Nowadays, more and more computer-based scientific experiments need to handle massive
amounts of data. Their data processing consists of multiple computational steps and …

Analyzing biological data (eg, annotating genomes, assembling NGS data...) may involve
very complex and interlinked steps where several tools are combined together. Scientific …

Large-scale, data-intensive scientific applications are often expressed as scientific
workflows (SWfs). In this paper, we consider the problem of efficient scheduling of a large …

Process mining serves for gaining insights into business process behavior based on event
logs. These techniques are typically limited to addressing data included in the log. Recent …

Several scientists have moved their IO-and CPU-intensive workflows to Data-Intensive
Scalable Computing (DISC) frameworks aiming at benefit from high scalability, broad …

Methods and apparatus are provided for analytical processing of provenance data for High
Performance Computing workflow optimization. Prediction models for a workflow composed …

With their globally distributed datacenters, clouds now provide an opportunity to run complex
large-scale applications on dynamically provisioned, networked and federated …

Nowadays, more and more scientific experiments need to handle massive amounts of data.
Their data processing consists of multiple computational steps and dependencies within …

Scientific workflows allow scientists to conduct experiments that manipulate data with
multiple computational activities using Scientific Workflow Management Systems (SWfMSs) …

Abstract Recently, some Scientific Workflow Management Systems (SWfMSs) with
provenance support (eg Chiron) have been deployed in the cloud. However, they typically …