The extraction of useful information from data is often a complex process that can be
conveniently modeled as a data analysis workflow. When very large data sets must be …

Since digital data repositories are more and more massive and distributed, we need smart
data analysis techniques and scalable architectures to extract useful information from them …

Workflows are an effective paradigm to model complex data analysis processes, such as
knowledge discovery in databases applications, which can be efficiently executed on …

The conventional technologies and methods are not able to store and analyse recent data
that come from different sources: various devices, sensors, networks, transactional …

This paper presents an open cloud based platform for composition, execution, and sharing
of interactive data mining workflows. It is based on the principles of service-oriented …

Computing clouds have become the platform of choice for the deployment and execution of
scientific workflows. Due to the uncertainty and unpredictability of scientific exploration, the …

The paper presents a platform for distributed computing, developed using the latest software
technologies and computing paradigms to enable big data mining. The platform, called …

Computational science workflows have been successfully run on traditional HPC systems
like clusters and Grids for many years. Today, users are interested to execute their workflow …

A workflow models a process as consisting of a series of steps that simplifies the complexity
of execution and management of applications. Scientific workflows in domains such as high …

The huge amount of data generated, the speed at which it is produced, and its heterogeneity
in terms of format, represent a challenge to the current storage, process and analysis …