III: Medium: Provenance Analytics: Exploring Computational Tasks and their History

点击翻译按钮获取中文摘要

"This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5)."This proposal will address the provenance of computational processes and the data they manipulate. These are of fundamental importance in maintaining scientific process. Provenance (also referred to as audit trail, lineage, and pedigree) captures information about the steps used to generate a given data product. Such information provides documentation that is key to preserving the data and determining the data's quality and authorship as well as interpreting, reproducing, sharing and publishing results. It also seeks to produce algorithms and techniques for extracting and reusing useful knowledge embedded in workflow specifications. Workflows and workflow-based systems have proven to be successful in capturing computational tasks at various levels of detail and automatically record provenance information. They have recently emerged as an alternative to ad-hoc approaches to assembling computational tasks that are widely used in the scientific community. In order to effectively use provenance information and to deal with a potential information overload, we need novel tools and techniques that help users. The ability to explore the knowledge available in the provenance of computational tasks has the potential to foster large-scale collaborations, expedite scientific training in disciplinary and inter-disciplinary settings, as well as to reduce the lag time between data acquisition and scientific insight.