The field of scientific workflow management systems has grown significantly as applications
start using them successfully. In 2007, several active researchers in scientific workflow …

In this survey, we discuss the challenges of executing scientific workflows as well as existing
Machine Learning (ML) techniques to alleviate those challenges. We provide the context …

Scientific workflows are commonly used to model and execute large-scale scientific
experiments. They represent key resources for scientists and are enacted and managed by …

We present an algorithm and a software architecture for a cloud-based system that executes
cyclic scientific workflows whose structure may change during run time. Existing approaches …

Computer simulations consume and produce huge amounts of raw data files presented in
different formats, eg, HDF5 in computational fluid dynamics simulations. Users often need to …

In 2006 a group of leading researchers was gathered to discuss several challenges to
scientific workflow supporting technologies and many of which still remain open challenges …

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

Dynamic workflows are scientific workflows to support computational science simulations,
typically using dynamic processes based on runtime scientific data analyses. They require …

WorkWays is a science gateway that supports human‐in‐the‐loop scientific workflows.
Human–workflow interactions are enabled by a dynamic Input Output (IO) model, which …

Scientific workflows need to be iteratively, and often interactively, executed for large input
datasets. Reducing data from input datasets is a powerful way to reduce overall execution …