The great variety and intrinsic complexity of current Big Data technologies hampers the
development of analytic processes for large data sets in domains where their business …

Workflow is a common term used to describe a systematic breakdown of tasks that need to
be performed to solve a problem. This concept has found best use in scientific and business …

Data analysis applications have become essential to extract significant insight from
heterogeneous data sources. However, their development requires technical expertise in …

The big data era is here, a natural result of the digital revolution of the last few decades. The
emergence of big data in virtually all areas of life raises a fundamental question-how can we …

Big Data processing, especially with the increasing proliferation of Internet of Things (IoT)
technologies and convergence of IoT, edge and cloud computing technologies, involves …

This paper discusses technical aspects of how business workflow management systems can
be improved in order to apply them in the field of scientific workflows and reap all their …

Interest in processing big data has increased rapidly to gain insights that can transform
businesses, government policies, and research outcomes. This has led to advancement in …

Workflow technology is rapidly evolving and, rather than being limited to modeling the
control flow in business processes, is becoming a key mechanism to perform advanced data …

Big Data analytics in science and industry are performed on a range of heterogeneous data
stores, both traditional and modern, and on a diversity of query engines. Workflows are …

Electronic Commerce (EC) is a rapidly growing research and development area of very high
practical relevance. A major challenge in successfully designing EC applications is to …