PNNL

Abstract

Modern scientific enterprises are inherently knowledge-intensive. Scientific studies in domains such as geosciences, climate, and biology require the acquisition and manipulation of large amounts of experimental and field data to create inputs for large-scale computational simulations. The results of these simulations are then analyzed, leading to refinements of inputs and models and additional simulations. The results of this process must be managed and archived to provide justifications for regulatory decisions and publications that are based on the models. In this paper we introduce our Velo framework that is designed as a reusable, domain independent knowledge management infrastructure for modeling and simulation. Velo leverages, integrates and extends open source collaborative and content management technologies to create a scalable and flexible core platform that can be tailored to specific scientific domains. We describe the architecture of Velo for managing and associating the various types of data that are used and created in modeling and simulation projects, as well as the framework for integrating domain-specific tools. To demonstrate realizations of Velo, we describe examples from two deployed sites for carbon sequestration and climate modeling. These provide concrete example of the inherent extensibility and utility of our approach.