several researchers have
identified the need of reducing the vulnerability of urban areas to XEs
(Columbia/Wharton Roundtable, 2002; Godschalk, 2003; Mileti, 1999) and improve
the effectiveness of relief team actions in these situations (Mendonça, 2007;
National Commission on Terrorist Attacks, 2004; Scalem et al., 2004). The
significant human and economical costs emphasize this urgent need.
The relief team actions can be classified according to the three phases of disaster
relief processes: (a) the preparedness of first response plans for disasters, (b) the
response process to reduce the impact of XEs, and (c) the recovery of the affected
areas (Mileti, 1999; National Science and Technology Council, 2003). Mileti (1999)
defines these phases as follows: (a) “preparedness involves building an emergency
response and management capability before a disaster occurs to facilitate an
effective response when needed”; (b) “response refers to the actions taken
immediately before, during and after a disaster occurs to save lives, minimize
damage to property, and enhance the effectiveness of recovery”; and (c) “recovery
involves short-term activities to restore vital support systems and long-term
activities to return life to normal”.
Although the three phases involve group decision-making in differing contexts,
this paper focuses only on the response phase of urban relief efforts. Response is the
Supporting Group Decision Making When Extreme Events Affect Urban Areas
3
most complex and critical phase. Many pitfalls related to group decision-making and
coordination activities have been well documented (Comfort, 2001; Mileti, 1999;
Moore, 1999; National Research Council, 1999; National Commission on Terrorist
Attacks, 2004; Quarantelli, 1996; Stewart et al., 2002). These problems directly
influence the quality of decisions made and the effectiveness of the actions taken to
mitigate XEs.
Several research projects have been undertaken over the last five years in this
area. However, they do not consider the first responders working in the disaster area
as decision makers. The main reason is that due to the communication problems
inside the affected zone first responders become partially or totally isolated during
relief efforts (Manoj et al., 2007). Therefore first responders are mainly reduced to
improvisation (Mendonça, 2007; Mendonça et al., 2007; Webb, 2004). This
improvisation jeopardizes the collaboration among them and the effectiveness of
emergency response (Mendonça, 2007; National Commission on Terrorist Attacks,
2004). Another key issue that affects decision making and collaboration inside the
disaster area is the lack of standards that ensure the communication and information
interoperability among the first responders and managers belonging to different
organizations.
Authors stated that contextual information disseminated through digital wireless
communication could be used as a basis to improve group decision-making and
coordination processes during the response phase (Ochoa et al., 2006). This
contextual information can be understood as “whatever does not intervene explicitly
with the solution to a problem but constrains it” (Brézillon et al., 2004). These may
include: number of available first responders, current environmental condition, the
features of the disaster area and so on. During the response phase a large amount of
contextual information is generated which results from the development of the
event, including the relief actions carried out by the teams. The prompt capture and
distribution of this information can play an important role in the decisions made and
actions carried out by disaster relief teams during that phase (Canós et al., 2005;
Turoff, 2002; van de Walle et al., 2007). Currently, this contextual information is
poorly considered in group decision-making processes and most response plans.
However, “emergency managers have learned and stated that accurate and timely
information is as crucial as is rapid and coherent coordination among responding
organizations” (van de Walle et al., 2007).
This paper presents a proposal to include first responders as decision makers and
it describes a technological platform to record, represent and distribute contextual
information during disaster relief efforts. The platform intends to improve the
decision-making and coordination processes among first responders and the
command post. The platform is composed of a software, hardware and
communication system. It runs on mobile computing devices and it allows two
information representations. Visual representations support the decision-making
during disaster relief efforts, and the digital (internal) representation ensures the
information’s interoperability. The communication support enhances the
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Journal of Decision Systems
communication and coordination capabilities of participant organizations. The
platform also includes the support for information delivery in heterogeneous
technological scenarios.
The next section characterizes extreme events and explains the relevance these
characteristics have on the decision-making and coordination process. Section 3
describes the extreme collaboration scenario where the group decision-making
process should be supported as part of disaster relief efforts. Section 4 presents the
related work. Section 5 describes the technological platform that supports the group
decision making and coordination processes. Section 6 presents the conclusions and
the further work.
2. Characterizing Extreme Events
Prior research has proposed six properties of extreme events that are important
mainly for decision making and decision support. These properties are: rarity,
uncertainty, high and broad consequences, complexity, time pressure, and multiple
decision makers (Stewart et al., 2002). They are commented below.
XEs are rare. Their low frequency of occurrence restricts the opportunities for
preparation and learning from them. This rarity creates the need for diverse thinking,
solutions and skills. Furthermore, this rarity makes these events difficult to
understand, model and predict.
XEs are also uncertain because both their occurrence is unpredictable and their
evolution is highly dynamic. The challenges an XE presents and its consequences
are the joint product of that event, the affected community, and the organizations
involved in preparation and response. Every disaster is different; therefore disasters
present varying challenges to decision making, e.g., time availability and geographic
scale.
When XEs affect urban areas they usually have high and broad consequences,
leading to the need to manage interdependencies among a wide range of physical
and social systems (Godschalk, 2003; Rinaldi et al., 2001). The risks and the
disaster evolution should be evaluated quickly and accurately so that decisions can
be effective and timely. When these processes involve several people and
organizations, it may be appropriate to use tools to support interaction among these
people and organizations.
Event complexity arises in part due to the severe consequences of XEs
(Columbia/Wharton Roundtable, 2002). It may also arise as a result of
interdependencies among urban infrastructure systems (Godschalk, 2003; Rinaldi et
al., 2001). The complexity of the events requires the participation of experts in
several areas (e.g. civil engineers, transportation/electrical engineers and chemical
experts) to support decision making. The activities of these persons need to be
coordinated.
Supporting Group Decision Making When Extreme Events Affect Urban Areas
5
Time pressure forces a convergence of planning and execution (Moorman et al.,
1998), so that opportunities for analysis are few (Stewart et al., 2002). It is therefore
vital that accurate and timely information be gathered and delivered among the
organizations participating in the disaster relief effort. Information supporting
forecasting event impact and propagation is needed. This time pressure also creates
a need for convergent thinking in order to generate coordinated mitigation actions in
a timely fashion.
Finally, we have to consider that multiple decision makers will be involved in the
relief activities given the complexity and diversity of organizations participating.
They may compete or negotiate while responding to the event. It may therefore be
advisable to consider how decision support systems can assist the management of
shared resources and help people to converge soon to joint decisions. These
decisions and the actions produced by them need to be coordinated in order to carry
out an integral mitigation effort.
All these XE properties add requirements and challenges to the decision making
and coordination processes. However, there are several other issues that also add
requirements to the disaster relief process, for example the usability of the
technological solutions, the commitment level for inter-organizational collaboration,
and the features and role of the affected area. The proposal presented in this paper is
focused just on providing communication support, information interoperability and
delivery inside the disaster area as a way to reduce uncertainty and improvisation
space. The information availability and interaction capabilities among first
responders inside the affected area would help improve the decision making and
coordination process. The usability of this technological solution was carefully
considered during the design phase and it is discussed in sections 5.2 and 5.4.
3. Urban Disaster Relief Scenario
Urban areas can be seen as an interconnected system (public utilities, transportation
systems, communications, power systems, and homes and office buildings) where a
failure can potentially affect many people. When XEs affect urban areas, the key
issue is to control the cascading effects on the interconnected systems (Godschalk,
2003; Rinaldi et al., 2001; Stewart et al., 2002).
Typically, the response process involves a disaster relief mission that relies on
geographically distributed teams consisting of personnel in several roles, such as
field agents, team leaders, coordinators, decision makers and specialists/advisors.
The teams are composed of various individuals and organizations with diverse
expertise depending on the type of XE to mitigate, the features of the affected area
and the available resources. In major disasters, the first response teams are
composed of firefighters, police officers, medical personnel, government officers
and various specialists (Figure 1).
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Journal of Decision Systems
Typically, firefighters are mainly focused on fire fighting, evacuation of
civilians, search and rescue activities and evaluation of the affected area. Police
officers are mainly in charge of isolating the disaster area, supporting the evacuation
process and protecting the civil property. Medical personnel provide first-aid and
transportation of victims to health centers. The government officers are usually in
charge of making the macro-decisions and coordinating the activities of the
participating organizations. The role of the specialists is to support managers in the
decision making process. For example they analyze possible consequences of a
decision and provide advice to make the response process more effective/safe.
Usually, when XEs affect urban areas, civil engineers are involved to carry out
structural analysis of civil infrastructure (Aldunate et al., 2006; Federal Emergency
Management Agency, 2002).
Figure 1. Composition of an urban disaster relief mission
Several constraints exist in an urban relief mission: (1) one of the main issues is
the mission needs to be launched in a short period of time; (2) cultural, age and
discipline differences may exist since a disaster relief mission is performed by
participants from various organizations and it could involve more than one country;
(3) on-site information should be easily understandable and deliverable for all
organizations; and (4) the communication availability in the disaster area should be
Supporting Group Decision Making When Extreme Events Affect Urban Areas
7
provided in order to deliver information, communicate decisions and coordinate
activities. Currently, most communication support inside a disaster area is based on
2 or 3 radio channels; and information delivery is based on physical maps
disseminated among first responders (Aldunate et al., 2006). Considering that in
large urban disasters there may be hundreds or thousands of first responders, these
communication support and information delivery systems are clearly insufficient
(National Commission on Terrorist Attacks, 2004).
3.1. Decision Making Scenario
Decision makers have to consider that several activities such as searching for and
rescuing survivors, and repairing buildings temporarily to support rescue missions,
must be carried out in a short time period (Turoff, 2002). Typically the first 12-24
hours are the most critical. Therefore, the decisions triggering these tasks should
also be made as soon as possible. Searching and rescuing survivors should be
performed immediately after a disaster occurs.
For that reason, the availability and understandability of the contextual
information that supports the decision process should be high. Compiled information
with a graphical representation (e.g. teams’ location, task assignments and resource
allocation presented on a map) can be used to be easy to understand by persons
making decisions in different organizations. However, if such information needs to
be delivered among the participants, it will require the support of interoperable
information and communication systems. Since the type and amount of contextual
information that could be used to make decisions is diverse and comes from several
sources, the processes of capturing, representing and delivering such information
play a key role in getting accurate and on-time decisions.
Other aspects to consider are the decision dissemination and implementation.
Not all persons have to know every decision made; therefore decisions have to be
communicated to the right persons and delivered in the appropriate way (e.g.
visual/sound alarms or on-demand notifications). Reported experiences show that
organizations participating in relief efforts keep inter-organization interactions
among themselves to a minimum, and follow their own protocols and procedures
(National Commission on Terrorist Attacks, 2004; Stewart et al., 2002). This
jeopardizes the implementation of decisions. Government agencies are usually in
charge of the emergency management process, and their major challenge is to make
the macro-decisions and coordinate efforts from other organizations (Dykstra, 2003;
Jackson et al., 2002; National Research Council, 2002). However, people only obey
executives from their own organization (National Commission on Terrorist Attacks,
2004; Smith, 2003). Thus, the decisions made by government managers might not
have the expected effect.
The problems related to decision delivery and implementation are based on the
lack of an inter-organizational structure able to establish responsibilities and
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Journal of Decision Systems
decision making levels. Although proposals for this structure could be stated in
some national response plan (Federal Emergency Management Agency, 2002), in
practice it is the result of a self-organizing negotiation and even discussion process
(National Commission on Terrorist Attacks, 2004).
Regardless of the way this structure is generated - by a self-organizing process or
established by a national plan - two types of decision making processes are
conducted during the response process: organizational decision making and
improvisation. Organizational decision making is the process of making decisions
following the protocols, rules and conventions defined by an organization. This
process is usually done in a common command post or in the command post of each
organization. The implementation of these decisions is carried out mainly using the
organization’s own resources (e.g. equipment, human resources and materials).
These decisions have an effect on the relief effort and also on the activities of other
first response organizations. Since the rules and protocols of an organization are not
usually designed to be used in inter-organizational activities, a decision made by an
organization could imply negative effects on other ones (National Commission on
Terrorist Attacks, 2004; Stewart et al., 2002).
Improvisations used to be a consequence of the communication problems in the
disaster area. Members of first response teams usually communicate among
themselves using radio systems, because the fixed communication infrastructure is
frequently collapsed, unreliable or overloaded. They share two or three radio
channels to carry out the communication process, which are insufficient and
inappropriate for large relief efforts (Aldunate et al., 2006; National Commission on
Terrorist Attacks, 2004). The lack of control on the transmission channels and the
poor information transmission capabilities may leave several response teams
isolated or uninformed. In such situations, the only choice for such persons is
improvisation. Improvisation is typical of large relief efforts and it is mainly carried
out in the field (Mendonça, 2007). The decisions made during improvisation are
based on the experience of the decision maker or the group. Little or no information
supports such decisions and their implementation involves just local group
resources. Improvisations usually involve small scope activities; however, all these
activities happening in parallel have important consequences on the global results of
the relief effort.
Several researchers have identified the opportunity to use IT-based solutions to
deal with the challenges involved in the inter-organizational decision making and
activities coordination processes (National Research Council, 2002; National
Science and Technology Council, 2003; National Commission on Terrorist Attacks,
2004). Digital communications, robotics, distributed real-time systems, GIS,
collaborative systems, mobile computing and information interoperable formats are
some tools that could be used to face these challenges. These IT-based solutions will
have to deal with the first responders’ mobility, and they will be easy to transport,
deploy and use in a disaster area.
Supporting Group Decision Making When Extreme Events Affect Urban Areas
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3.2. Coordination Scenario
The coordination problems have several causes. Most of them are a consequence of
limitations in both the decision making processes and the technological support for
communication. It is clear that decisions made by an organization should be aligned
with their partners’ decisions as a way to reduce unexpected consequences and to
keep the relief activities coordinated. For this reason the decisions made need to be
appropriately communicated to first responders in the field and also to decision
makers of other organizations. It is also clear that not all persons have to know every
decision.
The information and tasks related to these decisions have to be also visible to
other organizations to keep the relief effort coordinated. In this scenario, the
technological solution supporting the communication process represents a key
element toward achieving effective coordination; particularly the capability of
transmitting and routing information. In case of disaster relief efforts, digital
wireless communication with routing capability would provide important advantages
to coordination and decision making processes (Aldunate et al., 2006; National
Commission on Terrorist Attacks, 2004). This communication support guarantees
that several types of information can be delivered to mobile workers, and the
communication channel will be available when a person needs to transmit or receive
information. However, it does not ensure that the information can be understood by
members of different organizations. This last feature can be ensured if the internal
and external information representation is standardized, thereby achieving
information interoperability among the organizations.
4. Related Work
Some countries have defined plans and responsibilities to adopt during
emergency situations in order to coordinate efforts among organizations and to
organize the decision-making processes. An example of them is the USA
government which defined the Federal Response Plan (FRP) (Federal Emergency
Management Agency, 2002), establishing the role of 27 federal departments and
agencies during disaster relief efforts. The FRP does not incorporate technological
solutions to support coordination activities among first responders and to service
disaster managers’ information and operational needs. However, FRP assigns
responsibilities to these agencies in order to coordinate the group decision making
process. The FRP estimates around 24 hours to deploy such a plan. However, the
survival rate drops to 50% after the first 24h in cases of collapse, and to under 5% in
cases of fire.
Other initiatives are the Multi-Sector Crisis Management Consortium (MultiSector Crisis Management Consortium, 2006) and the E-Team initiative (E-TEAM,
2006), which have developed a set of IT tools to support coordination among local
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disaster managers and remote experts in order to enhance the decision making
process. Typically, the local disaster managers use a mobile command post which
provides videoconferencing capabilities. Although this initiative has made important
contributions to the group decision support area, it does not allow representing and
sharing key information among first responders working in the affected area. There
are other projects, such as CAR (Federal Emergency Management Agency, 1997),
CATS (Swiatek, 1999), OpenGIS (Farley, 1999) and Sahana (Currion et al., 2007),
which have developed information systems to coordinate tasks among first response
organizations. Similar to those mentioned previously, these systems are not able to
represent and share contextual information among first responders deployed in the
affected area as they require stable communication and large computing power. In
the best case, first responders inside the disaster area are able to use PDAs supported
by Wi-Fi or GSM (cellular network) to send/receive information from the command
post or partners.
Multi-agent systems such as Robocup Rescue (Kitano et al., 2001), Combined
Systems (van Veelen et al., 2006), Aladdin (Jennings et al., 2006), EQ-Rescue
(Fiedrich, 2006), and FireGrid/I-Rescue (Tate, 2006) can also be used to support
decision making and coordination processes carried out by managers located in the
command post. These systems integrate legacy information systems, mobile
communication devices and sensor networks in order to provide advices and alerts to
disaster managers. These initiatives do not support the decision making and
coordination processes carried out by first responders working in the field.
On the other hand, Turoff, et al have proposed a very detailed, theoretical model
for the design of an emergency management information system (DERMIS), to
support emergency management at the regional or national emergency operating
center level (Turoff et al., 2006). However, no implementations are currently
available. To date the research on Computer Supported Cooperative Work (CSCW),
with few exceptions, has ignored the Incident Command Systems that support
emergency situations (Hannestad, 2005). The consequences of this can be seen in
disasters such as the Sumatra-Andaman earthquake of December 26, 2004 that
generated the Indian Ocean tsunami. There, software engineers in Sri Lanka
voluntarily worked day and night to build a basic emergency response system,
lacking any other alternative to coordinate the activities of first responders deployed
in the field. The system was up and running some weeks after the tsunami (van de
Walle et al., 2007).
Results about the use of these tools as support of real disaster relief processes are
not reported in the literature. Although we know the systems used in 9/11 terrorist
attacks and Katrina hurricane did not provide good support (National Commission
on Terrorist Attacks, 2004; van de Walle et al., 2007), we do not know which
systems were used in those extreme events. On the other hand, we do know that
Sahana system was used to support the recovery phase after the Indian Ocean
Tsunami (Currion et al., 2007). The results produced by the system are not reported,
Supporting Group Decision Making When Extreme Events Affect Urban Areas
11
however. For that reason it not easy to determine the effectiveness of these tools in
real disaster relief efforts.
Some other recent initiatives have developed prototype solutions that support the
decision making and coordination processes carried out by first responders working
in the field. Examples of these solutions are an ad-hoc distributed shared memory
system providing consistent and reliable communication among first responders
(Aldunate et al., 2006) and the map based tools to represent and share information
on response process evolution (Guerrero et al., 2006). These works are part of the
authors’ previous research activities. Although these prototypes have been shown to
be useful for training of firefighters, they are not able to capture, represent and
deliver contextual information in order to improve the first response decision
making and coordination activities in the field. After a long search through research
related to this, no similar initiative was found. Therefore, this proposal could
represent a basis for future research and development in the stated knowledge
domain.
5. Platform for Context Management
In order to deal with the challenges involved in the inter-organizational decision
making and coordination processes, this section presents a software platform that
involves three main components for capturing, representing and delivering
contextual information (Figure 2). The capture of contextual information is the
module in charge of gathering relevant information to support the decision making
process. The information gathering is carried out during preparedness, response and
recovery stages. Typically, during preparedness activities information such as
location of cranes, trucks, experts, health centers, police/fire departments, and
government agencies are recorded. This information also includes maps and
evacuation routes, plans and areas with high population density. This contextual
information is part of the previous formal knowledge (Barbosa et al., 2005) and it
usually is vital for effective and fast responses.
The contextual information to be captured and recorded during the response
process is mainly related to the XE, decisions made and relief effort evolution. Such
context information is known as current contextual knowledge (Barbosa et al.,
2005).
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Figure 2. Platform main functionality
The second component of the platform is in charge of representing the
contextual information in a way that such information can be easily shared,
understood, and automatically processed by any organization participating in the
relief actions. The context information stored in the platform has two types of
representations (Figure 2): one internal and several external ones. The internal
representation uses XML (eXtensible Markup Language) (World Wide Web
Consortium, 2006) to represent the information and XML Schema (van der Vlist,
2002) to add semantics to such information. It ensures that when this information is
shared, any organization will be able to understand it and process it.
The external representations are usually visual. In the case of this platform it is
composed of a set of layers that deploy context information on a map. These layers
can be compounded in order to show richer information to make decisions.
The third component of the platform is in charge of delivering the shared
information to members of a work session. It involves communication support based
on a Mobile Ad-hoc NETwork (MANET) (Tschudin et al., 2003). This functionality
was reused from PASIR (Neyem et al., 2005), which implements networking
capabilities, XML data synchronization, session management and information
sharing using multicast and broadcast. These services allow people to work as
autonomous units that are part of a relief community. It also allows us to implement
user roles and deliver information to users considering their grants. This
functionality represents the basis to coordinate the inter-organization actions.
The platform was implemented through a prototype that currently runs on
notebooks, tabletPCs and PDAs (Personal Digital Assistants). The prototype has
been preliminary evaluated by experts of the 6th and 8th firefighters company of
Supporting Group Decision Making When Extreme Events Affect Urban Areas
13
Santiago (Chile) and it got good results. Section 5.5 presents more details about this
evaluation process. Next sections describe the process of capturing, representing and
delivering the context information when it is supported by the platform.
5.1. Capturing Context Information
Context information is required to make accurate decisions. These decisions have to
be made on short notice; therefore the gathering process has to be previously done.
Two main questions arise from this need: what context information has to be stored?
and how to capture such information? Based on talks with first response managers,
authors determined that context information related to the mitigation effort, the
extreme event and the group decision support need to be captured and represented in
order to improve the decision-making process (Figure 3) (Ochoa et al., 2006).
Since the decisions have to be fast, the stable contextual information (e.g. maps
or location of health centers) needs to have been previously added to the platform;
for example during preparedness. The highly dynamic context information has to be
captured and reported on the fly. Specialized autonomous units that automatically
collect and inform the context information to a platform agent are recommended for
this task. The information can be weather conditions, presence of chemical and
biological agents, or level of dust/smoke in the air.
5.1.1. Relevant Context Types
Typically, the contexts related to the mitigation effort, the extreme event and the
group decision support system are composed of a Previous Formal Knowledge
component and a Current Context Knowledge component (2). The previous formal
knowledge consists of any information relevant to the decision-making process
known before the occurrence of an XE; e.g., information from emergency response
plans, city maps, experts’ location and available resources. Usually, this knowledge
is explicit and it does not change during the course of the emergency. However, it is
not always available or up-to-date.
On the other hand, the current context knowledge is composed of the information
relevant to the decision-making process, which is known just after the occurrence of
an XE. This information can be related to the XE itself or the response process.
Examples of this contextual information are the type and magnitude of the XE, the
allocated resources in the disaster area, location of medical personnel and entry/exit
routes to/from the affected area. This information should be gathered, processed and
stored in order to be considered as part of the current contextual knowledge. This
contextual information is highly dynamic and volatile due to the continuous
evolution of the disaster scenario. Next, these key contextual concepts are
introduced.
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Journal of Decision Systems
Extreme Events. XEs represent the type of hazardous event which originated the
emergency and the physical scenario. These include natural, accidental and
intentional disasters. The previous formal knowledge in this case includes: maps,
evacuation roads, risks areas and typical consequences and behaviors of XEs. On the
other hand, the current contextual knowledge of an XE includes factors that could
affect the behavior of the XE (e.g. meteorological conditions) and XE features such
as the type and magnitude, and the identification of the affected area.
Figure 3. Context of the key concepts and relationships among them
Mitigation Effort. The mitigation effort represents the activities carried out to
reduce the impact of the XE on Society. The previous formal knowledge related to
this concept includes information such as: available resources (materials providers,
construction companies, first response and humanitarian organizations,
transportation companies, specialist centers, disaster management agencies, health
centers, police departments and firefighter departments) and their probable location,
and emergency plans and policies. On the other hand, the current contextual
knowledge is composed of information about the allocated and available resources,
the list of tasks (scheduled and triggered) and their level of completion, the current
(and expected) meteorological conditions, and the working protocols for first
responders.
Supporting Group Decision Making When Extreme Events Affect Urban Areas
15
Group Decision Support (GDS). It considers the contextual information to support
decision making not only inter-organizations but also inside an organization as well
as improvisations. In order to support the correct actions and keep the relief effort
coordinated when an XE happens, the decision makers can benefit from the use of
group decision support which includes relevant information. The previous formal
knowledge of this concept includes information such as: restrictions on the assigned
resources and previous personal knowledge (this knowledge is embedded in each
emergency responder’s mind, and it has been acquired during past experiences,
training sessions and simulations of real-life settings (Barbosa et al., 2005)). On the
other hand, the current contextual knowledge incorporates decisions that are
implemented by managers, the tasks triggered by these decisions, the government
priorities, the isolated perimeter, the expert recommendations and information about
victims.
There is other contextual information relevant to support decision making and
coordination activities, however it has been considered as part of the further work.
For example, the primary use of the affected area (e.g. tourism, business, residence)
would indicate the number and type of persons that could be there and if the people
are familiar or not with their surroundings. Thus, would be possible to establish the
probability of auto-evacuation of such people.
5.1.2. Relationships Among Contexts
Changes in the context of a key concept eventually influence the context of other
key concepts. These influences are discussed below.
Mitigation Effort – Extreme Event. The context of the mitigation effort will depend
on the type and magnitude of the XE. For example, the number of firefighters
participating in a relief effort will be different in case of a building collapse or a fire.
In addition, decisions made as part of the relief effort have an impact on the XE
mitigation. For example, assigning more teams to fight a fire could help reduce the
time for mitigating it. This strong relationship between the context of these two
components helps: (a) to understand the dimensions of actions and consequences of
a decision, and (b) to estimate the magnitude of a mitigation effort required to
handle an XE. Although the context of these concepts is highly dynamic, the
relationship between these two contexts is stable. It means a decision maker is able
to understand the consequences related to changes in the context of the mitigation
effort or the XE.
Mitigation Effort – Group Decision Support. Typically, the context of the mitigation
effort affects the type and quality of the decisions made by the managers. For
example, accurate and ready information about the possible location of victims
could help increase the number of survivors after a building collapse. The available
resources and the urgency to trigger a task are some of the restrictions that the
mitigation effort context imposes over the group decision support. Furthermore, the
16
Journal of Decision Systems
hierarchical structure of the mitigation effort context helps locate the decisions made
and analyze their impact. Because the context of the group decision support is
composed of much knowledge from the mitigation effort context, both contexts are
strongly related and this relationship is stable.
Group Decision Support – Extreme Event. Similar to the previous case, the context
of the group decision support is also composed of much knowledge from the XE
context; thus, both contexts are strongly related. For example, if a fire is collapsing a
building, then decision makers have to evacuate the personnel they assigned for
searching and rescuing victims in the building. However, these relationships are
complex. It means disaster managers will not be able to predict the consequences a
change in one of these contexts will have on the other context.
Figure 4. Decision-making during preparedness, response and recovery
The known relationships among these contexts will be part of the previous
formal knowledge, and the unknown relationships will be part of the current
contextual knowledge. Considering these two types of contexts it is possible to see a
transverse dimension of contexts. This transverse dimension will improve the
decision making process during the three phases of a disaster relief effort:
preparedness, response and recovery (Figure 4).
The previous formal knowledge will help managers to support the decisionmaking process during the preparedness phase. During the response phase disaster
relief managers will use both types of contextual information to support decisionmaking. Finally, the current contextual knowledge from the response phase and the
Supporting Group Decision Making When Extreme Events Affect Urban Areas
17
previous formal knowledge are the only basis to support the decision-making
process in the recovery phase. Thus, every phase can be supported using this
contextual information.
5.2. Representing and Using Context Information
Context information to improve group decision support when disasters occur is a
complex description of knowledge related to three key concepts that have been
presented: a) the mitigation effort, b) the extreme event and c) the group decision
support. In these key concepts, the previous formal knowledge and the current
contextual knowledge have to be represented, accessed and processed in order to
promote coordination among organizations and to support the decision-making
process. Therefore, it is convenient to create a collaboration space where several
groups of people participate, even those belonging to several organizations. Their
contributions incorporate various rich perspectives, but they can also bring
difficulties like a lack of common opinions and various ways of expressing
knowledge.
The proposed platform standardizes the representation of the shared knowledge
to avoid these problems and ensures the information interoperability and
understandability. This knowledge is part of the context and it supports the work of
different roles participating in the disaster relief effort, such as: supporting agents,
managers, monitors, first response teams working in the field and first response
teams in stand-by (Figure 5).
Supporting agents are people in charge of making the previous formal
knowledge available. This knowledge concerns the XE, the group decision support
and the mitigation effort. Moreover, they also update the current contextual
knowledge related to these concepts. Information on availability of resources which changes depending on the gathering and allocation processes - is an example
of updated knowledge. Typically, the supporting agents do not make decisions.
However, some of them (i.e. remote experts) can provide advice to managers in
order to improve the quality of the decisions made.
Managers use the previous formal knowledge and the current contextual
knowledge to make decisions. These decisions update the current contextual
knowledge and also trigger tasks that are assigned and communicated to first
response teams deployed in the work field.
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Journal of Decision Systems
Figure 5. Using contextual information during the response process
On the other hand, monitors (government personnel or hospital managers) and
first response teams in stand-by are able to follow the disaster relief evolution and to
internalize the shared contextual information. This will improve the quality of the
local decisions made by these first responders when they are deployed in the field,
and it will reduce their adaptation period. Besides, it will also help reduce the loss of
personal contextual information due to the exchange of first response teams.
Our working hypothesis is that the appropriate representation of contextual
information is closely related to providing the information needed to support
coordination activities and decision making in the event response effort. However,
in order to have the contextual information stored, it is necessary to have a system to
gather, represent and communicate this information from the place it is perceived to
the place where it can be used.
Software systems are representational, so concern with context naturally leads to
concern about how context can be encoded and represented. In particular, the
context consists of a set of features of the environment surrounding generic
activities. These features can be encoded and made available to a software system
along side an encoding of the activity itself (Borges et al., 2004; Dourish, 2004).
This process is inherent in the notion that our systems will “capture”, “model”, and
“represent” context. Although the capture and model of context are relevant issues,
the most critical one in this scenario is the representation. This is because several
Supporting Group Decision Making When Extreme Events Affect Urban Areas
19
people from diverse emergency organizations should understand, share and update
this knowledge. This platform has an internal and several external representations
for the contextual information.
5.2.1. Internal Representation
The strategy of internal representation is responsible for the information
interoperability among the organizations participating in the relief efforts. This
strategy establishes two key features of the information: data format and meaning.
The data format is supported by XML (eXtensible Markup Language) (World Wide
Web Consortium, 2006), chosen because it is a standard that provides flexibility and
it is easy to use. The information meaning is represented through XML Schema (van
der Vlist, 2002), which is also a widely accepted standard.
Figure 6. Process of digital documents generation
The schemas allow organizations to compose information in order to form bigger
or more complex pieces of knowledge, which could be used to support coordination
activities or decision making. For example, basic information about a fire in a
20
Journal of Decision Systems
building (e.g. structure and type of building, fire intensity, coverage area, weather
conditions and firefighting resource allocated) could be composed to determine the
threshold of safety for firefighters working in the emergency area. Other examples
are the online reports that integrate contextual information from several sources.
These reports are designed to support decision making activities. They are
implemented as digital documents that can be shared among the organizations
without risks of information misunderstanding. Figure 6 shows the process to get
any kind of digital document.
Digital document generation starts with the request from a user. The event is
captured and processed by the digital document generator, which is in charge of
producing the first version of a digital document (e.g. report of contextual
information related to the XE, the mitigation effort or the group decisions). This
module invokes the metadata/schema retriever in order to get the right schema and
metadata that guide the process of composing information to create the digital
document. Then, the digital documents generator recovers the basic information (in
XML format) from the dataspace and produces a preliminary digital document,
which adheres to the structure specified by the XML schemas. The generated
document is re-checked by the digital document analyzer in order to guarantee that
its information adheres to the predefined standards of formats and meanings. Digital
documents that overcome this test can be considered interoperable; therefore they
are stored into the shared dataspace and several organizations (and mainly decision
makers) can access them and process them depending on their specific needs.
5.2.2. External Representation
The external representation is the one that can be accessed by the final user. A
typical question during the design of a groupware application for this scenario is:
which is the appropriate way to represent the context information in order to
improve group decision support? Provided the decisions have to be made quickly,
the information representation needs to be rich and easy to understand, even for
persons that belong to different organizations. Typically, visual representations
provide the best support. The described platform presents the context information
based on several visual layers (Figure 7).
The lower layer represents a general view of the affected area. Based on that,
several upper layers with diverse information can be displayed. Each upper layer is a
map that represents the information needed by a specific organization or group, such
as police, firefighters and civil engineers. There decision makers can make marks on
the maps in order to record their decisions. Then, all authorized persons will be able
to see the marks made by the managers. This information can also be transmitted to
the first responders working in the field and also to those awaiting an assignment.
Thus, they will have sound information to make local decisions or to improvise.
Supporting Group Decision Making When Extreme Events Affect Urban Areas
21
Figure 7. Visual representation of context in the software system
Some typical marks the managers make on the maps are the location of available
and allocated resources, the requested resources, the safe and dangerous areas, the
entry and exit routes, health personnel location and pending and current activities.
All this knowledge is useful not only to make decisions but also to coordinate the
inter-organization efforts. However, it will be possible only if there is a strong
support for communication and information delivery in ad-hoc interactions
scenarios.
(a)
(b)
(c)
Figure 8. Groupware system to support disaster relief efforts
Figure 8 presents a software prototype developed on the proposed platform. This
system has a lightweight version and a full functionality version. The lightweight
version is used by first responders deployed in the field. Typically 2 or 3 first
responders in each group use the system to support the group’s local decisions,
improvisations, receive their assignments and update shared information. They
move with the group, but they are not located in the hot spot. Their main function is
to support the partner in the work field, for example in search and rescue activities.
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Journal of Decision Systems
The lightweight module runs on a PDA fastened to the first responder’s arm (see
figure 8a and 8b). The PDA uses a Compact Flash Memory card in which the maps
of Santiago (Chile) were previously loaded. Such maps include 4 levels of zoom and
require 52MB of storage. Thus, the only information that is communicated among
mobile computing devices in the field is the XML files that implement each
information layer. This reduces traffic on the Wi-Fi network and allows first
responders to work autonomously. Due to this working strategy, PDA’s hardware
limitations do not represent a big issue. Additionally, since the system supports
zoom and scroll in any screen direction, the small size of the PDA screen is not an
impediment to viewing the graphical information.
The full functionality version of the system provides support for all the external
views previously mentioned. It runs on desktop PCs and notebooks (figure 8c),
usually located in the command post. Additionally, this version of the system can
manage groups, deliver messages/information to user roles or group members. It can
also manage orders, task assignments and resource allocation. The system
implements a shared repository that can be accessed by other managers using the
same system. The repository stores maps, regulations, response plans and contact
information of government agencies, experts, construction companies and disaster
relief organizations. Finally, the system allows managers to carry out
videoconferences with remote experts. The full functionality version of the system
requires intensive use of computing resources; therefore it should run at least on a
notebook or desktop PC. Section 5.4 presents the details of the hardware
recommended to run the system.
5.3. Delivering Shared Information
The work scenario in urban disaster relief effort is unstable, hazardous and
highly dynamic. The fixed communication infrastructure is frequently collapsed,
unreliable or overloaded after an XE. The radio systems currently used by first
responders are not able to transmit digital information and do not provide routing
capabilities. On the other hand, the deployment of the communication systems
should be fast and easy, because of the urgency to maintain control of the mitigation
effort.
The use of wireless communication is essential, as mobile workers (e.g. police,
firefighters and medical personnel) deployed in the field must be able to inform and
be informed of new developments and to receive assignments and other relevant
information (e.g. damaged buildings, maps, probable people locations and
vulnerable points). However, this type of communication brings several
requirements to any solution proposed to deliver information in disaster relief
scenarios. Next section describes the most important ones.
Supporting Group Decision Making When Extreme Events Affect Urban Areas
23
5.3.1. Requirement for Information Delivery
Wireless communication can be carried out with or without infrastructure. Both
types of services are needed and fortunately they are compatible. Typically, the
wireless communication without supporting infrastructure is more restrictive;
therefore any solution proposed to deliver information in such scenario should be
designed for this type of network, well known as Mobile Ad-hoc NETworks
(MANETs) (Tschudin et al., 2003). The most relevant requirements imposed by
these networks are the following ones:
 No centralized mechanisms: Since ad-hoc networks do not have any underlying
infrastructure, centralized routing algorithms are not applicable. Centralized
components become critical failure points and then there are the typical problems
with scalability and fault tolerance for processing all the information.
 High autonomy: Mobile software applications should function as autonomous
solutions since the communication service is unstable. Depending on the type of
communication the mobile workers have, they can work synchronously or
asynchronously. Thus, the mechanisms for these two ways of information delivery
should be provided.
 Interoperability: Provided mobile workers belonging to different organizations
may need to engage in casual or opportunistic interactions, the data and services
format should be standardized in order to ensure the interoperability. Thus,
receivers will be able to understand the information and services they get.
 Roles and session support: The roles of the persons participating in the mitigation
effort are diverse. These roles have to be considered when delivering decisions
and to allow the access and update of shared information. Similarly, these people
could establish private work sessions in which the message delivery and shared
information can be accessed just by the session members.
The communication support currently available is based on Wi-Fi with routing
capabilities. Provided the graphical information (maps) is previously loaded in each
mobile device, the information transmitted through the network is mainly XML files
representing orders, notifications and information layers. If a PDA or notebook does
not have the information previously loaded, it can request it via wireless to the
command post. Although it is also possible to recover this information from any
mobile device deployed in the disaster area, we recommend getting it from the
command post or from a computing device that is not in use by first responders.
Thus, we avoid high data transfer rates on the MANET. The effective data transfer
rate among two devices physically close (i.e. reachable in one hop) is presently
about 50-100 kbps.
5.3.2. Information Delivery Strategy
The platform considers each computing device as an autonomous unit. For that
reason it implements fully distributed session and user management. The shared
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Journal of Decision Systems
dataspace is also distributed, with an ad-hoc percentage of information replication.
In addition, the platform only provides support for asynchronous communication
because of the wireless communication instability. The strategies for information
delivery implemented in the platform consider these features and four basic
asynchronous mechanisms for information delivery:
 Delivery to all. Every user reachable through the MANET receives the
message.
 Delivery by session. Just the members of a session receive the message. This
message delivery strategy can consider more than one session.
 Delivery by roles. Users playing a specific role are the only ones who receive
the messages. This message delivery strategy can consider more than one
role.
 Delivery to a user. This is a point to point communication. It could be a
pushed or a pulled messages interchange. It is a pulled one when the user
requests information, for example to the shared dataspace. It is pushed when
the user sends information to others, for example a notification alarm.
Most of these strategies use a multicast protocol. Any node acts alternatively as
client and server depending on whether it is sending or receiving information. The
messages that are not delivered are stored in a pool, which has a specific policy of
retries.
5.4. Technological Support
The software was developed in C# by using .Net Framework for the full
functionality version of the system, and .Net Compact Framework for the
lightweight version. The maps were recovered from a MS MapPoint Server. The
heavyweight version was tested in notebooks with a 2,3 Ghz Pentium VI CPU and 1
GB of RAM. This version is mainly used by managers located in the command post.
The lightweight version was tested using PDAs with at least a 400 Mhz CPU and
64MB of memory (additional to the compact Flash memory). Two PDA screen sizes
were used: 640x480 and 320x240. In the second case, the size of the map tiles must
be adjusted to allow a correct visual representation. The main advantages of the
PDAs are their portability and speed of deployment. Their main limitation is battery
life (about 2 hours of continuous use). Currently, all computing devices considered
in the solution are off-the-shelf systems that were not designed to be used in disaster
scenarios. Therefore they can be affected by dust, heat, water or impact. In a fully
operational version of the solution, rugged computing devices should be used in
order to deal with the hardware durability problem.
The network support is based on IEEE 802.11b with routing capabilities. No
access points were used. The network is composed only of the mobile devices
deployed in the disaster area. They act as bridges to allow communication among
Supporting Group Decision Making When Extreme Events Affect Urban Areas
25
devices that are not reachable in one hop. Each node in the network keeps track of
the MANET topology over time.
5.5. Preliminary Results
Both versions of the system were preliminarily evaluated by experts of the 6 th and 8th
firefighters companies of Santiago (Chile) during March 2007. These experts are the
official urban search and rescue trainers for Chilean firefighters, and police/military
officers. The experts evaluated the system functionality, performance and usability.
The first important conclusion indicates the system is ready to be used at least in
small urban incidents (fires, chemical spills, small collapses). The system
functionality was considered useful to support urban search and rescue activities.
The main comments to consider are two: (a) the system does not use international
icons to represent standard information (e.g. safe areas or evacuation routes) and the
visual information is not shown according to the sectors defined by the National
Disaster Response Plan.
The usability was evaluated simulating the actions that firefighters have to do
during two small urban emergency situations: a fire and a car accident. The features
of these emergencies were recovered from the real emergency situation that was
occurring at the time. The usability evaluation was conducted in the Alarms Center
of Santiago. During the next weeks, the prototype will be used by these firefighters
in real small urban incidents.
Finally, system performance was good in the case of the heavyweight version.
Three notebooks were used in this test. Five PDAs were used in the test of the
lightweight version, and although the performance of such system was acceptable, it
needs to be improved. The main performance problem was produced by the PDA
transmission capability and the MANET bandwidth requirement which generated a
bottleneck. Currently we are designing incremental tests with notebooks and PDAs
in order to analyze network load and the evolution of system performance.
6. Conclusions and Further Work
Given their size, complexity and rarity, XEs challenge the relief organization
capabilities for responding, particularly when they affect urban areas. The
coordination among first response organizations, and the decision making process,
have been identified as two key factors that produce a major impact on the results of
the response process. The use of contextual information could be used to assist in
meeting these challenges.
All disaster relief phases demand knowledge which is embedded in procedures
and in the minds of people who handle them. Specifically during the response phase,
a high amount of contextual information is generated. This information covers the
development of the event, including the relief actions carried out by the teams. The
prompt capture and distribution of this information can play an important role in the
26
Journal of Decision Systems
decisions made by the managers and the actions carried out by disaster relief teams.
Most response plans, however, are not designed to make proper use of this type of
contextual information.
Advances in IT provide opportunities to deal with these two key issues.
Particularly, digital wireless communication and distributed collaborative systems
have been considered as interesting tools to provide communication and information
support.
Considering this perspective the paper presented a software platform able to
record, represent and manage contextual information related to the mitigation effort,
group decision support and extreme event, and the relationships among these
contexts. The contextual information represented in the platform helps improve
group decision support and activity coordination during disaster relief efforts. Visual
representations of this information support group decision-making during disaster
relief efforts, the digital (internal) representation of such information ensures
interoperability and the technological support enhances the communication and
coordination capabilities of participating organizations. Decision-making and
coordination activities carried out in scenarios similar to this one, such as police and
military operations, and security operatives during massive social events, can take
advantage of this platform.
The use of the platform should help designers of disaster response support
systems to represent and store contextual information in their knowledge base and to
selectively disseminate it among the several emergency response teams in order to
improve the result of their relief actions. We have assumed the contextual
information can be disseminated among the people participating in the disaster relief
effort. However, many challenges need to be addressed in order to make possible
effective contextual information dissemination, such as multicasting support, data
distribution based on roles, and support for synchronous/asynchronous work
(Aldunate et al., 2006).
Future work includes, in the short term, the testing of the platform in simulated
scenarios, in order to determine how scalable the system is. Additionally, prototypes
will be used by firefighters to support small urban emergency events. This will allow
us to evaluate system usability and the real advantages and disadvantages it
provides. Based on that result, the tool will be adjusted and tested through an
evolutionary process. Finally, the context information domain included in the tool
will be extended in order to improve the support for decision making and
coordination activities.
7. Acknowledgements
This work was partially supported by grant No. UCH 0109 from MECESUP (Chile)
and Fondecyt No. 11060467 and 1040952 (Chile). Marcos R. S. Borges was
partially supported by a grant from CNPq (Brazil) No. 305900/2005-6.
Supporting Group Decision Making When Extreme Events Affect Urban Areas
27
8. References
Aldunate R., Ochoa S., Pena-Mora F., Nussbaum M., “Robust Mobile Ad-hoc Space for
Collaboration to Support Disaster Relief Efforts Involving Critical Physical
Infrastructure”, ASCE Journal of Computing in Civil Engineering, vol. 20 no. 1, 2006, p.
13-27.
Barbosa V.D., Borges M.R.S, Gomes J.O., Canós J.H., “Knowledge Management Support for
Collaborative Emergency Response”, in Proceeding of the 9th International Conference on
Computer Supported Cooperative Work in Design (CSCWD 2005), Coventry, UK, March
24-26 2005, p. 1188-1193.
Borges M.R.S., Brézillon P., Pino J.A., Pomerol J., “Bringing Context to CSCW”, in
Proceeding of the 8th International Conference on Computer Supported Cooperative Work
in Design (CSCWD 2004), Xiamen, P.R. China, May 26-28 2004, p. 161-166.
Brézillon P., Borges M.R.S., Pino J.A., Pomerol, J., “Context-Awareness in Group Work:
Three Case Studies”, in Proceedings of the IFIP WG8.3 International Conference on
Decision Support Systems (DSS 2004): Decision support in an uncertain world, Prato,
Italy, July 1-3 2004, p. 115-124.
Canós J.H., Borges M.R.S., Alonso G., “An IT View of Emergency Management”, IEEE
Computer, vol. 38 no. 12, 2005, p. 27.
Comfort L., Coordination in Complex Systems: Increasing Efficiency in Disaster Mitigation
and Response, Annual Meeting of American Political Science Association, San Francisco,
USA, September 2001.
Columbia/Wharton Roundtable, Risk Management Strategies in an Uncertain World, IBM
Palisades Executive Conference Center, Palisades, New York, April 12-13, 2002.
Currion P., de Silva C., Van de Walle B., “Open source software for disaster management”,
Communications of the ACM, vol. 50 no. 3, 2007, p. 61-65.
Dourish P., “What We Talk About When We Talk About Context”, Journal on Personal and
Ubiquitous Computing, vol. 8 no. 1, 2004, p. 19-30.
Dykstra E., Toward an International System Model in Emergency Management, Public Entity
Risk Institute, 2003.
E-TEAM,
Digital
Resources,
Retrieved
http://www.eteam.com/resources/index.html
May
13,
2006,
from
Farley J., “Building Enterprise Government Using OpenGIS Technology”, in Proceeding of
the Geospatial Information and Technology Association, Open GIS Seminar, Charlotte,
North Carolina, April 25-28 1999.
Federal Emergency Management Agency, State Capability Assessment for Readiness
Process, Report to the US Senate Committee on Appropriations, 1997.
Federal Emergency Management Agency, Federal Response Plan (FRP), 9230.1-PL, 2002.
Fiedrich F., “An HLA-based multiagent system for optimized resource allocation after strong
earthquakes”, in Proceedings of the 38th Winter Simulation Conference (WSC 2006),
Monterey, CA, USA, December 03-06 2006, p. 486-492.
28
Journal of Decision Systems
Global Disaster Information Network, Retrieved May 22, 2006, from http://www.gdin.org/
Godschalk D., “Urban Hazard Mitigation: Creating Resilient Cities”, ASCE Journal on
Natural Hazards Review, vol. 4 no. 3, 2003, p. 136-143.
Guerrero L., Ochoa S., Pino J.A., Collazos C., “Selecting Devices to Support Mobile
Collaboration”, Journal on Group Decision and Negotiation, vol. 15 no. 3, 2006, p. 243271.
Hannestad S., “Incident Command System: A Developing National Standard of Incident
Management in the U.S.”, in Proceedings of the 2nd International Conference on
Information Systems for Crisis Response and Management (ISCRAM 2005), Brussels,
Belgium, April 18-20 2005, p. 19-28.
International Federation of Red Cross and Red Crescent Societies, World Disasters Report
2004: Focus on Community Resilience, 2004.
Jackson B., Peterson D., Bartis J., LaTourrette T., Brahmakulam I., Houser A., Sollinger J.,
Protecting Emergency Responders: Lessons Learned from Terrorist Attacks, RAND
Science and Technology Policy Institute Report, March 2002.
Jennings N.R., Ramchurn S.D., Dutta P., Rogers A., Vetsikas I., “The ALADDIN project:
Agent technology to the rescue”, in Proceedings of the 1st International Workshop on
Agent Technology for Disaster Management (ATDM 2006), Hokadoke, Japan, May 8
2006, p. 157-158.
Kitano H., Tadokoro S., “RoboCup rescue: A grand challenge for multi-agent and intelligent
systems”, AI Magazine, vol. 22 no. 1, 2001, p. 39-52.
Manoj B.S., Baker A., “Communication challenges in emergency response”, Communications
of the ACM, vol. 50 no. 3, 2007, p. 51-53.
Mendonça D., “Decision support for improvisation in response to extreme events: Learning
from the response to the 2001 World Trade Center attack”, Decision Support Systems,
vol. 43 no. 3, 2007, p. 952-967.
Mendonça D, Jefferson T., Harrald J., “Collaborative adhocracies and mix-and-match
technologies in emergency management”, Communications of the ACM, vol. 50 no. 3,
2007, p. 44-49.
Mileti D., Disasters by Design: A Reassessment of Natural Hazards in United States, Joseph
Henry Press, Washington DC, 1999.
Moore G., Crossing the Chasm: Marketing and Selling High-Tech Products to Mainstream
Customers, Harper Collins Publishers, New York NY, 1999.
Moorman C., Miner A., “Organizational Improvisation and Organizational Memory”,
Academy of Management Review, vol. 23 no. 4, 1998, p. 698-723.
Multi-Sector Crisis Management Consortium, Multi-Sector Crisis Management Consortium
Programs, Retrieved July 6, 2006, from http://www.mscmc.org/index.html
National Research Council, Reducing Disaster Losses Through Better Information, National
Academic Press, USA, 1999.
Supporting Group Decision Making When Extreme Events Affect Urban Areas
29
National Research Council, Making the nation safer: The role of science and technology in
countering terrorism, National Academies Press, USA, 2002.
National Science and Technology Council, Reducing Disaster Vulnerability Through Science
and Technology Report, National Science and Technology Council, Committee on the
Environment and Natural Resources, 2003.
National Commission on Terrorist Attacks Upon the United States, The 9/11 Commission
Report, 2004.
Neyem A., Ochoa S.F., Guerrero L.A., Pino J.A., “Sharing Information Resources in Mobile
Ad-hoc Networks”, in Proceeding of the 11th International Workshop on Groupware:
Design, Implementation, and Use (CRIWG 2005), Lecture Notes in Computer Science,
vol. 3706, Porto do Galinhas, Brazil, September 25-29 2005, p. 351-358.
Ochoa S.F., Neyem A., Pino J.A., Borges M.R.S., “Using Context to Support
Group Decision Making in Disasters Affecting Urban Areas”, in Proceeding of IFIP
TC8/WG 8 International Conference on Creativity and Innovation in Decision Making
and Decision Support (CIDMDS 2006), London, England, June 29 - July 1 2006, p. 546561.
Quarantelli E., Major Criteria for Judging Disaster Planning and Managing and their
Applicability in Developing Societies, Background paper for the International Seminar on
the Quality of Life and Environmental Risk, R.J. Brazil, October, 1996.
Rinaldi S., Peerenboom J., Kelly T., “Complexities in Identifying, Understanding, and
Analyzing Critical Infrastructure Interdependencies”, IEEE Control Systems Magazine,
vol. 22 no. 6, 2001, p. 11-25.
Scalem M., Bandyopadhyay S., Sircar A., “An approach towards a decentralized Disaster
Management Information Network”, in Proceeding of the 2nd Asian Applied Computing
Conference (AACC 2004), Lecture Notes in Computer Science, vol. 3285, Kathmandu,
Nepal, October 29-31 2004, p. 287-295.
Smith S., Inter-Agency Collaboration and Consequence Management: An All-Hazard
Approach to Emergency Incident Response, Public Entity Risk Institute, 2003.
Stewart T., Bostrom A., Extreme Event Decision Making Workshop Report, Decision Risk
and Management Science Program NSF, June, 2002.
Swiatek J., Crisis Prediction Disaster Management, SAIC Science and Technology Trends II,
June, 1999.
Tate A., “The helpful environment: Geographically dispersed intelligent agents that
collaborate”, IEEE Intelligent Systems, vol. 21 no. 3, 2006, p. 57-61.
Tschudin C., Lundgren H., Nordström E., “Embedding MANETs in the Real World”, in
Proceedings of the IFIP-TC6 8th International Conference on Personal Wireless
Communications (PWC 2003), Lecture Notes in Computer Science, vol. 2775, Venice,
Italy, September 23-25 2003, p. 578-589.
Turoff M., “Past and Future Emergency Response Information Systems”, Communications of
the ACM, vol. 45 no. 4, 2002, p. 29-32.
Turoff M., Chumer M., Van de Walle B., Yao X., “The Design of a Dynamic Emergency
30
Journal of Decision Systems
Response Management Information System (DERMIS)”,
Communications, vol. 58, March 2006, p. 637-661.
Annual
Review
of
van der Vlist E., XML Schema, The W3C's Object-Oriented Descriptions for XML, First
Edition, O’Reilly, 2002.
van de Walle B., Turoff M., “Emergency Response Information Systems: Emerging Trends
and Technologies”, Communications of the ACM, vol. 50 no. 3, 2007, p. 29-31.
van Veelen B., Storms P., van Aart C., “Effective and efficient coordination strategies for
agile crisis response organizations”, in Proceedings of the 3 rd International Conference on
Information Systems for Crisis Response and Management (ISCRAM 2006), New Jersey,
USA, May 14 2006, p. 202-213.
Webb G.R., “Role improvising during crisis situations”, International Journal of Emergency
Management, vol. 2 no. 1-2, 2004, p. 47-61.
World Wide Web Consortium, Extensible Markup Language (XML) 1.1. Second Edition,
W3C
Recommendation,
Retrieved
August
8,
2006,
from
http://www.w3.org/TR/2006/REC-xml11-20060816/
World Health Organization, Was 2005 the year of natural disasters?, Bulletin of the World
Health Organization, vol. 84 no. 1, 2006, p. 4-8.