Enhancing Enterprise Information Systems Synergy in Disaster

Management

Ovidiu Noran

Griffith University, Nathan QLD 4111, Australia

Keywords: Disaster Management, Enterprise Architecture, Collaborative Networks.

Abstract: Climate change-triggered catastrophic events appear to be steadily increasing in intensity and frequency.

Proper preparation, response and recovery are essential in order to survive and recover from disasters. Un-

fortunately however, the organizations responsible for delivering emergency response services often under-

perform, mainly owing to the lack of proper collaboration (especially interoperation) of their information

systems. This paper analyses disaster management-specific collaboration issues from an enterprise infor-

mation systems perspective and proposes improvements based on advances in information systems and in-

teroperability research, using an enterprise architecture perspective and artefacts in order to provide a sus-

tainable holistic and life cycle-based solution.

1 INTRODUCTION

Although emphasis on environmental sustainability

and emissions reduction is increasing worldwide,

any significant results are bound to take extensive

time to slow down and reverse the current trend of

environmental degradation. In the meantime, climate

change-triggered catastrophic events appear to stead-

ily increase in intensity and frequency. In this con-

text, it is essential to be able to promptly and effec-

tively prevent, prepare for, respond to and recover

from catastrophic events. Governments worldwide

usually react by creating policies and organisations

(e.g. agencies) to tackle these aspects. The ‘disaster

management organisations’ (DMOs) thus created

operate in a complex environment (history / tradi-

tion, geographic location and culture, level / type of

governance etc), that typically triggers heterogeneity

and independent evolution. The resulting organisa-

tional diversity, while generally beneficial, requires

additional effort to achieve proper and effective col-

laboration (Whitman and Panetto, 2006). As coping

with large scale catastrophic events typically re-

quires resources and capabilities beyond those of in-

dividual organisations, effective cooperation of

DMOs at all necessary levels and addressing all rel-

evant aspects is essential. Failing to achieve this has

dire consequences including loss of property and

human life.

Enterprise Information Systems (EISs), as an es

sential and ubiquitous component of every organisa-

tion (Lehtinen and Lyytinen, 1986), play an essential

role in achieving the level of cooperation required to

enable organisational sustainability of the DM en-

deavour. This paper aims to focus on the information

system (IS) aspect of disaster management interop-

erability (as a crucial component of cooperation) and

to propose ways to address them using knowledge

accumulated in the IS and interoperability research

areas. The analysis is performed from an enterprise

architecture (EA) point of view and using EA arte-

facts, in an attempt to promote a whole-system and

life cycle-based approach covering all aspects

deemed as relevant for the DM universe of dis-

course.

2 DISASTER MANAGEMENT:

CURRENT ISSUES

The operation of emergency services is typically

regulated at state, national and international levels

(see (Australian Government, 2011); (Federal Emer-

gency Management Agency, 2011); (Go-vernment

of South Australia, 2004); (United Nations Interna-

tional Strategy for Disaster Reduction Secretariat

(UNISDR), 2011)). However, simply instructing or-

ganisations to cooperate using generic directives

does not bring about true collaboration. The likely

275

Noran O..

Enhancing Enterprise Information Systems Synergy in Disaster Management.

DOI: 10.5220/0004437202750283

In Proceedings of the 15th International Conference on Enterprise Information Systems (ICEIS-2013), pages 275-283

ISBN: 978-989-8565-61-7

 2013 SCITEPRESS (Science and Technology Publications, Lda.)

consequences are increased response times, confu-

sion about the situation on the ground and dispute as

to who, where and when is in charge.

Often, it is also difficult to coordinate the EISs of

DM participants due to incompatibilities in infra-

structure and difficulty in filtering and validating the

typical flood of information generated during disas-

ter events. For example, inconsistency in the type

and format of alert messages may delay intervention

and hinder warnings by creating a situation where

the population is ‘intoxicated’ with numerous am-

biguous and locally-irrelevant messages (Queens-

land Floods Commission of Enquiry, 2011); (Victo-

rian Bushfires Royal Commission, 2009). This may

lead to reduced prevention and response efforts on

the part of the intended recipients, potentially result-

ing in property and life loss situations. Currently, ef-

forts to standardise warning message protocols are

localised and enjoy rather low take-up rates (OASIS,

2005).

Two main approaches have been traditionally

used to address DMO cooperation problems. They

involve either centralisation (hierarchical command)

or federalisation of emergency services. Irrespective

of the approach used, proper emergency response

and cooperation has still not been achieved, as re-

flected in criticism expressed in various literature

(e.g. ('t Hart et al., 2005); (Clark, 2006); (Wiese,

2006)). The use of military operations-style net-

work-enabled capabilities as the backbone of disas-

ter management (von Lubitz et al., 2008) is valid on-

ly as part of the overall DM effort; in addition, it

also risks leading to over-reliance on infrastructure

that is very likely to fail during disaster events.

Various documents, inquiries reviews and reports

(('t Hart et al., 2005); (Brewin, 2011); (Igarashi et

al., 2011); (Queensland Floods Commission of En-

quiry, 2011); (United Nations International Strategy

for Disaster Reduction Secretariat (UNISDR),

2011); (Victorian Bushfires Royal Commission,

2009); (Wiese, 2006), etc), suggest that the culprits

responsible for the current shortcomings could in

fact be the inadequate information and knowledge

flow and quality between the participants’ EISs

(Prizzia and Helfand, 2001); (Wickramasinghe and

von Lubitz, 2007). The main causes of these prob-

lems appear to be heterogeneity-induced lack of

compatibility, mistrust, organisational confusion

(who does what and when) and even perceptions of

competition. True and efficient collaboration re-

quires the interoperability of processes, resources

and organisational cultures of the participants

(Kapucu et al., 2010); (Trakas, 2012), all of which

are reflected in their EISs (Stohr and Konsynsky,

1992). Another set of essential aspects addressed to

a lesser extent are the life cycles of the DMOs, dis-

aster management task forces (DMTFs), government

agencies, legislation, service providers, disaster

events and especially the relations between these life

cycles.

Other domains have also struggled with such

problems and have come up with possible solutions.

For example, the DMOs’ situation resembles that of

commercial enterprises that need to take on projects

beyond their own resources and knowledge, in the

context of global economy. Their solution is to set

up or join so-called ‘Collaborative Networks’ (CNs)

(Camarinha-Matos et al., 2009). Another valid anal-

ogy is that of allied armed forces that prepare to co-

operate in crisis situations by using standardised

agreements and joint exercises (NATO, 2006).

As DMOs worldwide may have full time, milita-

rised and voluntary / reserve staff components (de-

pending on the geographical location and local legal

and administrative situation), concepts from the

above commercial and military areas can be used

(provided of course that proper customisation is per-

formed so as to match the specific scenario).

3 DISASTER MANAGEMENT

COOPERATION: APPROACH

AND ASPECTS

DM cooperation involves many aspects; for exam-

ple, in addition to receiving the mandate to cooper-

ate, DMOs must also have the will and especially the

capability to work together in an optimal way.

The concept of interoperability is often used as a

measure of IS cooperation capability (e.g. the Levels

of Information System Interoperability (LISI) taxon-

omy in the Department of Defence Architecture

Framework v1 (2004)).

The analysis of interoperability in the DM do-

main must include some important aspects:

 what is the required interoperability extent?

 what components and / or aspects need to in-

teroperate?

 how can it be ensured that all necessary aspects

are covered ?

 can sustainable interoperability be achieved as all

participants evolve?

3.1 Extent of Interoperability

As each disaster event is unique, there is no ‘one

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276

size fits all crisis situations’ DMO interoperability

level. At a minimum, the participating organisations’

systems should be compatible, so they don’t hinder

each other’s operations (see Fig. 1).

Compatibility

Full

Integration

Acceptable

Possible

scenarios

Independence

Interoperability

Desirable

Figure 1: Acceptable and desirable EIS Interoperability

levels in disaster management.

In an emergency situation, the EISs of some task

force members are likely to be affected to various

degrees (culminating in complete shutdown). In this

situation, the remaining DMOs should be able to

continue within acceptable performance parameters

(see e.g. the ARPANET resilient network concept

(Heart et al., 1978)) and ideally, compensate for the

essential duties of the failed participants.

In a different scenario, even if the central point

of command and task force members were not af-

fected by the disaster event(s), the coordination be-

tween them could still be severely hindered by

communication infrastructure breakdown (see for

example (Crawford, 2012); (Queensland Floods

Commission of Enquiry, 2011)). In this situation, the

task force participants should be able to autono-

mously carry on their duties for a certain amount of

time. Such a capability can be acquired based on

pre-agreed procedures and shared knowledge set up

in advance and continuously monitored and updated

to maintain relevance and consistency.

Reviewing the relevant interoperability body of

knowledge we find that ISO14258 (ISO, 2005) es-

tablishes several ways to achieve interoperability:

integrated (common format for all models), unified

(common format at meta level) and federated (par-

ticipants negotiating an ontology as they go to

achieve a shared understanding of models). In the

case of DMOs, neither full EIS integration nor fed-

eralisation appeared to achieve the desired results,

mainly due to the organisational heterogeneity of

DMOs and the impossibility to negotiate ‘on the fly’

during disaster event response.

The unified approach (who according to litera-

ture appears the most feasible in this situation) re-

quires only the ontology to be negotiated in advance.

Unfortunately however, despite significant ontology

integration advances, currently in DM there seems to

be no effective solution other than the DMOs spend-

ing time well before disaster events in order to agree

on the meanings associated with the concepts used

to exchange knowledge. Once that is achieved,

proper EIS semantic interoperability should be al-

most intrinsic to the task forces formed by the partic-

ipant DMOs.

3.2 Interoperability Aspects

Of all the interoperability aspects reviewed in the

relevant literature, the most stringent in the disaster

management area appear to be data and process.

Thus, the ability to extract and exchange data from

heterogeneous sources (delivering high volume and

often unreliable data during disaster events) is para-

mount to being aware of the conditions on the

ground and avoiding potentially life-threatening sit-

uations for emergency crews and population. Prior

agreements on data format and especially on its

meaning are essential. ‘Process interoperability’ in

this context concerns the capability to perform joint

operations but also to ‘take over’ and perform pro-

cesses on behalf of a disaster management task force

participant that may have been temporarily or per-

manently disabled.

The pragmatic interoperability aspect as de-

scribed by Whitman and Panetto (2006) relates to

the willingness and capacity of the participants to

cooperate. In disaster management, the human com-

ponent of the EIS needs attention prior to task force

formation in order to allow gaining trust and com-

mon understanding among the participants.

Organisational interoperability is an important

aspect in disaster management as task force partici-

pants may often exhibit significant organisational

structure diversity. The issues identified by Chen

(Chen, 2006) based on the Enterprise Interoperabil-

ity Framework (EIF), namely responsibility, authori-

ty and type of organisation can all impact heavily on

the functionality of the disaster management task

force. In a crisis situation, the roles (mapping of the

human resources onto the decisional structure) and

hierarchy must be clear to everyone from the start so

that the DMTF can ‘hit the ground running’ and fo-

cus straight on the disaster event rather than waste

precious time figuring out its own management and

operational details.

Finally, cultural interoperability (Whitman and

EnhancingEnterpriseInformationSystemsSynergyinDisasterManagement

277

Panetto, 2006) appears to be one of the hardest ob-

stacles to overcome. The only current working solu-

tion appears to be regular immersion of the partici-

pant organisations in each other’s cultures (for

example, Army joint exercises, or expatriates as

skilled language translators). This immersion facili-

tates the transfer and conversion of tacit and explicit

knowledge between the participants and thus enables

the unified approach previously identified as optimal

in disaster management.

A recurring concept through all aspects analysed

above is the ‘co-habitation’ of the organisations that

are expected to form disaster management task forc-

es, seen as a prerequisite towards the achievement of

EIS interoperability - whether functional, informa-

tional, organisational or cultural. This paper propos-

es to tackle the co-habitation concept by adopting a

life cycle-based, customised Collaborative Network

paradigm.

4 COLLABORATIVE

NETWORKS FOR DISASTER

MANAGEMENT

Collaborative Networks (CNs) are created in order

to allow participating companies to know each other,

gain trust and establish common agreed-upon proce-

dures and infrastructure baselines. This enables CN

members to promptly form Virtual Organisations

(VOs), i.e. groups of companies that temporarily

come together under a unique identity in order to bid

for, win and complete projects requiring extensive

resources and knowledge. A CN ‘lead partner’ may

also be present, (self-)elected on size, influence, re-

sources, etc. CN partners may take part in one or

several VOs at any given time.

The CN concept may be adapted and applied to

the disaster management area. Thus, the time availa-

ble for the set-up of a ‘disaster management’ VO

(here represented by the DMTF) is significantly

shorter than that available for a commercial project

bidding process. In addition, the disaster manage-

ment CN (DMCN), its participants and the DMTF(s)

produced will operate under tight legal operational

guidelines set by relevant Governments and national

and international frameworks (e.g. (Federal Emer-

gency Management Agency, 2011).

The commercial and competitive motivations of

the typical CN participants will translate in this case

into efficiency and cooperation motivations reflected

in lives and property rescued. The usual create / join

/ remain / leave the CN decision processes are man-

dated from outside (or by the lead partner) for most

participants. Reference models (patterns) classified

on type and location (such as flooding, tornadoes,

wildfires, earthquakes etc (Ellis et al., 2004)) are to

be created from lessons learned in past disaster relief

efforts and used to refine future DMTFs. shared re-

pository and customised for specific geography, in-

tensity, duration, side-effects and consequences.

The DMTF(s) produced by the DMCN will be

set up for and assigned a specific DM project relat-

ing to a particular disaster event (or combination

thereof). EIS cooperation aspects such as manage-

ment, communication infrastructure, and other or-

ganisational interoperability issues would have been

sorted out in advance within the DMCN, ensuring a

prompt and appropriate task force response (address-

ing a typical shortcoming identified in past crisis

management efforts (Trakas, 2012)).

Human-related aspects such as trust, organisational

culture and recognition (featuring prominently in

volunteer-based organisations (Esmond, 2011);

(McLennan, 2008)) could be also addressed using

the concept of ‘emergency services academies’ with

local branches providing training based on a con-

sistent interstate curriculum (see (Queensland Gov-

ernment, 2011) for an example).

5 THE LIFE CYCLE CONTEXT:

AN ENTERPRISE

ARCHITECTURE VIEW

All entities involved in disaster management efforts

continuously change, going (sometimes repeatedly)

through a set of life cycle phases that form the enti-

ties’ ‘life histories’ (ISO/IEC, 2005). EIS interoper-

ability requirements are inherently linked to life his-

tory as they will vary during each host

organisation’s life cycle phase; therefore, it is essen-

tial that the analysis and search for cooperateon and

interoperability improvements is performed in a life

cycle context.

In the following we argue that adopting an ‘en-

terprise architecture’ (EA) approach provides an op-

timal way to integrate the life cycle aspect into EIS

cooperation analysis. This is because EA provides a

holistic approach to business evolution and agility

“by creating, communicating and improving the key

requirements, principles and models that describe

the enterprise's future state […]. EA comprises peo-

ple, processes, information and technology of the en-

terprise, and their relationships to one another and to

the external environment” (Gartner Research, 2012).

This EA definition is in agreement with the view of

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278

Management

and Control

Cust Service

Simplify

Formalism used

in the Business Mode

Human

Machine

Resource

Information

Function

Hardware

Software

Design

Prelim. design

Detailed design

Identification

Concept

Implementation

Operation

Decommission

Requirements

Partial level of

GERA Modelling

Framework

Organisation

Life Cycle-

ased

formalism

Figure 2: Using Enterprise Architecture Modelling Framework elements to develop a life cycle formalism.

IS as a socio-technical system (Pava, 1983) with

voluntaristic people (McGregor, 1960) in a complex

organisational, political and behavioural context

(Iivari, 1991); (Keen and Morton, 1978). As such, it

enables the use of EA as a life cycle-based, integrat-

ed and holistic approach to analyse the EIS coopera-

tion requirements of the DMCN and DMTF partici-

pants.

To illustrate the way EA artefacts and methods

can guide and enrich the analysis and improvement

of DMO cooperation, we have selected a generic ar-

chitecture framework (AF) that subsumes and ab-

stracts several other mainstream AFs, defined in

Annex A of ISO15704 (ISO/IEC, 2005) and called

the Generalised Enterprise Architecture and Meth-

odology (GERAM). The modelling framework (MF)

of GERAM’s reference architecture (called GERA)

contains a rich repository of aspects (notably includ-

ing human) that can all be represented in a life cycle

context. GERA’s MF has been used to model and

analyse systems across many areas (e.g. (Mo, 2007);

(Noran 2008; 2009)).

Aspect-based subsets of the GERA MF can be

turned into life cycle-based formalisms used to pro-

duce business models requiring a life cycle-based

analysis. For example, the aspects previously identi-

fied as significant in improving EIS cooperation in

disaster management (such as function, information,

resources, organisation) but also additional useful

viewpoints like management vs. operations, automa-

tion boundary / human extent, etc) can be represent-

ed as shown in Fig. 2, left.

Aspects can also be separated to promote clarity

by using ‘flattened’ representations; for example, the

2-dimensional structure shown in Fig. 2 right is used

to focus on the product/service and management

viewpoints in a life cycle context. This formalism

can then be used for separate, dedicated function, in-

formation (see Fig. 5), resource, organisation, hard-

ware, software etc diagrams.

Fig. 3 left shows the use of the above-described

formalism to represent a disaster event, focusing on-

ly on the relevant life cycle phases and relations to

other events’ life cycles. Thus, Fig. 3 left shows how

a Primary Disaster Event (PDE) can trigger / influ-

ence other events (SDE, TDE); For example, an

earthquake PDE can trigger a tsunami SDE that can

in turn trigger a partial nuclear meltdown TDE. The

model also shows that PDE can also influence TDE

directly and/or in parallel. Events such as chain reac-

tions can also be shown (arrows from Operation to

Implementation within the same entity). Note that

here, the meaning of the generic GERA MF ‘De-

tailed Design’ and ‘Implementation’ life cycle phas-

es refers to features of the event – e.g. earthquake

time, epicentre and duration or tsunami spread, wave

speed, height etc.

The right hand side of Fig. 3 shows how the life

cycle phases of a disaster management project

(DMP) can be mapped against typical disaster man-

agement activities (e.g. as defined by the Australian

Government (2011)) performed by a DMTF that sets

up and operates that project.

EnhancingEnterpriseInformationSystemsSynergyinDisasterManagement

279

= Management view = Possible scenario

PDE

Legend:

PDE / SDE / TDE = Primary / Secondary / Tertiary Disaster Event;

DMP = Disaster Mgmt Project; DMTF = Disaster Management Task Force

Disaster Event modelling

TDE

SDE

Mgmt.

Prevention

Preparation

Response

Recovery

DMP

life cycle phases

Prod.

Disaster Event mapping

= Production view

DMTF

Activities

Figure 3: Disaster events mapping and modelling accomplished using a life cycle-based modelling formalism.

Operation

Implementation

Det. Design

Prel. Design

Requirements

Concept

Identification

Prevention

Preparation

Response

Recovery

Decommission

Disaster Mgmt

Project

Life Cycle

Unified

Approach

Business

Service

Process

Data

Conceptual

(syntax | semantics)

Technological

Organisational

(DMTF) Disaster

Management

Actions

IS Interoperability

Aspects / Importance

= essential

= secondary

= tertiary

Legend (aspect importantce):

Figure 4: Enterprise Information Systerms’ Interoperability requirements mapped on disaster management actions and the

disaster management project life cycle, using Chen’s EIF (Chen, 2006) and GERA’s MF-based formalism.

Such diagrams are useful to help DMCN and

DTMF participants to promptly grasp a common un-

derstanding of the disaster event lifecycle and man-

agement aspects, thus overcoming initial EIS in-

teroperability semantic barriers and facilitate all

DMP phases Fig. 4 uses a modified version of

Chen’s EIF and GERA’s MF-based life cycle mod-

elling formalism to show how the relevance and ap-

plicability of the EIS interoperability aspects depend

on the specific life cycle phases of the disaster event

and the DMTFs’ actions to address them.

As can be seen from the figure, various interop-

erability aspects may take precedence as the disaster

event life cycle phases unfold. For example, during

the response phase, data and process IS interopera-

bility aspects are paramount. This is because accu-

rate and fresh data is required and processes may

need to be performed interchangeably due to poten-

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280

tial disability of some DMTF participants (or the

need to call upon replacement DMCN members).

During the recovery, which typically takes place

over an extended period of time and requires less re-

al-time responsiveness, organisational business and

service EIS interoperability aspects may become

more important.

6 SAMPLE APPLICATION TO EIS

INTEROPERABILITY

Fig. 4 shows only the influence of the disaster event,

management project and task force life cycles on the

interoperability requirements. As a matter of fact,

DMCNs, DMOs, DMTFs and DMPs interact with a

plethora of entities and artefacts during their life his-

tory. These interactions must also be analysed in or-

der to gain a holistic view of the EIS cooperation re-

quirements.

Using the GERA-based formalism described in

Section 5, diagrams can be constructed for the as-

pects identified in Section 3.2 as relevant to IS in-

teroperability. For example, Fig. 5 shows interoper-

ability-related interactions for the Information (data)

interoperability aspect, in the previously described

scenario of a collaborative network (DMCN) creat-

ing task forces (DMTFs) supervising disaster man-

agement projects (DMPs) that coordinate disaster

event responses.

The arrows in the figure show data interoperabil-

ity requirements and influences. For example, the

participating DMOs’ EISs need to interoperate dur-

ing their Operation life cycle phase; however this

may also imply some redesign (line between DMO1

and DMO2 linking Operation and other life cycle

phases, depending on the redesign extent). The EIS

of the DMBE must be able to interoperate with the

EIS of the DMTF it creates and DMPs managed by

them in their Operation life cycle phases, with influ-

ences on other phases in case of subsequent redesign

(details omitted for clarity).

In another example, data ‘interoperation’ (i.e.

properly interpreting the messages) of the population

POP with the Government’s Disaster Management

Agencies (GDMAs, such as (Government of

Queensland, 2012)) is important as may result in

changes to legislation - hence in the DMO and

DMBE interoperability requirements. However, data

interoperability between the EISs of DMOs partici-

pating in a DMTF and between the DMTF’s EIS and

POP is paramount as it will directly influence the ex-

tent of lost property and casualties. Past experience

and feedback from disaster enquiries (Ellis et al.,

2004); (Queensland Floods Commission of Enquiry,

2011); (Victorian Bushfires Royal Commission,

2009) has shown that two major goals of the disaster

management cooperation enhancement effort (partly

reflected in Fig. 5) should be: a) whether POP re-

ceives, understands, believes and acts on DMTF

warnings and directives and b) that DMTF partici-

pants can properly interoperate during the disaster

event. Thus the EIS of the DMTFs (and implicitly

DMOs) should be also designed to avoid ambiguity

and maximise focus in relation to the local specific

semantic interoperability requirements (language,

technology type, customs etc). For example, the

message format and distribution in a densely popu-

lated and developed area would most likely differ

from the one used in a sparsely and/or under-

developed region - at least until warning information

standardisation is successfully and widely imple-

mented.

Importantly, some organisations shown in Fig. 5

should be able to redesign themselves to a certain

extent (arrows from Operation life cycle phase to

upper phases within same entities e.g. in DMBE,

DMO, DMTF). This reflects an essential capability

to adapt (and thus be agile and resilient) in the face

of changes in the situation and environment that are

likely to occur briskly and unexpectedly during dis-

aster events.

The Disaster Management Qualification and

Training organisation (DMQT, e.g. (Queensland

Government, 2011)) can assess the suitability of or-

ganisations to enter a DMBE by requiring (and

providing training if appropriate) EIS data interoper-

ability between DMO applicants and the DMBE.

This requirement may also go beyond the Operation

life cycle phase, should training / redesign of the

participants be performed.

The validity and effectiveness of the DMBE

concept can be tested by joint exercises (JEs), simu-

lating disaster events; they can also help reveal addi-

tional EIS data interoperability problems. JEs will

assess the resilience of DMTFs in various scenarios,

with appropriate corrective action taken to improve

DMCN members’ preparedness and DMTF agility.

7 CONCLUSIONS AND FURTHER

WORK

As the world climate is changing, mankind is expe-

riencing more frequent and intense catastrophic

events. The DM effort must adapt to these changes

by addressing urgent cooperation issues in advance

and in a holistic manner so that when disaster events

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281

DMCN

DMO1

GDMA

DMP / JE

POP

DMTF

DMC

EML

Life cycle phases: Id: Identification; C=concept; R=requirements, PD=preliminary design, DD=detailed design,

I=implementation, Op=operation, D=decommissioning. Other aspects: P=Production / Service, M=management

DMBP

TFRM

Legend:

DMOx: Disaster Mgmt. Orgs

DMP: Disaster Mgmt Project

JE: Joint Exercise

DMCN: Disaster Mgmt Collab Netw.

EML: Emrg. Mgmt Laws

DMBP: Disaster Mgmt Best Practice

DMC: Disaster Mgmt Contractors

DMQT: Disaster Mgmt. Qualification

& Training

TFRM: Task Force Reference

Model

DMTF: Disaster Mgmt Task Force

GDMA: Govt Disaster Mgmt Agency

POP: population

: Operation phase, Production

& Management

: Operation Phase, Production

: Possible scenario

DMO2

DMQT

Figure 5: High-level IS Data Interoperability requirements in the context of a Disaster Management Collaborative Network

and Disaster Management Task Force solution (some details omitted for clarity).

occur, efficient collaborative task forces can be

promptly put together. In order to tackle the EIS in-

teroperability problems that plague the DMOs now-

adays, it is proposed to adopt a customised collabo-

rative approach based on commercial CN and VOs.

As DMCN participants’ life cycles play a central

role in their EIS interoperability, it is argued for and

shown how an EA approach and artefacts can pro-

vide an integrated, holistic and life cycle-based ap-

proach supporting the proposed collaborative para-

digm applied to the DM effort.

Further research will concentrate on testing, veri-

fying and validating the findings with DMOs, in-

cluding the set up of pilot DMCNs future case stud-

ies.

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