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Engineering for Resilience in the Era of Big Data Workshop

Monday, September 19, 2016

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Engineering for Resilience in the Era of Big Data: November 16, 2016

Purpose

This workshop will present the formulation for resilience of urban infrastructure systems, and will present steps for the analysis of multidimensional urban infrastructure networks using some advances in data science.

Objectives

The workshop will provide: a) a review and the theoretical background of the Big Data paradigm with relation to resilience engineering, b) an introduction to the process and methods of the Big Data paradigm, c) an examination of the major steps for implementing the Big Data paradigm in resilience engineering, highlighting the importance of visualization, d) uses of the advances in the Big Data paradigm in resilience engineering, e) a presentation of some successful applications of Big Data in resilience engineering, and f) finally, a discussion of knowledge gaps, research needs and some future applications.

Background

Resilience engineering is a new paradigm for complex system performance and maintenance decision-making. The initial definition of resilience is that it deter-mines the persistence of relationships within systems, and it measures the ability of these systems to persist while absorbing change of state variables, driving variables, and parameters. Critical infrastructure data collection using highly sophisticated sensors and other equipment has led to a "Big Data" situation in terms of both the understanding and analysis of the information collected. Gi-ven the unprecedented amount of data that will be collected and stored in the future, one of urban infrastructures' greatest challenges is how to benefit from this Big Data phenomenon. In addition, as the amount of data collected grows exponentially, current algorithms are not efficient or scalable enough to deal with such large volumes of data. This has dictated new methods for the formu-lation, analysis, and interpretation of resilience indices for effective maintenance decisions. The characteristics of the data, including nature and size, redefine the analytical approaches that the emerging discipline of resilience engineering has been using. Therefore, the formulation, analysis, and interpretation (including visualization) of the urban infrastructure and other critical infrastructure must be revisited. The tools and approaches needed to mine, analyze, and visualize data at extreme scales can be fully realized only if we use end-to-end solutions, which demand collective efforts between data scientists and engineers. The massive amount of data has already offered new opportunities in supporting a wide range of standalone critical infrastructure. For example, the use of deep learning and topological data analysis, data streaming methods and tensor decomposition has been shown to present a great opportunity in the resilience engineering research.

Registration

Deadline November 2,  2016
Limited Seating Available

Venue

Bechtel Conference Center
American Society of Civil Engineers
1801 Alexander Bell Drive
Reston, VA 20191
T: 703.295.6200
Complimentary Parking Available

Organizers and Contacts

Professor Nii Attoh-Okine
University of Delaware
okine@udel.edu

Professor Bilal M. Ayyub
University of Maryland, College Park
ba@umd.edu

Supporters