Towards Advancing Research with Workflows: A perspective from the Workflows Community Summit -- Amsterdam, 2025

2026-02-04

AI Summary

This work addresses key challenges impeding the adoption of scientific workflows, including tensions between generality and domain specificity, insufficient sustainability, lack of recognition for contributions, inadequate standardization, and limited funding and interdisciplinary collaboration. Building on consensus from the 2025 Amsterdam Workflow Community Summit, the project proposes an integrated roadmap spanning technology, policy, and community engagement. It advocates shifting evaluation criteria from computational performance to scientific impact, establishing community-driven workflow patterns and benchmarks, and creating dedicated workflow engineer roles embedded within academic training programs. The outcomes include a reproducibility framework, cross-platform collaboration mechanisms, and standardized methodologies, collectively enhancing the transparency, usability, and long-term sustainability of scientific workflows.

Technology Category

• Application Domains: Humanities & Computational Social Science
• Planning, Routing, and Scheduling: Activity and Plan Recognition
• Humans and AI: Planning and Decision Support for Human-Machine Teams

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Data management and stream processing for Web, mobile and wireless applications
• Responsible Web: Algorithmic accountability and transparency on the web
• Security and Privacy: Data transparency and provenance

Abstract

Scientific workflows have become essential for orchestrating complex computational processes across distributed resources, managing large datasets, and ensuring reproducibility in modern research. The Workflows Community Summit 2025, held in Amsterdam on June 6th, 2025, convened international experts to examine emerging challenges and opportunities in this domain. Participants identified key barriers to workflow adoption, including tensions between system generality and domain-specific utility, concerns over long-term sustainability of workflow systems and services, insufficient recognition for those who develop and maintain reproducible workflows, and gaps in standardization, funding, training, and cross-disciplinary collaboration. To address these challenges, the summit proposed action lines spanning technology, policy, and community dimensions: shifting evaluation metrics from raw computational performance toward measuring genuine scientific impact; formalizing workflow patterns and community-driven benchmarks to improve transparency, reproducibility, and usability; cultivating a cohesive international workflows community that engages funding bodies and research stakeholders; and investing in human capital through dedicated workflow engineering roles, career pathways, and integration of workflow concepts into educational curricula and long-term training initiatives. This document presents the summit's findings, beginning with an overview of the current computing ecosystem and the rationale for workflow-centric approaches, followed by a discussion of identified challenges and recommended action lines for advancing scientific discovery through workflows.

Problem

• scientific workflows
• reproducibility
• sustainability
• standardization
• cross-disciplinary collaboration

Innovation

• scientific workflows
• reproducibility
• community-driven benchmarks
• workflow engineering
• scientific impact