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4 Publications visible to you, out of a total of 4
A terminology for scientific workflow systems

Abstract (Expand)

The term “scientific workflow” has evolved over the last two decades to encompass a broad range of compositions of interdependent compute tasks and data movements. It has also become an umbrella term … for processing in modern scientific applications. Today, many scientific applications can be considered as workflows made of multiple dependent steps, and hundreds of workflow systems have been developed to manage and run these scientific workflows. However, no turnkey solution has emerged from the field to address the diversity of scientific processes and the infrastructure on which they are supposed to be implemented. Instead, new research problems requiring the execution of scientific workflows with some novel feature often lead to the development of an entirely new workflow system. A direct consequence of this situation is that many existing workflow management systems (WMSs) share some salient features, offer similar functionalities, and can manage the same categories of workflows but at the same time also have some distinct capabilities that can be important for specific applications. This situation makes researchers who develop workflows face the complex question of selecting a WMS. This selection can be driven by technical considerations, to find the system that is the most appropriate for their application and for the computing and storage resources available to them, or other factors such as reputation, adoption, strong community support, or long-term sustainability. To address this problem, a group of WMS developers and practitioners joined their efforts to produce a community-based terminology of WMSs. This paper summarizes their findings and introduces this new terminology to characterize WMSs. This terminology is composed of fives axes: workflow structure and characteristics, composition, orchestration, data management, and metadata capture. Each axis comprises several concepts that capture the prominent features of WMSs. Based on this terminology, this paper also presents a classification of 23 existing WMSs according to the proposed axes and terms.

Authors: Frédéric Suter, Tainã Coleman, İlkay Altintaş, Rosa M. Badia, Bartosz Balis, Kyle Chard, Iacopo Colonnelli, Ewa Deelman, Paolo Di Tommaso, Thomas Fahringer, Carole Goble, Shantenu Jha, Daniel S. Katz, Johannes Köster, Ulf Leser, Kshitij Mehta, Hilary Oliver, J.-Luc Peterson, Giovanni Pizzi, Loïc Pottier, Raül Sirvent, Eric Suchyta, Douglas Thain, Sean R. Wilkinson, Justin M. Wozniak, Rafael Ferreira da Silva

Date Published: 2026

Publication Type: Journal

An Ecosystem of Services for FAIR Computational Workflows

Abstract (Expand)

Computational workflows, regardless of their portability or maturity, represent major investments of both effort and expertise. They are first class, publishable research objects in their own right. … They are key to sharing methodological know-how for reuse, reproducibility, and transparency. Consequently, the application of the FAIR principles to workflows [goble_2019, wilkinson_2025] is inevitable to enable them to be Findable, Accessible, Interoperable, and Reusable. Making workflows FAIR would reduce duplication of effort, assist in the reuse of best practice approaches and community-supported standards, and ensure that workflows as digital objects can support reproducible and robust science. FAIR workflows also encourage interdisciplinary collaboration, enabling workflows developed in one field to be repurposed and adapted for use in other research domains. FAIR workflows draw from both FAIR data [wilkinson_2016] and software [barker_2022] principles. Workflows propose explicit method abstractions and tight bindings to data, hence making many of the data principles apply. Meanwhile, as executable pipelines with a strong emphasis on code composition and data flow between steps, the software principles apply, too. As workflows are chiefly concerned with the processing and creation of data, they also have an important role to play in ensuring and supporting data FAIRification. The FAIR Principles for software and data mandate the use of persistent identifiers (PID) and machine actionable metadata associated with workflows to enable findability, reusability, interoperability and reusability. To implement the principles requires a PID and metadata framework with appropriate programmatic protocols, an accompanying ecosystem of services, tools, guidelines, policies, and best practices, as well the buy-in of existing workflow systems such that they adapt in order to adopt. The European EOSC-Life Workflow Collaboratory is an example of such a digital infrastructure for the Biosciences: it includes a metadata standards framework for describing workflows (i.e. RO-Crate, Bioschemas, and CWL), that is managed and used by dedicated new FAIR workflow services and programmatic APIs for interoperability and metadata access such as those proposed by the Global Alliance for Genomics and Health (GA4GH) [rehm_2021]. The WorkflowHub registry supports workflow Findability and Accessibility, while workflow testing services like LifeMonitor support long-term Reusability, Usability and Reproducibility. Existing workflow management systems/languages and packaging solutions are incorporated and adapted to promote portability, composability, interoperability, provenance collection and reusability, and to use and support these FAIR services. In this chapter, we will introduce the FAIR principles for workflows, the connections between FAIR workflows, and the FAIR ecosystems in which they live, using the EOSC-Life Collaboratory as a concrete example. We will also introduce other community efforts that are easing the ways that workflows are shared and reused by others, and we will discuss how the variations in different workflow settings impact their FAIR perspective.

Authors: Sean R. Wilkinson, Johan Gustafsson, Finn Bacall, Khalid Belhajjame, Salvador Capella, José María Fernández González, Jacob Fosso Tande, Luiz Gadelha, Daniel Garijo, Patricia Grubel, Björn Grüning, Farah Zaib Khan, Sehrish Kanwal, Simone Leo, Stuart Owen, Luca Pireddu, Line Pouchard, Laura Rodriguez-Navas, Beatriz Serrano-Solano, Stian Soiland-Reyes, Baiba Vilne, Alan Williams, Merridee Ann Wouters, Frederik Coppens, Carole Goble

Date Published: 21st May 2025

Publication Type: InBook

Applying the FAIR Principles to computational workflows

Abstract

Not specified

Authors: Sean R. Wilkinson, Meznah Aloqalaa, Khalid Belhajjame, Michael R. Crusoe, Bruno de Paula Kinoshita, Luiz Gadelha, Daniel Garijo, Ove Johan Ragnar Gustafsson, Nick Juty, Sehrish Kanwal, Farah Zaib Khan, Johannes Köster, Karsten Peters-von Gehlen, Line Pouchard, Randy K. Rannow, Stian Soiland-Reyes, Nicola Soranzo, Shoaib Sufi, Ziheng Sun, Baiba Vilne, Merridee A. Wouters, Denis Yuen, Carole Goble

Date Published: 1st Dec 2025

Publication Type: Journal

WorkflowHub: a registry for computational workflows

Abstract (Expand)

The rising popularity of computational workflows is driven by the need for repetitive and scalable data processing, sharing of processing know-how, and transparent methods. As both combined records of … analysis and descriptions of processing steps, workflows should be reproducible, reusable, adaptable, and available. Workflow sharing presents opportunities to reduce unnecessary reinvention, promote reuse, increase access to best practice analyses for non-experts, and increase productivity. In reality, workflows are scattered and difficult to find, in part due to the diversity of available workflow engines and ecosystems, and because workflow sharing is not yet part of research practice. WorkflowHub provides a unified registry for all computational workflows that links to community repositories, and supports both the workflow lifecycle and making workflows findable, accessible, interoperable, and reusable (FAIR). By interoperating with diverse platforms, services, and external registries, WorkflowHub adds value by supporting workflow sharing, explicitly assigning credit, enhancing FAIRness, and promoting workflows as scholarly artefacts. The registry has a global reach, with hundreds of research organisations involved, and more than 800 workflows registered.

Authors: Ove Johan Ragnar Gustafsson, Sean R. Wilkinson, Finn Bacall, Stian Soiland-Reyes, Simone Leo, Luca Pireddu, Stuart Owen, Nick Juty, José M. Fernández, Tom Brown, Hervé Ménager, Björn Grüning, Salvador Capella-Gutierrez, Frederik Coppens, Carole Goble

Date Published: 1st Dec 2025

Publication Type: Journal

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