From Data to Knowledge to Discoveries: Artificial Intelligence and Scientific Workflows

Abstract

Scientific computing has entered a new era of scale and sharing with the arrival of cyberinfrastructure facilities for computational experimentation. A key emerging concept is scientific workflows, which provide a declarative representation of complex scientific applications that can be automatically managed and executed in distributed shared resources. In the coming decades, computational experimentation will push the boundaries of current cyberinfrastructure in terms of inter-disciplinary scope and integrative models of scientific phenomena under study. This paper argues that knowledge-rich workflow environments will provide necessary capabilities for that vision by assisting scientists to validate and vet complex analysis processes and by automating important aspects of scientific exploration and discovery.