Toward an Ontology Framework Supporting the Integration of Geographic Information with Modeling and Simulation for Critical Infrastructure Protection
Author | : |
Publisher | : |
Total Pages | : |
Release | : 2009 |
ISBN-13 | : OCLC:727267843 |
ISBN-10 | : |
Rating | : 4/5 ( Downloads) |
Download or read book Toward an Ontology Framework Supporting the Integration of Geographic Information with Modeling and Simulation for Critical Infrastructure Protection written by and published by . This book was released on 2009 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Protecting the nation's infrastructure from natural disasters, inadvertent failures, or intentional attacks is a major national security concern. Gauging the fragility of infrastructure assets, and understanding how interdependencies across critical infrastructures affect their behavior, is essential to predicting and mitigating cascading failures, as well as to planning for response and recovery. Modeling and simulation (M & S) is an indispensable part of characterizing this complex system of systems and anticipating its response to disruptions. Bringing together the necessary components to perform such analyses produces a wide-ranging and coarse-grained computational workflow that must be integrated with other analysis workflow elements. There are many points in both types of work flows in which geographic information (GI) services are required. The GIS community recognizes the essential contribution of GI in this problem domain as evidenced by past OGC initiatives. Typically such initiatives focus on the broader aspects of GI analysis workflows, leaving concepts crucial to integrating simulations within analysis workflows to that community. Our experience with large-scale modeling of interdependent critical infrastructures, and our recent participation in a DRS initiative concerning interoperability for this M & S domain, has led to high-level ontological concepts that we have begun to assemble into an architecture that spans both computational and 'world' views of the problem, and further recognizes the special requirements of simulations that go beyond common workflow ontologies. In this paper we present these ideas, and offer a high-level ontological framework that includes key geospatial concepts as special cases of a broader view.