SC

Thanks to the proliferation of computational techniques and the availability of datasets, data-intensive research has become commonplace in science. Sharing and re-use of datasets is key to scientific progress. A critical requirement for enabling data ...

Data provenance is the lineage of an artifact or object. Provenance can provide a basis upon which data can be regenerated, and can be used to determine the quality of both the process and provenance itself. Provenance capture from workflows is ...

Reusing and repurposing scientific workflows for novel scientific experiments is nowadays facilitated by workflow repositories. Such repositories allow scientists to find existing workflows and re-execute them. However, workflow input parameters often ...

Dispel is a scripting language for constructing workflow graph which can then be executed by some other computational infrastructure. It facilitates construction of abstract components (called Processing Elements, or PEs) that can be instantiated in ...

An accurate performance prediction service can be very useful for resource management and the scheduler service and help them make better resource utilization decisions by providing better execution time estimates. In this paper we present a novel ...

Task characteristics estimations such as runtime, disk space, and memory consumption, are commonly used by scheduling algorithms and resource provisioning techniques to provide successful and efficient workflow executions. These methods assume that ...

Scientific workflow management is heavily used in our organization. After six years, a large number of workflows are available and regularly used to run biomedical data analysis experiments on distributed infrastructures, mostly on grids. In this paper ...

The ability to accurately predict the performance of software components executing within a Cloud environment is an area of intense interest to many researchers. The availability of an accurate prediction of the time taken for a piece of code to execute ...

Domain experts are often untrained in big data technologies and this limits their ability to exploit the data they have available. Workflow systems hide the complexities of high-end computing and software engineering by offering pre-packaged analytic ...

Dependency management remains a major challenge for all forms of software. A program implemented in a given environment typically has many implicit dependencies on programs, libraries, and other objects present within that environment. Moving ...

Workflow systems play an important role in the analysis of the fast-growing genomics data produced by low-cost next generation sequencing (NGS) technologies. Many biomedical research groups lack the expertise to assemble and run the sophisticated ...

This paper identifies the high value to researchers in many disciplines of having web-based graphical editors for scientific workflows and draws attention to two technological transitions: good quality editors can now run in a browser and workflow ...

Data analysis workflows are often composed by many concurrent and compute-intensive tasks that can be efficiently executed only on scalable computing infrastructures, such as HPC systems, Grids and Cloud platforms. The use of Cloud services for the ...