Tag: nf-core

FONDA PhD Defense: Fabian Lehmann on “Adaptive Scheduling of Dynamic Workflows”

Fabian Lehmann defended his dissertation, “Adaptive Scheduling of Dynamic Workflows” with distinction on June 29th, 2026. Fabian was a member of subproject B5 in FONDA Phase I. His work examines the tradeoff between workflow portability and efficiency, and introduces WONDERS, a best of both worlds optimization strategy for Nextflow workflows.

In order for scientific workflows to be portable, workflow management systems such as Nextflow cannot rely on hard-coded assumptions about the dataset or underlying infrastructure to improve efficiency. WONDERS utilizes the Common Workflow Scheduling Interface (CWSI), developed by Fabian, to bring workflow context to the resource manager, then combines his three novel approaches for workflow optimization: WOW, PONDER, and SCALE.

WOW is a scheduling approach which reduces network congestion within a cluster by basing scheduling decisions primarily on the co-location of tasks and data. PONDER and SCALE are tools which predict and minimize the ongoing use of memory (PONDER) and CPU (SCALE) over the course of a workflow execution. The combination of the three techniques in WONDERS results in super-additive improvements in workflow makespan (average reduction ~50% compared to nf-core default settings) when tested on a variety of Nextflow workflows using real-world data from remote sensing and bioinformatics.

Congratulations Fabian!

November 25th-26th: Workshop on reducing carbon emissions in large-scale computational data analysis

On Tuesday November 25th, in lieu of our normal Lecture Series talks, we will begin our Workshop on reducing carbon emissions in large-scale computational data analysis! The workshop will continue on Wednesday with more speakers and opportunities for discussion.

The workshop was planned in collaboration with the Quantitative Biology Center (QBiC), the bioinformatics core facility from the University of Tübingen. We have invited 14 speakers from around Europe and the UK to discuss current research into the environmental impacts of large scale scientific computing. More information, including the schedule, can be found here.

Data Aware Scheduling Method Now Available for Nextflow

With the latest release of the nf-cws Nextflow-Plugin, Fabian Lehmann and Friedrich Tschirpke introduce the WOW scheduling method as a production-ready feature. This release marks the transition of the WOW approach from a research prototype to a usable software component, fully integrated with the official Nextflow versions (v24.04.0 up to v25.02.3-edge).

Key Features:

  • WOW Scheduling for Nextflow: The Workflow-Aware data movement and task scheduling (WOW) method is now available as part of nf-cws. This enables dynamic coordination of data transfers and task execution, reducing network congestion and workflow runtime.
  • Seamless Integration: The nf-cws plugin can be used directly with Nextflow’s Kubernetes executor, requiring no experimental patches or custom setups.
  • Production Use: The improvements demonstrated in the original publication can now be leveraged by all Nextflow users in real-world scenarios.

-Fabian Lehmann

FONDA Integrated Research Training Group Courses

The Integrated Research Training Group (IRTG) has been very active in the past month providing courses and workshops for FONDA’s doctoral researchers. On April 28th and 29th Seqera, the company which supports the open source workflow engine “Nextflow” provided a tutorial using Nextflow to write and evaluate bioinformatics workflows. On May 7th, the IRTG members participated in a training course in Good Scientific Practice, especially geared towards computational sciences.

Future courses include a tutorial on GitLab with scientists from the German Aerospace Center on May 20th and 21st, a course on gender bias awareness on June 17, along with courses on workflow simulator WfCommons, and python-based workflow execution engine “Snakemake”.

FONDA contributed the first non-Bioinformatics Workflow to nf-core

We have successfully ported and contributed our Rangeland workflow [1], [2] to the nf-core workflow repository. This milestone marks the release of the first non-bioinformatics workflow on nf-core, which now serves as a blueprint for workflows in remote sensing and other domains. Being a part of the nf-core community confirms that our workflow uses best practices and ensures accessibility to researchers worldwide.


The Rangeland workflow analyzes trends in grassland changes, providing valuable insights for environmental research.

This achievement was made possible by subproject B5: Felix Kummer, Katarzyna Ewa Lewińska, Fabian Lehmann, and David Frantz.

-Fabian Lehmann