RAPID: Automating Emergency Data and Metadata Management to Support Effective Short Term and Long Term Disaster Recovery Efforts

Georgia Tech Research Corporation, Atlanta GA

Investigators

Abstract

Proposal #: CNS 11-38666 PI(s): Pu, Calton Institution: Georgia Institute of Technology Title: RAPID: Automating Emergency Data and Metadata Management to Support Effective Short and Long Term Disaster Recovery Efforts Project Proposed: This RAPID project, collecting, processing, and disseminating appropriate sensor data, aims to contribute to an effective recovery. The work addresses the challenges of sensor data flood during an emergency, through integration, evaluation, and enhancement of current data management tools, particularly with respect to meta-data. Automation of data and meta-data collection, processing, and dissemination are expected to alleviate the time pressure on human operators. The fundamental tools support quality information dimensions such as provenance, timeliness, security, privacy, and confidentiality, enabling an appropriate interpretation of the sensor data in the long term. For the short term, the tools are expected to help relief the workers as data producers and consumers; for the long term, they will provide high quality information for disaster recovery decision support systems. Additionally, the cloud-based system architecture and implementation of the CERCS cluster of Open Cirrus provide high availability and ease of access for recovery efforts in Japan as well as for researchers worldwide. The integration of techniques from several information dimensions (e.g., data provenance, surety, and privacy) and the application of code generation techniques to automate the data and metadata management tools constitute the intellectual merit of the proposed research. New challenges will be encountered in the potential interferences among the quality of information dimensions. It is also a new challenge to apply code generation techniques in the adaptation of software tools to accommodate changes imposed by environmental damages and contextual as well as cultural differences among countries. The investigator collaborates with Prof. Masaru Kitsuregawa from the University of Tokyo, Japan, a leading researcher in data management. He is the first database researcher from Asia to win the ACM SOGMOD Innovation Award (2009). In addition to a letter of support and biographical sketches of the Japanese collaborator, a support letter has been submitted by Intel to OISE, CISE and Engineering. Intel has offered access to the Intel Open Cirrus cluster to conduct the research. Broader Impacts: The proposed tools should contribute to improve both the quantity and quality of data being collected by a variety of sensors, thus improving the effectiveness of short and long term decision making. For example, measured radiation levels in agricultural products can serve as an indication of spreading radioactive contaminations that complement the direct readings of radiation in soil samples. The project enables informed decisions based on precise interpretation of real sensor data that may improve the quality of life at both human and social levels, while reducing costs. The project will also contribute in graduate student education.