Stuart Owen

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About Stuart Owen:

No description specified

SEEK ID: https://workflowhub.eu/people/5

Location: United Kingdom

ORCID: https://orcid.org/0000-0003-2130-0865

Joined: 7th Apr 2020

Expertise: Not specified

Tools: Not specified

Their tags

bioimaging ISMB poster

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Independent Teams

A space managed by WorkflowHub administrators for teams that don't want/need to manage their own space.

Teams: IBISBA Workflows, NMR Workflow, UNLOCK, NanoGalaxy, Galaxy Climate, PNDB, IMBforge, COVID-19 PubSeq: Public SARS-CoV-2 Sequence Resource, LBI-RUD, Nick-test-team, usegalaxy-eu, Italy-Covid-data-Portal, UX trial team, Integrated and Urban Plant Pathology Laboratory, SARS-CoV-2 Data Hubs, lmjxteam2, virAnnot pipeline, Ay Lab, iPC: individualizedPaediatricCure, Harkany Lab, Genomics Coordination Center, EJPRD WP13 case-studies workflows, Common Workflow Language (CWL) community, Testing, SeBiMER, IAA-CSIC, MAB - ATGC, Probabilistic graphical models, GenX, Snakemake-Workflows, ODA, IPK BIT, CO2MICS Lab, FAME, CHU Limoges - UF9481 Bioinformatique / CNR Herpesvirus, Quadram Institute Bioscience - Bioinformatics, HecatombDevelopment, Institute of Human Genetics, Testing RO Crates, Test Team, Applied Computational Biology at IEG/HMGU, INFRAFRONTIER workflows, OME, TransBioNet, OpenEBench, Galaxycompchem, Bioinformatics and Biostatistics (BIO2 ) Core, VIB Bioinformatics Core, CRC Cohort, ICAN, MustafaVoh, Single Cell Unit, CO-Graph, emo-bon, TestEMBL-EBIOntology, CINECA, Toxicology community, Pitagora-Network, Workflows Australia, Medizinisches Proteom-Center, Medical Bioinformatics, AGRF BIO, EU-Openscreen, X-omics, ELIXIR Belgium, URGI, Size Inc, GA-VirReport Team, The Boucher Lab, Air Quality Prediction, pyiron, CAPSID, Edinburgh Genomics, Defragmentation TS, NBIS, Phytoplankton Analysis, Seq4AMR, Workflow registry test, Read2Map, SKM3, ParslRNA-Seq: an efficient and scalable RNAseq analysis workflow for studies of differentiated gene expression, de.NBI Cloud, Meta-NanoSim, ILVO Plant Health, EMERGEN-BIOINFO, KircherLab, Apis-wings, BCCM_ULC, Dessimoz Lab, TRON gGmbH, GEMS at MLZ, Computational Science at HZDR, Big data in biomedicine, TRE-FX, MISTIC, Guigó lab, Statistical genetics, Delineating Regions-of-interest for Mass Spectrometry Imaging by Multimodally Corroborated Spatial Segmentation, WES, Bioinformatics Unit @ CRG, Bioinformatics Innovation Lab, BSC-CES, ELIXIR Proteomics, Black Ochre Data Labs, Zavolan Lab, Metabolomics-Reproducibility, Team Cardio, NGFF Tools, Bioinformatics workflows for life science, Workflows for geographic science, Pacific-deep-sea-sponges-microbiome, CSFG, SNAKE, Katdetectr, INFRAFRONTIER GmbH, PerMedCoE, EuroScienceGateway, Euro-BioImaging, EOSC-Life WP3 OC Team, cross RI project, ANSES-Ploufragan, SANBI Pathogen Bioinformatics, Biodata Analysis Group, DeSci Labs, Erasmus MC - Viroscience Bioinformatics, ARA-dev, Mendel Centre for Plant Genomics and Proteomics, Metagenomic tools, WorkflowEng, Polygenic Score Catalog, bpm, scNTImpute, Systems Biotechnology laboratory, Cimorgh IT solutions, MLme: Machine Learning Made Easy, Hurwitz Lab

Web page: Not specified

COVID-19 Biohackathon

The goal of COVID-19-Biohackathon 2020 (COVID-19-BH20) is to develop and gather computational tools that can be useful for studying the biology of the virus and the disease.

The COVID-19 Programme in Workflow Hub aims to gather workflows for the analysis of COVID-19 molecular biology data and their metadata. In this programme, all workflows and their metadata will be curated and made interoperable, reusable and reproducible. All workflows and their metadata will be easily accessible to everyone ...

Teams: Connor Lab, GalaxyProject SARS-CoV-2, InSaFLU, nf-core viralrecon, CWL workflow SARS-CoV-2, V-Pipe, Test team

Web page: https://github.com/virtual-biohackathons/covid-19-bh20

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GalaxyProject SARS-CoV-2

Ongoing analysis of COVID-19 using Galaxy, BioConda and public research infrastructures https://covid19.galaxyproject.org

Space: COVID-19 Biohackathon

Public web page: https://github.com/galaxyproject/SARS-CoV-2

Organisms: Homo sapiens, SARS-CoV-2

IBISBA Workflows

Workflows from the Industrial Biotechnology Innovation and Synthetic Biology Accelerator (IBISBA 1.0) project, which is funded by the European Union Horizon 2020 program INRAIA-02 under grant agreement 730976.

The workflows also appear on https://hub.ibisba.eu

Space: Independent Teams

Public web page: https://www.ibisba.eu

Organisms: Homo sapiens, SARS-CoV-2

Defragmentation TS

No description specified

Space: Independent Teams

Public web page: Not specified

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The University of Manchester

Country: United Kingdom

City: Manchester

Web page: https://ror.org/027m9bs27

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Ten simple rules for making a software tool workflow-ready

Specimen Data Refinery, FAIR Computational Workflows

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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 …

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

DOI: 10.1371/journal.pcbi.1009823

Citation: PLoS Comput Biol 18(3):e1009823

Created: 25th Apr 2022 at 11:43, Last updated: 16th Jan 2023 at 13:34

Views: 665, Downloads: 0

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

Specimen Data Refinery, FAIR Computational Workflows

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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

DOI: 10.1162/dint_a_00134

Citation: Data Intelligence:1-19

Created: 25th Apr 2022 at 11:45, Last updated: 16th Jan 2023 at 13:34

Views: 593, Downloads: 0

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