Figure 1. Long-term trends in disasters. The OFDA-CRED International Disaster Database cited by [3].

Figure 2. Urban population (in billions) in developed and in developing countries. According to United Nations (1999) [4].

Metamodel of Shared Situation Awareness for Resilience Management of Built Environment

Dr. Igor A. Kirillov

National Research Centre "Kurchatov Institute"

Moscow, Russia, kirillov.igor@gmail.com

Sergei A. Metcherin Moscow Institute of Physics and

Technology Moscow, Russia

sergei.metcherin@gmail.com

Prof. Stanislav V. Klimenko Institute of Computing for Physics

and Technology Protvino, Russia

stanislav.klimenko@gmail.com

Abstract— This report describes an ongoing Russian research program, which aimed at development of a methodological framework for a nation-wide multi-hazard crisis management «system of systems» (SoS) for built environment. In addition to a currently available system of separate departmental legacy cybersystems, targeted, mainly, at disaster response and recovery only, the proposed SoS shall provide a shared situational awareness of the stakeholders (operators and authorities, responsible for built environment - municipalities, Ministry of Emergency, Fire Brigades, Ambulance, Police, etc.) and the citizens under risk during at a whole life-cycle of hypothetical crisis, especially at pre-crisis and crisis stages. One of the cornerstone of crisis management SoS development is a common core ontology for conceptualization of risk-related activities within SoS framework. This article is focused on a proposed shared situation awareness meta-model and its distinctions from the prior art and concurrent developments.

Keywords - crisis, life-cycle, metamodel, ontology, system of systems, virtual collaborative spaces, built environment, resilience, risk-informed, sensor-based

I. INTRODUCTION Safety and security of citizens in built environment will

be one of a topical problem in coming years. During previous decade the risks of crises or emergencies with harmful or costly consequences (natural disasters, industrial accidents, terroristic calamities, etc.) of different nature and their negative impact on societies and economics steadily rising (see Figure 1).

Aircraft-building crash on 9/11 in New-York, tsunamis in south-east Asia, terrorist attacks in Tokyo and Madrid subways, earthquakes in Chili and Haiti are just a few world-wide and well-known examples.

Statistics of insurance companies, social perceptions and economic demands initiating a revision of the currently available paradigms of safety provision for the high consequence systems with high-density human (see Figure 2) or bio-resources population – megalopolises (in particular – capitals of countries), industrial or innovation agglomerates (California state in USA), world-scale centers for trade (Hogn Kong in China) or logistic (Rotterdam harbor area in the Netherlands), off-shore oil or gas extraction and transport systems (in Northern sea and Mexican Gulf).

Throughout the world a set of [1] initiatives to develop new tools for risks reduction and disaster prevention/preparedness were launched.

In USA, activities in this direction are coordinated by Federal Emergency Management Agency (FEMA).

In EU, planning and coordination of appropriate R&D efforts is doing by Joint Research Centre in Ispra (Italy) through its Institutes for the Protection and Security of the Citizen (IPSC) and for Environment and Sustainability (IES).

In Russia, in Item 107 and 108 of the National Strategy for State Safety and Security [5][3] two goals were posed - 1) "... to integrate situational centers of different state

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departments via seamless information interaction...", 2) "... provide harmonization of national informational infrastructure with global information networks and systems...", related with crisis/disaster/emergency management. In fact, mentioned National Strategy imply a development of System-of-Systems, i.e. a collection of crisis task-oriented or emergency management-dedicated systems that pool their resources and capabilities together to create a new, more complex system which offers more functionality and performance than simply the sum of the constituent systems.

All mentioned large-scale activities (mainly at R&D level) were initiated as a result of inability of existing theoretical and organizational frameworks to respond to today’s safety challenges.

II. RESILIENCE OF BUILT ENVIRONMENT - NEW PARADIGM OF CRISIS MANAGEMENT

In order to protect peoples, structures and others assets in contemporary cities and critical infrastructure against multi-hazards new concepts of crisis management are under development.

One of this emerging concept for provision of enhanced safeguarding for civil built environment is a "risk-informed, multi-hazard resilience management" (RM) paradigm [6] - or shortly - "resilience management".

Resilience management paradigm infers that enhancement of protection level will be provided via three basic threads –

� Multi-hazard risk-informed management of Available Adapting Capabilities (AAC),

� Multi-hazard risk-informed management of Existing Vulnerabilities (EV),

� Network-enabled management of Shared (between stakeholders - inhabitants, subjected to risk, and the multiple relief/care/safeguarding teams and systems – operators and authorities of built environment, rescue, ambulance, fire brigade, etc.) Situational Awareness (SSA)

Figure 3. Three pillars of resilience management paradigm (from [6]).

A. Shared Situation Awareness in Resilience Management Shared Situation Awareness is a central operational tool

within RM paradigm. It provides information and knowledge support both for decision making and for cooperative/collaborative actions of different stakeholders during whole life-cycle of crisis.

Practical implementation of agile (comprehensive, responsive and flexible) SSA requires electronic and semantic integration and interoperability of multiple Information Systems (IS) of stakeholders. Integration is requested in first turn, between well established state or authorized organizations (responders - Emergency, Ambulance, Police, etc.) and with their already functioning IS.

B. Shared Situation Awareness Problems in Legacy Crisis Management Systems

1) Reactive vs Proactive Approaches Main deficiency of dominating now paradigms for

safety/security/health provision is their, de facto, reactive nature.

De jure, almost all national or international crisis management systems follow to a proactive approach for safety assurance. This approach emphasizes need in prevention/preparedness (actions taken to prepare for effective crisis or emergency response) and mitigation (actions taken to reduce the consequences of a crisis or an emergency, when is emerging or has already occurred) (see Figure 4 below). A proactive approach is designed to anticipate and prevent accidents.

Figure 4. Representation of traditional crisis/disaster mamagement life-cycle (see different definitions of disaster/crisis/emergency cycle in [7]).

However, in practice, reactive programs/activities of the governmental and/or authorized bodies of responders kick in after an accident has occurred only. This trend (to concentrate, mainly, on post-disaster phases - response and recovery) is obvious, for example, in ontology, defined in the frame of the OASIS (Open Advanced System for dISaster & emergency management) project in 2005 and which will be the basis of a future European Disaster and Emergency

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Management System [8]. Specific tools, which can be operational for prevention/mitigation of hypothetical disaster, for example, via pro-active risk management, are absent in OASIS ontology (see Figure 5 below) and in other ongoing research projects [9].

Figure 5. Scope of disaster response ontology (OASIS project [11]).

2) Time-scale Separation in Resilience Management Majority of legacy information systems for disaster and

emergency management (DEM - for example, at national or at local level) were built in assumption, that the term "disaster" "...implies a sudden overwhelming and unforeseen event" [11]. It means, implicitly, that 1) duration of disaster was considered as negligible with characteristic times of EM procedures and communications, and 2) escalation of crisis at System-at-Risk (SaR - for example, high rise building or transport hub) level can not be monitored at EM level.

In reality, each crisis evolution (within or outside of the SaR boundaries) has its own duration. Sequence of the harmful processes (drivers of crisis escalation) can be characterized by measurable/computable indicators, i.e. crisis evolution can be described by appropriate SaR life-cycle, which is distinct from EM life-cycle (see Figure 6 below).

Figure 6. Time-scale separation for System-at-Risk (SaR) and Disaster and Emergency Mamagement (DEM) life-cycles.

Each crisis at a given SaR is preceded by a set of the phenomenological precursors and by a set of anomalies in performance of its technical, organizational or information sub-systems. Precursors can be visible or sensible either for external observers or internal (to SaR) monitoring system. Anomalies in performance can be identified and tracked by appropriate SaR's information system. Fast and accurate processing of information, concerning pre-cursors or/and abnormalities, can be used for preventing accident.

At crisis stage, either intrinsic robustness (for example, high fire resistance of building structure) of SaR or activation of the mitigation systems (like, for example, sprinklers) can prevent or, at least, retard escalation of crisis into disaster.

From resilience management perspective, at SaR's pre-crisis and crisis stages just situation awareness, shared (see Figure 6 above) between peoples inside of SaR, casual external observers, information systems of SaR and EM system is vital for risk minimization or even avoiding of transformation of crisis into disaster. For adequate capturing of this topic at least two sub-ontologies with different granularity shall be developed. It will be reasonable, that EM system will operate with a coarse-grained level of reality representation and SaR system with a fine-grained ones.

3) Interoperability of the Governmental and Volunteers Resources

Quality and completeness of shared situation awareness can be enhanced via usage of the resources and contributions from the ad hoc virtual collaborative spaces of the non-governmental and volunteers organizations.

Benefits of this type integration was demonstrated during large-scale forest fires in Russia in summer 2010. Volunteers took part in fire fighting and helping those affected by the fires. In some cases, informal help was faster and more effective than official help. Some volunteer coordination was via LiveJournal communities. The main one was pozar_ru. There was also a website Russian-fires.ru working on Ushahidi cyber platform that was used at Haiti and Chile earthquakes to coordinate volunteers.

The mentioned and other successful evidences of governmental-volunteers interaction argue why interoperability of their temporary/occasional (Facebook-, or Twitter-like virtual communities, WEB-based platforms for disaster/crisis monitoring, mobile phone calls, etc.) IS with governmental legacy Information Systems is necessary.

C. Shared Situation Awareness Ontology Integration Process for SoS Integration of drastically different (from nature of

information and software viewpoint) and heterogenous (from hardware viewpoint) communication systems can be made using ontology-based approach [13]-[17] for data, information and knowledge sharing and reuse.

We used existing situation awareness model [18] and disaster management model [19]as two starting points towards creating a unifying (as far as it will be reasonable) meta-model of ontology for a shared situation awareness (SSA) processes within a System-of-Systems (SoS).

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Figure 7. Shared situation awareness meta-model for resilience management of built environment within System-of-Systems

framework.

Figure 8. Risk meta-model for resilience management of built

environment within System-of-Systems framework.

Development of our meta-model was made from multi-hazard resilience management perspective. It was assumed, that meta-model to be operational for execution of the two key tasks, posed in [5].

Process of enlargement of core ontology [15], which was selected as our immediate predecessor, included the following steps:

1) identification of key modules in which the ontology can be divided into or extended,

2) identification the assumptions and ontological commitments that each existing or additional module should comply to (special attention was paid to overcome the ontology deficiencies, described in Sub-Section B of this paper. Knowledge from the concurrent projects [19] and [20] was also taken into account),

3) identification of what new knowledge or topical practical experience (from committed experts with relevant practical experience and knowledge) should be represented in each existing or new module,

4) feasibility analysis of proposed ontology improvements from viewpoint of their realization,

5) implementation of new proposed modules or reformulation/refinement of existing modules in Protege format for formal ontology building (including porting of sub-ontologies, generated by invited experts (without literacy in knowledge engineering) in the UML or concept map formats).

III. METAMODEL FOR SHARED SITUATION AWARENESS IN RESILIENCE MANAGEMENT OF BUILT ENVIRONMENT Proposed meta-model, which can, in principle, to

overcome deficiencies and limitations of the existing de facto reactive approach to disaster and emergency management, has the following specific features:

A. Risk Monitoring, Treatment and Communication as a Operational Tool for Proactive Prevention and Mitigation Introduction of risk monitoring, treatment and

communication (see Error! Reference source not found. below) as an additional obligatory task of disaster and emergency management system will provide a pragmatic and operational support of pro-active risk avoidance or harmful consequences minimization for built environment.

At left side of Figure 7 a core ontology of instantiation of legacy emergency system (as it is seen from the OASIS project perspective) is shown. Basic class "EMS" in this meta-model represents two types of concepts -

1) the loose "departmental Systems" (Fire Brigade, Police, Ambulance, etc.), whose duty is to respond to disaster or care of victims/casualties, and which have their own steadily functioning information systems, to be subjected to integration for more effective inter-departmental collaboration and

2) the ad hoc virtual collaborative spaces of the non-governmental and volunteers organizations.

Basic concepts of ontology of System-at-Risk (for example, high-rise building or multi-model transport hub,

etc.), which can be subjected to dangerous factors, is shown at right side of Figure 7.

Operational data, information and knowledge sharing between the "responders" and "assets-at-risk" in proposed architecture of System-of-Systems can be provided by "Risk Monitor" sub-system.

Relations between core concepts, related with risk monitoring, treatment and communication, in proposed SaR ontology are shown at Figure 8 below.

Vital for resilience management parameters - existing vulnerabilities of "assets-at-risk" inside of SaR and available adaptive capacities of SaR - can be

1) extracted and assessed using "Performance Monitor" and "Structural Health Monitor" and

2) communicated to tactical and strategic levels of

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Figure 9. Meta-model for on-line sensor- and video-based performance

and structural health monitoring of built environment.

Figure 10. Meta-model for vulnerabilities and adaptive capacities assessment during pre-crisis stage at SaR.

"responders" (in term of OASIS project vocabulary) via "Risk Monitor" in on-line or nearly on-line regime.

In contemporary high consequence built environment (stadiums, multi-functional trade and entertainment centers, etc.) on-line monitoring of SaR's performance and structural state-of-health is executed by a set of the sensor-based cyber spaces (see Figure 9 below), targeted on management of different (critical for safety and security) sub-systems of a given SaR - high consequence building or structure.

Formation, refinement and maintenance of the sub-ontology, focused on network-enabled sensoring and video surveillance and aimed at characterization of performance and structural state-of-health is based on

1) analysis of the interviews with experts in civil engineering, building engineering, architectural Engineering, structural engineering, information technology, construction management, safety/security management, construction informatics,

2) knowledge conceptualization from the technical sources and databases on BIM (Building Information Model)

[21], construction informatics [22], 3) information and knowledge acquisition from available

technical standards on emerging ([23]) or well established ([24]) topics of risk management and safety provision.

Extraction and timely use of crisis-relevant information from the appropriate cyber-spaces of SaR and its seamless fusion (via Risk Monitor) with Team Situation Awareness (TSA) of the state/authorized agencies and volunteer organizations will, certainly, facilitate and promote attaining of a really Shared Situation Awareness between the "responders", "volunteers"/observers and people-at-risk in case of hypothetical crisis situation within System-of-Systems framework.

Electronic and semantic integration of the SaR's and EMS' cyber-spaces will also be instrumental in the following aspects of risk minimization and resilience management of built environment:

1) dismantling or, at least, reasonable minimization of real problem, concerned with large disparity between characteristic times of crisis escalation inside of SaR and characteristic response time of the departmental EMS,

2) shift from reactive disaster management paradigm to a more pro-active approach to safety and recovery.

B. Quantifiable Metrics for Vulnerabilities and Available Adaptive Capacities Assessment at Pre-Crisis Stage In our ontology, describing crisis evolution at SaR level

(see right side of Figure 7 and upper side of Figure 6), notion "pre-crisis" (see methodological details of stages discrimination in [25]) means a time slot between moment, when the first pre-cursors of a hypothetical crisis appeared, and time moment, when the first local damages/injuries appeared.

Just at this stage (see Figure 10 below), a timely identification and assessment of emerging vulnerabilities and available adaptive capacities of SaR is essential for successful coping with crisis and for disaster prevention. Detailed description of methodology for quantitative

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assessment of vulnerabilities and capacities of building/structure is out scope of this article and will be made elsewhere. Here, we only mention, that Performance Monitor and Structural Health Monitor at SaR side, can be a reliable and indispensable source of data and information for Risk Monitor at EMS side. More detailed inter-relations between activities of SaR life-cycle (marked by yellow) and activities of EMS life-cycle (marked by green) are shown at Figure 10 above.

Introduction of quantifiable (measurable or computable) metrics for existing vulnerabilities and available adaptive capacities will make it possible a systematic, consequential transformation to a risk-informed resilience optimization of built environment.

IV. SUMMARY AND FUTURE WORK Meta-model for shared situation awareness for resilience

management of built environment is proposed. Our approach leads to a conceptual framework for a

nation-wide multi-hazard crisis management «System of Systems» for built environment. Proposed two-time-scale architecture of SoS is scalable and adaptive to cope with problem of "delayed response" of legacy emergency systems to crisis escalation in high consequence buildings and structures.

Tactical Situation Object from EU-funded OASIS project was selected as a prior art ontology.

Conceptual problems, associated with shared situation awareness in legacy emergency management systems and in concurrent research projects, were described.

Two new features (in comparison with prior art meta-model) were introduced - 1) risk monitoring, treatment and communication as an operational tool for proactive prevention/ mitigation, and 2) quantifiable metrics for assessment of the vulnerabilities and available adaptive capacities of building / structure.

Our meta-model was developed in deterministic paradigm.

An open issue is - how to tackle with intrinsic for crisis management data and information uncertainty and its propagation within SoS system ?

ACKNOWLEDGMENT Authors are grateful to the Russian Foundation of Basic

Research for support of the grants, targeted on the development of the risk-informed technologies (11-07-00329-а) and advanced visualization systems (11-07-13166-ofi-м-2011_RZD) for crisis management.

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