Carol J. Romanowski

Measurement of locality specific resilience

Resilience has been defined at the local, state, and national levels, and subsequent attempts to refine the definition have added clarity. Quantitative measurements, however, are crucial to a shared understanding of resilience. This paper reviews the evolution of resiliency indicators and metrics and suggests extensions to current indicators to measure functional resilience at a jurisdictional or community level. Using a management systems approach, an input/output model may be developed to demonstrate abilities, actions, and activities needed to support a desired outcome. Applying systematic gap analysis and an improvement cycle with defined metrics, the paper proposes a model to evaluate a communitys operational capability to respond to stressors. As each locality is different-with unique risks, strengths, and weaknesses-the model incorporates these characteristics and calculates a relative measure of maturity for that community. Any community can use the resulting model output to plan and improve its resiliency capabilities.

Regional response to large-scale emergency events

A widespread emergency event in the United States triggers the activation of a regional emergency operations center that manages a coordinated response to the disaster. Historically, the time-critical decisions made by emergency managers in the face of incomplete information and inadequate historical emergency event data have been guided primarily by their experience. The learning curve for emergency managers, especially novice managers, is steep, and is exacerbated by the complexity and scope of emergency events. This paper proposes a methodology designed to provide emergency managers with locality-specific information and resource allocation recommendations for large-scale event response, creating the foundation for a decision support system that draws on emergency event data. This work is the first to use locally-specific data for an emergency management decision support system. Two major allocation scenarios that influence the number of resources allocated to an event are considered and solutions are suggested to address them. Although the methodology is developed for a mid-sized region, it is generalizable to any region.

Information management and decision support in critical infrastructure emergencies at the local level

In a critical infrastructure disaster incident, emergency managers are often compelled to make time-critical decisions based on incomplete information streaming in at disparate times from multiple data sources. As the incident progresses, the ability to predict where additional resources will be needed is crucial to both response and recovery. Decision making and prediction in this context requires combining (fusing) incoming data streams; presenting relevant information from these streams in a form appropriate for each user; and using data from similar historical events to predict resource needs and incident evolution. This paper discusses the role of data fusion, data integration, and data mining in decision making for municipal or regional emergency managers. It also explores the implementation of web-based decision support tools. Finally, the paper makes recommendations for improving information management and streamlining decision support.

A curricular framework for critical infrastructure protection education for engineering, technology and computing majors

The 16 critical infrastructure sectors identified by the US Department of Homeland Security employ many engineering, technology and computing graduates who increasingly face critical infrastructure protection (CIP) issues. However, most undergraduate curricula in these disciplines do not incorporate CIP in any meaningful way. This paper proposes a flexible curricular framework for integrating CIP into undergraduate education via self-contained inter-disciplinary CIP course modules; a course module is a distinct curricular unit such as a lab or teaching component for use by an instructor in existing courses without requiring any course or program modifications. The proposed course modules cover physical, human, and cyber aspects of CIP. The framework is designed for use in multiple disciplines, and the modules are designed for presentation at different levels of the undergraduate experience, with subsequent modules building on those presented earlier. This approach is intended to prepare students for careers solving problems in design, implementation, and maintenance of robust, sustainable infrastructure assets.

Mapping a community resilience management system: Building operational knowledge

System standards have been implemented in many contexts over the last few decades. Using closely aligned standards such as the emerging ISO 37120 typology for sustainable and resilient communities, and by drawing from various recognized capability models and indices, this paper develops a structure for operationalization of a community resilience management system, and then maps the system against the key attributes of a resilient community. This effort is a first step toward the management of long term resilience in our communities.

Decision making to support local emergency preparation, response, and recovery

Effective emergency management depends upon accurate information, especially in the case of disaster scale preparation, recovery, and response. As recent experience demonstrates, leveraging situational information is critical to community recovery. Critical incident management involves the fusion of variant informational sources leveraged through collection technologies onto a common organizational platform. Fusion of information requires a clear delineation of informational needs, flows, and interactions. Variability and uncertainty in the data must be addressed and accounted for. The compatibility and reliability of the data must also be fully defined. In the best circumstances, the platform would also guide the decision-maker in action by guiding the method by which the decision is executed. This paper discusses decision support system model development and demonstrates applicability to regional emergency management operations.

Catching the wave: Big data in the classroom

Many diverse domains-in the sciences, engineering, healthcare, and homeland security-have been grappling with the analysis of “Big Data,” which has become shorthand to represent extremely large amounts of diverse types of data. A recent Gartner report predicts that around 4.4 million IT jobs globally will be created by 2015 to support Big Data, with 1.9 million of those jobs in the United States. Therefore, understanding approaches and techniques for handling and analyzing Big Data from diverse domains has become crucial for not only in computing but also engineering students. The mini-workshop will make use of active and collaborative learning exercises to introduce faculty in computer science, software engineering, and other disciplines to concepts and techniques involved in managing and analyzing Big Data. Approaches for incorporating Big Data into the engineering and computing curricula will also be presented.

Critical infrastructure protection and risk analysis in the mid-size city

In this work, we frame a methodology for performing risk analysis for mid-size cities and their metropolitan statistical areas (MSAs) that addresses infrastructure vulnerabilities impacting far beyond the MSA boundaries. We address the challenges and pitfalls in assessing critical infrastructure in these MSAs, discuss inter- and intra-sector dependencies, and present a method to analyze criticality. These studies generate valuable results for emergency manager and planner use, especially since operations in these communities cover a wider geographical area with fewer resources in manpower and equipment. We conclude with recommendations for analysis and decision support tools built upon infrastructure assets, interdependencies, and connections with assets outside the MSA.

A Holistic Approach to Schema Matching

Schema matching, which establishes whether two objects are semantically related, has been a focus of data management research due to its critical role in enterprise information integration. Current schema matching techniques typically tend to exploit only a single method selected from matching schema structure, or syntax, or semantics, or data and probability distributions, which reduces the success of schema matching. An alternative approach to improve the effectiveness of schema matching is to use a holistic approach that integrates and generalizes techniques based on structural and syntactic comparisons, as well as probability distribution and mutual information. This paper describes this holistic approach and its implementation, and presents initial results of comparisons with existing techniques.

Building forward: Strategic community resilience

The need for community resilience continues to gain prominence, and is reflected in a broad array of supporting efforts including measurement methodologies, system standards, governance and policy, and significant private efforts. However, communities continue to experience gaps and struggle to foster a strategic path for the long-term sustainable community resilience. Creating resilience at the community level requires a systematic effort, which can be accomplished via the design of a cohesive and opportunity-focused toolkit for cities and regions. Application of this toolkit can then drive measurable gains in community level resilience. This paper describes how notable available community level applications can be strategically combined to implement community resilience.