Abstract. The Dynamic Data Driven Application Systems (DDDAS) concept entails the ability to incorporate dynamically data into an executing application simulation, and in reverse, the ability of applications to dynamically steer measurement processes. Such dynamic data inputs can be acquired in real-time on-line or they can be archival data. DDDAS offers the promise of improving modeling methods, augmenting the analysis and prediction capabilities of application simulations, improving the efficiency of simulations and the effectiveness of measurement systems. In the recent years grid computing technologies provide advanced computational capabilities for applications and application simulations At the same time measurement infrastructures, from instruments to sensor systems, to data storage technologies and remote data access have also matured. The DDDAS concept dynamically integrates computational and measurement aspects of an application, and in that respect the "platform" supporting the application becomes a unified computational and measurement infrastructure. Enabling the synergistic feedback and control-loop between application simulations and measurements requires novel application modeling approaches and interfaces to measurement systems, mathematical and statistical algorithms tolerant to perturbations from dynamic data inputs, and systems software to support the dynamic resource requirements of such applications. This and the rest of the papers in the proceedings of this workshop provide examples of ongoing research developing DDDAS technologies, both in terms of new capabilities in applications, measurement methods and in related systems software technologies.
REF It provides better analysis and prediction of a system through inputting big data into the simulation model in real time.
Dynamic data driven applications systems: A new paradigm for application simulations and measurements
Computational Science-ICCS 2004: 4th International Conference
Computer Science