Publications

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59 Publications visible to you, out of a total of 59
Recording provenance of workflow runs with RO-Crate

Abstract (Expand)

Recording the provenance of scientific computation results is key to the support of traceability, reproducibility and quality assessment of data products. Several data models have been explored to … address this need, providing representations of workflow plans and their executions as well as means of packaging the resulting information for archiving and sharing. However, existing approaches tend to lack interoperable adoption across workflow management systems. In this work we present Workflow Run RO-Crate, an extension of RO-Crate (Research Object Crate) and Schema.org to capture the provenance of the execution of computational workflows at different levels of granularity and bundle together all their associated objects (inputs, outputs, code, etc.). The model is supported by a diverse, open community that runs regular meetings, discussing development, maintenance and adoption aspects. Workflow Run RO-Crate is already implemented by several workflow management systems, allowing interoperable comparisons between workflow runs from heterogeneous systems. We describe the model, its alignment to standards such as W3C PROV, and its implementation in six workflow systems. Finally, we illustrate the application of Workflow Run RO-Crate in two use cases of machine learning in the digital image analysis domain.

Authors: Simone Leo, Michael R. Crusoe, Laura Rodríguez-Navas, Raül Sirvent, Alexander Kanitz, Paul De Geest, Rudolf Wittner, Luca Pireddu, Daniel Garijo, José M. Fernández, Iacopo Colonnelli, Matej Gallo, Tazro Ohta, Hirotaka Suetake, Salvador Capella-Gutierrez, Renske de Wit, Bruno P. Kinoshita, Stian Soiland-Reyes

Date Published: 10th Sep 2024

Publication Type: Journal

Scaling Scientific Workflows in Europe: Architecture and Deployment of the Galaxy-Pulsar Computational Network

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Description This preprint outlines the development and deployment of the European Pulsar Network (EPN)—a federated, scalable architecture enabling distributed job execution across national and European …opean Galaxy instances. Built within the Horizon Europe EuroScienceGateway project, the EPN leverages the Galaxy workflow system and the Pulsar job execution service to offload computational workloads to remote endpoints seamlessly and securely. The work introduces an Open Infrastructure (OI) framework that automates provisioning, deployment, and monitoring using Terraform, Ansible, and Jenkins. The pre-print highlights deployments across thirteen Pulsar nodes and six national Galaxy portals, illustrating how the EPN supports reproducible, FAIR-aligned data analysis while abstracting infrastructure complexity for researchers.

Authors: Marco Antonio Tangaro, Stefano Nicotri, Björn Grüning, Sanjay Kumar Srikakulam, Armin Dadras, Oana Kaiser, Mira Kuntz, Anthony Bretaudeau, Paul De Geest, Sebastian Luna-Valero, María Chavero Díez, José María Fernández González, Salvador Capella-Gutierrez, Josep Lluís Gelpí, Jan Astalos, Boris Jurič, Miroslav Ruda, Łukasz Opioła, Hakan Bayındır, SILVIA GIOIOSA, Gaetanomaria De Sanctis, Federico Zambelli

Date Published: 7th Aug 2025

Publication Type: Unpublished

survInTime - Exploring surveillance methods and data analysis on Brazilian respiratory syndrome dataset and community mobility changes

Abstract (Expand)

Background The covid-19 pandemic brought negative impacts in almost every country in the world. These impacts were observed mainly in the public health sphere, with a rapid raise and spread of the … disease and failed attempts to restrain it while there was no treatment. However, in developing countries, the impacts were severe in other aspects such as the intensification of social inequality, poverty and food insecurity. Specifically in Brazil, the miscommunication among the government layers conducted the control measures to a complete chaos in a country of continental dimensions. Brazil made an effort to register granular informative data about the case reports and their outcomes, while this data is available and can be consumed freely, there are issues concerning the integrity and inconsistencies between the real number of cases and the number of notifications in this dataset. Results We projected and implemented four types of analysis to explore the Brazilian public dataset of Severe Acute Respiratory Syndrome (srag dataset) notifications and the google dataset of community mobility change (mobility dataset). These analysis provides some diagnosis of data integration issues and strategies to integrate data and experimentation of surveillance analysis. The first type of analysis aims at describing and exploring the data contained in both datasets, starting by assessing the data quality concerning missing data, then summarizing the patterns found in this datasets. The Second type concerns an statistical experiment to estimate the cases from mobility patterns organized in periods of time. We also developed, as the third analysis type, an algorithm to help the understanding of the disease waves by detecting them and compare the time periods across the cities. Lastly, we build time series datasets considering deaths, overall cases and residential mobility change in regular time periods and used as features to group cities with similar behavior. Conclusion The exploratory data analysis showed the under representation of covid-19 cases in many small cities in Brazil that were absent in the srag dataset or with a number of cases very low than real projections. We also assessed the availability of data for the Brazilian cities in the mobility dataset in each state, finding out that not all the states were represented and the best coverage occurred in Rio de Janeiro state. We compared the capacity of place categories mobility change combination on estimating the number of cases measuring the errors and identifying the best components in mobility that could affect the cases. In order to target specific strategies for groups of cities, we compared strategies to cluster cities that obtained similar outcomes behavior along the time, highlighting the divergence on handling the disease.

Authors: Yasmmin Côrtes Martins, Ronaldo Francisco da Silva

Date Published: 27th Sep 2023

Publication Type: Journal

Ten simple rules and a template for creating workflows-as-applications

Abstract

Not specified

Authors: Michael J. Roach, N. Tessa Pierce-Ward, Radoslaw Suchecki, Vijini Mallawaarachchi, Bhavya Papudeshi, Scott A. Handley, C. Titus Brown, Nathan S. Watson-Haigh, Robert A. Edwards

Date Published: 15th Dec 2022

Publication Type: Journal

Ten simple rules for making a software tool workflow-ready

Abstract (Expand)

Workflows have become a core part of computational scientific analysis in recent years. Automated computational workflows multiply the power of researchers, potentially turning “hand-cranked” data …data processing by informaticians into robust factories for complex research output. However, in order for a piece of software to be usable as a workflow-ready tool, it may require alteration from its likely origin as a standalone tool. Research software is often created in response to the need to answer a research question with the minimum expenditure of time and money in resource-constrained projects. The level of quality might range from “it works on my computer” to mature and robust projects with support across multiple operating systems. Despite significant increase in uptake of workflow tools, there is little specific guidance for writing software intended to slot in as a tool within a workflow; or on converting an existing standalone research-quality software tool into a reusable, composable, well-behaved citizen within a larger workflow. In this paper we present 10 simple rules for how a software tool can be prepared for workflow use.

Authors: Paul Brack, Peter Crowther, Stian Soiland-Reyes, Stuart Owen, Douglas Lowe, Alan R. Williams, Quentin Groom, Mathias Dillen, Frederik Coppens, Björn Grüning, Ignacio Eguinoa, Philip Ewels, Carole Goble

Date Published: 24th Mar 2022

Publication Type: Journal

The impact of non-lineage defining mutations in the structural stability for variants of concern of SARS-CoV-2

Abstract (Expand)

Motivation The identification of the most important mutations, that lead to a structural and functional change in a highly transmissible virus variants, is essential to understand the impacts and the … possible chances of vaccine and antibody escape. Strategies to rapidly associate mutations to functional and conformational properties are needed to rapidly analyze mutations in proteins and their impacts in antibodies and human binding proteins. Results Comparative analysis showed the main structural characteristics of the essential mutations found for each variant of concern in relation to the reference proteins. The paper presented a series of methodologies to track and associate conformational changes and the impacts promoted by the mutations.

Authors: Yasmmin Martins, Ronaldo Francisco da Silva

Date Published: 22nd Jun 2023

Publication Type: Journal

The Specimen Data Refinery: A Canonical Workflow Framework and FAIR Digital Object Approach to Speeding up Digital Mobilisation of Natural History Collections

Abstract (Expand)

A key limiting factor in organising and using information from physical specimens curated in natural science collections is making that information computable, with institutional digitization tending … to focus more on imaging the specimens themselves than on efficiently capturing computable data about them. Label data are traditionally manually transcribed today with high cost and low throughput, rendering such a task constrained for many collection-holding institutions at current funding levels. We show how computer vision, optical character recognition, handwriting recognition, named entity recognition and language translation technologies can be implemented into canonical workflow component libraries with findable, accessible, interoperable, and reusable (FAIR) characteristics. These libraries are being developed in a cloud- based workflow platform—the ‘Specimen Data Refinery’ (SDR)—founded on Galaxy workflow engine, Common Workflow Language, Research Object Crates (RO-Crate) and WorkflowHub technologies. The SDR can be applied to specimens’ labels and other artefacts, offering the prospect of greatly accelerated and more accurate data capture in computable form. Two kinds of FAIR Digital Objects (FDO) are created by packaging outputs of SDR workflows and workflow components as digital objects with metadata, a persistent identifier, and a specific type definition. The first kind of FDO are computable Digital Specimen (DS) objects that can be consumed/produced by workflows, and other applications. A single DS is the input data structure submitted to a workflow that is modified by each workflow component in turn to produce a refined DS at the end. The Specimen Data Refinery provides a library of such components that can be used individually, or in series. To cofunction, each library component describes the fields it requires from the DS and the fields it will in turn populate or enrich. The second kind of FDO, RO-Crates gather and archive the diverse set of digital and real-world resources, configurations, and actions (the provenance) contributing to a unit of research work, allowing that work to be faithfully recorded and reproduced. Here we describe the Specimen Data Refinery with its motivating requirements, focusing on what is essential in the creation of canonical workflow component libraries and its conformance with the requirements of an emerging FDO Core Specification being developed by the FDO Forum.

Authors: Alex Hardisty, Paul Brack, Carole Goble, Laurence Livermore, Ben Scott, Quentin Groom, Stuart Owen, Stian Soiland-Reyes

Date Published: 7th Mar 2022

Publication Type: Journal

Towards consistently measuring and monitoring habitat condition with airborne laser scanning and unmanned aerial vehicles

Abstract (Expand)

Indicators of habitat condition are essential for tracking conservation progress, but measuring biotic, abiotic and landscape characteristics at fine resolution over large spatial extents remains … challenging. In this viewpoint article, we provide a comprehensive synthesis of the challenges and solutions for consistently measuring and monitoring habitat condition with remote sensing using airborne Light Detection and Ranging (LiDAR) and affordable Unmanned Aerial Vehicles (UAVs) over multiple sites and transnational or continental extents. Key challenges include variability in sensor characteristics and survey designs, non-transparent pre-processing workflows, heterogeneous and complex data, issues with the robustness of metrics and indices, limited model generalizability and transferability across sites, and difficulties in handling big data, such as managing large volumes and utilizing parallel or distributed computing. We suggest that a collaborative cloud virtual research environment (VRE) for habitat condition research and monitoring could provide solutions, including tools for data discovery, access, and data standardization, as well as geospatial processing workflows for airborne LiDAR and UAV data. A VRE would also improve data management, metadata standardization, workflow reproducibility, and transferability of structure-from-motion algorithms and machine learning models such as random forests and convolutional neural networks. Along with best practices for data collection and adopting FAIR (findability, accessibility, interoperability, reusability) principles and open science practices, a VRE could enable more consistent and transparent data processing and metric retrieval, e.g., for Natura 2000 habitats. Ultimately, these improvements would support the development of more reliable habitat condition indicators, helping prevent habitat degradation and promoting the sustainable use of natural resources.

Authors: W. Daniel Kissling, Yifang Shi, Jinhu Wang, Agata Walicka, Charles George, Jesper E. Moeslund, France Gerard

Date Published: 1st Dec 2024

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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