High Consequence Systems and Semantic Computing

Abstract

Socioeconomic needs combined with technological advances are creating a demand for an increasing number of systems for which high-assurance is an essential attribute. These system designs, which increasingly include semantic computing components, span a broad spectrum of applications. They are incredibly diverse and their complexity is growing. The conditions under which these systems operate are such that system faults will occur and must be comprehensively accounted for in the systems' designs.This article investigates the landscape of high-assurance systems, the challenges these systems face, and what must be done to address those challenges. Challenges include societal needs, scienti¯c frontiers, dynamics of technological evolution, and drivers of current research models.gathering Google Chairman Eric Schmidt said``We need to set out an agenda for innovation for our country as a whole" [14].In the book Engines of Innovation it is argued that research universities must step up and play a more central role in tackling``the world's biggest problems" [63]. The core of such innovation often rests on the successful leveraging of computer and information technology within the context of a larger system. We postulate that, in the years to come, semantic computing will provide an essential fulcrum in many such systems. Independent of the underlying technologies employed, the implications of technological dependence are enormous: In their 2010 report, the President's Council of Advisors on Science and Technology (PCAST) stated that Networking and Information Technology (NIT)``underpins our national prosperity, health, and security". It should not be surprising then that the new millennium has seen a distinct shift of academic missions in the direction of interdisciplinary and applied use of computer technology in a shift which is often referred to as translational science.It is the context of leveraging computer technology to solve``the world's biggest problems" that has led innovators to envision and develop a wide range of highconsequence systems. A classical de¯nition of a high-consequence system is a system in which a high``cost" (or consequence) is associated with failure. Here the cost metric is not limited to the monetary axis, but can range across any axis of social value such as human life, or national security. From this de¯nition, it can be argued that the terms``world's biggest problems" and``high-consequence problems" are practically synonymous. The corollary to this argument is that one can then expect solutions to the world's biggest problems to be realized though innovative highconsequence systems. It is worth noting that these system designs are extremely diverse: they include autonomous decentralized control systems such as the system used to control Japan's bullet train, marine renewable energy systems such as those being developed o® the Florida coast, medical systems permitting the sharing of clinical guidelines and synthesis of clinical work°ows and protocols, supervisory control and acquisition (...

Creating Model with System Breakdown Structure for System Dynamics

“…At the beginning, system dynamics was introduced by Jay Forrester in 1961 [8] and continued evolving and growing significantly in understanding and resolving some of the problems in some fields of science such as economic, environmental, management, and so on. The system is evaluated from the simple one into the complex one [9] which needs more advance techniques to analyze [10].…”