Journal article  Open Access

A workflow language for research e-infrastructures

Candela L., Grossi V., Manghi P., Trasarti R.

HyWare  Workflow languages  Scientific workflows  Open Science 

Research e-infrastructures are "systems of systems," patchworks of resources such as tools and services, which change over time to address the evolving needs of the scientific process. In such environments, researchers carry out their scientific process in terms of sequences of actions that mainly include invocation of web services, user interaction with web applications, user download and use of shared software libraries/tools. The resulting workflows are intended to generate new research products (articles, datasets, methods, etc.) out of existing ones. Sharing a digital and executable representation of such workflows with other scientists would enforce Open Science publishing principles of "reproducibility of science" and "transparent assessment of science." This work presents HyWare, a language and execution platform capable of representing scientific processes in highly heterogeneous research e-infrastructures in terms of so-called hybrid workflows. Hybrid workflows can express sequences of "manually executable actions," i.e., formal descriptions guiding users to repeat a reasoning, protocol or manual procedure, and "machine-executable actions," i.e., encoding of the automated execution of one (or more) web services. An HyWare execution platform enables scientists to (i) create and share workflows out of a given action set (as defined by the users to match e-infrastructure needs) and (ii) execute hybrid workflows making sure input/output of the actions flow properly across manual and automated actions. The HyWare language and platform can be implemented as an extension of well-known workflow languages and platforms.

Source: International Journal of Data Science and Analytics (Online) (2021). doi:10.1007/s41060-020-00237-x

Publisher: Springer

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BibTeX entry
	title = {A workflow language for research e-infrastructures},
	author = {Candela L. and Grossi V. and Manghi P. and Trasarti R.},
	publisher = {Springer},
	doi = {10.1007/s41060-020-00237-x},
	journal = {International Journal of Data Science and Analytics (Online)},
	year = {2021}