Most of the large-scale scientific experiments modeled as scientific workflows produce a
large amount of data and require workflow parallelism to reduce workflow execution time …

One of the main challenges of scientific experiments is to allow scientists to manage and
exchange their scientific computational resources (data, programs, models, etc.). The …

Cloud computing is gaining tremendous momentum in both academia and industry. In this
context, we define the term “Cloud Workflow” as the specification, execution and provenance …

Scientific workflow has become a common practice for scientists to effectively formalize and
structure complex scientific processes, which in turn has accelerated scientific discoveries in …

The heterogeneity and historical complexity of interventions on built heritage are testified by
the constant development of the conservation discipline. The purpose of the research is the …

Scientific workflow has recently become an enabling technology to automate and speed up
the scientific discovery process. Although several scientific workflow management systems …

Many of the existing large‐scale scientific experiments modeled as scientific workflows are
compute‐intensive. Some scientific workflow management systems already explore parallel …

Scientific workflows are typically used to automate the processing, analysis and
management of scientific data. Most scientific workflow programs provide a user-friendly …

Scientific workflows are becoming increasingly popular for compute-intensive and data-
intensive scientific applications. The vision and promise of scientific workflows includes …

Data curation is critical for scientific data digitization, sharing, integration, and use. This
paper presents Kurator, a software package for automating data curation pipelines in the …