On the Fundamental Tautology of Validating Data-Driven Models and Simulations

John Michopoulos and Sam Lambrakos

Materials Science and Technology Division,U.S. Naval Research Laboratory, Washington, DC. 20375, U.S.A

Abstract. Recent advances in Dynamic Data Driven Application Systems (DDDAS) facilitated by the present level of computational technologies, as well as advances in data-driven modeling and simulation, impose the need for a critical evaluation of paradigms underlying Qualification, Validation and Verification (QV&V). This paper discusses the fundamental irrelevance of conventional validation procedures with respect to data-driven models and simulations. This inherent property of data-driven models and simulations makes the data-driven approaches extremely desirable from a reliability perspective. An informal comparison of the logical flow of traditional and evolved QV&V demonstrates the tautological nature of data-driven model validation. A brief epistemological review of the origins of traditional and evolved QV&V is also presented.

LNCS 3515, pp. 738-745.

Last modified: