Supporting large-scale science with workflows

Abstract

Current workflow systems support data flow through complex analyses in a distributed environment. The scope of scientific workflow systems could expand to support the entire scientific research cycle, which includes data flow, design flow, and knowledge flow tasks. Example tasks and requirements within each of these are explored, illustrated by a use case in environmental science. Nexus points between scientific tasks and potential workflow support mechanisms are identified and described. Several new ideas, or modifications of existing ideas are introduced: science dashboards, meta-provenance, event-driven workflows, extreme workflow development, and collective thinking workflows.