Until not long ago, manually capturing and storing provenance from scientific experiments
were constant concerns for scientists. With the advent of computational experiments …

We propose noWorkflow, a tool that transparently captures provenance of scripts and
enables reproducibility. Unlike existing approaches, noWorkflow is non-intrusive and does …

In scientific collaboration, data sharing, the exchange of ideas and results are essential to
knowledge construction and the development of science. Hence, we must guarantee …

This chapter outlines some of the challenges and opportunities associated with adopting
provenance principles (Cheney et al., Dagstuhl Reports 2 (2): 84–113, 2012) and standards …

Workflow is a well-established means by which to capture scientific methods in an abstract
graph of interrelated processing tasks. The reproducibility of scientific workflows is therefore …

Gait is emerging as a powerful tool to detect early disease and monitor progression across a
number of pathologies. Typically quantitative gait assessment has been limited to …

Transparency optimized state convergence scheme is a simple, elegant and easy to design
bilateral control algorithm for nth-order linear teleoperation systems modeled on state space …

Cloud computing has become a major approach to help reproduce computational
experiments. Yet there are still two main difficulties in reproducing batch based Big Data …

Accurate and comprehensive storage of provenance information is a basic requirement for
modern scientific computing. A significant effort in recent years has developed robust …

In the scientist's community one of the most vital challenges is the issue of reproducibility of
workflow execution. In order to reproduce the results of an experiment, on one hand …