ELIXIR-STEERS M3.3 Use cases for benchmarking workflows identified

In the framework of ELIXIR-STEERS, task 3.3 aims to extend the OpenEBench community-led evaluation feature. This extension will enable the technical benchmarking of workflows used for common analyses in the Life Sciences domain based on reference datasets. For that purpose, from the ELIXIR-STEERS Task 3.3 perspective, a software has been developed to obtain a set of technical metrics. Such metrics should enable the assessment of efficiency and environmental impact of software executions. This software is the Execution Metrics Collector, which gathers low-level technical metrics from Linux processes, which are then used to derive high-level indicators, including computational carbon footprint estimations. The Technical Metrics live document describes the low and high-level community-led metrics. The identification of use cases for benchmarking workflows has been carried out in collaboration with ELIXIR-STEERS WP2, several ELIXIR Communities and other relevant Life Sciences communities, and is presented in Milestone 3.3 report. From the use cases identified, we will obtain low- and high-level metrics that will enable assessing the workflow executions' carbon footprint impact. We will connect those workflows with popular managers systems like Galaxy to gather usage. Altogether will provide us with valuable information about reproducibility and the reuse of workflows by the different scientific communities in ELIXIR and, potentially, beyond.

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-04-30
DOI
https://doi.org/10.5281/zenodo.15363545
Primary Topic
Scientific Computing and Data Management
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

ELIXIR-STEERS M3.3 Use cases for benchmarking workflows identified

Zenodo (CERN European Organization for Nuclear Research)
Scientific Computing and Data Management
article

ELIXIR-STEERS M3.3 Use cases for benchmarking workflows identified

article en

Abstract

In the framework of ELIXIR-STEERS, task 3.3 aims to extend the OpenEBench community-led evaluation feature. This extension will enable the technical benchmarking of workflows used for common analyses in the Life Sciences domain based on reference datasets. For that purpose, from the ELIXIR-STEERS Task 3.3 perspective, a software has been developed to obtain a set of technical metrics. Such metrics should enable the assessment of efficiency and environmental impact of software executions. This software is the Execution Metrics Collector, which gathers low-level technical metrics from Linux processes, which are then used to derive high-level indicators, including computational carbon footprint estimations. The Technical Metrics live document describes the low and high-level community-led metrics. The identification of use cases for benchmarking workflows has been carried out in collaboration with ELIXIR-STEERS WP2, several ELIXIR Communities and other relevant Life Sciences communities, and is presented in Milestone 3.3 report. From the use cases identified, we will obtain low- and high-level metrics that will enable assessing the workflow executions' carbon footprint impact. We will connect those workflows with popular managers systems like Galaxy to gather usage. Altogether will provide us with valuable information about reproducibility and the reuse of workflows by the different scientific communities in ELIXIR and, potentially, beyond.

Zenodo (CERN European Organization for Nuclear Research)
University of Padua (IT), University of Freiburg (DE), University of Southern Denmark (DK), Barcelona Supercomputing Center (ES), Národný ústav detských chorôb (SK), Centro Nacional de Biotecnología (ES), Institut Français de Bioinformatique (FR), OLS, Weizmann Institute of Science (IL), Universitat Politècnica de Catalunya (ES)
Responsible consumption and production
Openalex Percentile: Top 56%
Scientific Computing and Data Management
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.