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author= {Crusoe, Michael R. and Abeln, Sanne and Iosup, Alexandru and Amstutz, Peter and Chilton, John and Tijani\'{c}, Neboj\^{s}a and M\'{e}nager, Herv\'{e} and Soiland-Reyes, Stian and Gavrilovi\'{c}, Bogdan and Goble, Carole and the CWL Community},
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title= {Methods Included: Standardizing Computational Reuse and Portability with the Common Workflow Language},
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journaltitle= {Communications of the ACM},
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shortjournal= {Commun. ACM},
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issn= {0001-0782, 1557-7317},
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volume= {65},
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number= {6},
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pages= {54--63},
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year= {2022},
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month= jun,
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doi= {10.1145/3486897},
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note= {Published May 20, 2022 (Issue June 2022)}
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author= {Crusoe, Michael R. and Abeln, Sanne and Iosup, Alexandru and Amstutz, Peter and Chilton, John and Tijani\'{c}, Neboj\^{s}a and M\'{e}nager, Herv\'{e} and Soiland-Reyes, Stian and Gavrilovi\'{c}, Bogdan and Goble, Carole and the CWL Community},
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title= {Methods Included: Standardizing Computational Reuse and Portability with the Common Workflow Language},
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journaltitle= {Communications of the ACM},
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shortjournal= {Commun. ACM},
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issn= {0001-0782, 1557-7317},
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volume= {65},
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number= {6},
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pages= {54--63},
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year= {2022},
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month= jun,
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doi= {10.1145/3486897},
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note= {Published May 20, 2022 (Issue June 2022)}
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}
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@article{Ewert2023Proposal,
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title= {{{FAIRagro}} - {{A FAIR Data Infrastructure}} for {{Agrosystems}} (Proposal)},
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author= {Ewert, Frank and Specka, Xenia and Anderson, James M. and Arend, Daniel and Asseng, Senthold and Boehm, Franziska and Feike, Til and Fluck, Juliane and Gackstetter, David and Gonzales-Mellado, Aida and Hartmann, Thomas and Haunert, Jan-Henrik and Hoedt, Florian and Hoffmann, Carsten and König, Patrick and Lesch, Stephan and Lindstädt, Birte and Lischeid, Gunnar and Martini, Daniel and Möller, Markus and Rascher, Uwe and Reif, Jochen and Senft, Matthias and Stahl, Ulrike and Svoboda, Nikolai and Usadel, Björn and Webber, Heidi and Weiland, Claus},
abstract= {This document is the proposal for the consortium FAIRagro in the framework of the National Research Data Infrastructure (NFDI) in Germany. The proposal was submitted to the German Research Foundation (DFG) in Nov 2021. The proposal was finally accepted~ with a revised working program~in Feb 2023. All financial resources (personnel, material, direct project costs, in-kind contributions) were removed from the public version.n},
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langid= {english},
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keywords= {agrosystems,NFDI,research data infrastructures,research data management},
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title= {{{FAIRagro}} - {{A FAIR Data Infrastructure}} for {{Agrosystems}} (Proposal)},
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author= {Ewert, Frank and Specka, Xenia and Anderson, James M. and Arend, Daniel and Asseng, Senthold and Boehm, Franziska and Feike, Til and Fluck, Juliane and Gackstetter, David and Gonzales-Mellado, Aida and Hartmann, Thomas and Haunert, Jan-Henrik and Hoedt, Florian and Hoffmann, Carsten and K\"{o}nig, Patrick and Lesch, Stephan and Lindst\"{a}dt, Birte and Lischeid, Gunnar and Martini, Daniel and M\"{o}ller, Markus and Rascher, Uwe and Reif, Jochen and Senft, Matthias and Stahl, Ulrike and Svoboda, Nikolai and Usadel, Bj\"{o}rn and Webber, Heidi and Weiland, Claus},
abstract= {This document is the proposal for the consortium FAIRagro in the framework of the National Research Data Infrastructure (NFDI) in Germany. The proposal was submitted to the German Research Foundation (DFG) in Nov 2021. The proposal was finally accepted~ with a revised working program~in Feb 2023. All financial resources (personnel, material, direct project costs, in-kind contributions) were removed from the public version.n},
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langid= {english},
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keywords= {agrosystems,NFDI,research data infrastructures,research data management}
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}
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@article{Simko2019Reana,
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title= {{{REANA}}: {{A System}} for {{Reusable Research Data Analyses}}},
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shorttitle= {{{REANA}}},
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author= {Šimko, Tibor and Heinrich, Lukas and Hirvonsalo, Harri and Kousidis, Dinos and Rodríguez, Diego},
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editor= {Forti, A. and Betev, L. and Litmaath, M. and Smirnova, O. and Hristov, P.},
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date= {2019},
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journaltitle= {EPJ Web of Conferences},
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shortjournal= {EPJ Web Conf.},
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volume= {214},
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pages= {06034},
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publisher= {EDP Sciences},
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issn= {2100-014X},
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doi= {10.1051/epjconf/201921406034},
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urldate= {2025-07-07},
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abstract = {The revalidation, reinterpretation and reuse of research data analyses requires having access to the original computing environment, the experimental datasets, the analysis software, and the computational workflow steps which were used by researchers to produce the original scientific results in the first place.REANA (Reusable Analyses) is a nascent platform enabling researchers to structure their research data analyses in view of enabling future reuse. The analysis is described by means of a YAML file that captures sufficient information about the analysis assets, parameters and processes. The REANA platform consists of a set of micro-services allowing to launch and monitor container-based computational workflow jobs on the cloud. The REANA user interface and the command-line client enables researchers to easily rerun analysis workflows with new input parameters. The REANA platform aims at supporting several container technologies (Docker), workflow engines (CWL, Yadage), shared storage systems (Ceph, EOS) and compute cloud infrastructures (Ku-bernetes/OpenStack, HTCondor) used by the community.REANA was developed with the particle physics use case in mind and profits from synergies with general reusable research data analysis patterns in other scientific disciplines, such as bioinformatics and life sciences.},
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title= {{{REANA}}: {{A System}} for {{Reusable Research Data Analyses}}},
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shorttitle= {{REANA}},
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author= {\v{S}imko, Tibor and Heinrich, Lukas and Hirvonsalo, Harri and Kousidis, Dinos and Rodr\'{\i}guez, Diego},
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editor= {Forti, A. and Betev, L. and Litmaath, M. and Smirnova, O. and Hristov, P.},
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date= {2019},
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journaltitle= {EPJ Web of Conferences},
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shortjournal= {EPJ Web Conf.},
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volume= {214},
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pages= {06034},
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publisher= {EDP Sciences},
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issn= {2100-014X},
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doi= {10.1051/epjconf/201921406034},
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urldate= {2025-07-07},
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abstract = {The revalidation, reinterpretation and reuse of research data analyses requires having access to the original computing environment, the experimental datasets, the analysis software, and the computational workflow steps which were used by researchers to produce the original scientific results in the first place.REANA (Reusable Analyses) is a nascent platform enabling researchers to structure their research data analyses in view of enabling future reuse. The analysis is described by means of a YAML file that captures sufficient information about the analysis assets, parameters and processes. The REANA platform consists of a set of micro-services allowing to launch and monitor container-based computational workflow jobs on the cloud. The REANA user interface and the command-line client enables researchers to easily rerun analysis workflows with new input parameters. The REANA platform aims at supporting several container technologies (Docker), workflow engines (CWL, Yadage), shared storage systems (Ceph, EOS) and compute cloud infrastructures (Ku-bernetes/OpenStack, HTCondor) used by the community.REANA was developed with the particle physics use case in mind and profits from synergies with general reusable research data analysis patterns in other scientific disciplines, such as bioinformatics and life sciences.}
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}
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@article{SoilandReyes2022ROCrate,
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title = {Packaging Research Artefacts with {{RO-Crate}}},
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author = {Soiland-Reyes, Stian and Sefton, Peter and Crosas, Mercè and Castro, Leyla Jael and Coppens, Frederik and Fernández, José M. and Garijo, Daniel and Grüning, Björn and La Rosa, Marco and Leo, Simone and Ó Carragáin, Eoghan and Portier, Marc and Trisovic, Ana and {RO-Crate Community} and Groth, Paul and Goble, Carole},
title = {Packaging Research Artefacts with {{RO-Crate}}},
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author = {Soiland-Reyes, Stian and Sefton, Peter and Crosas, Merc\`{e} and Castro, Leyla Jael and Coppens, Frederik and Fern\'{a}ndez, Jos\'{e} M. and Garijo, Daniel and Gr\"{u}ning, Bj\"{o}rn and La Rosa, Marco and Leo, Simone and \'{O} Carrag\'{a}in, Eoghan and Portier, Marc and Trisovic, Ana and {RO-Crate Community} and Groth, Paul and Goble, Carole},
title = {Recording Provenance of Workflow Runs with {{RO-Crate}}},
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author = {Leo, Simone and Crusoe, Michael R. and Rodríguez-Navas, Laura and Sirvent, Raül and Kanitz, Alexander and Geest, Paul De and Wittner, Rudolf and Pireddu, Luca and Garijo, Daniel and Fernández, José M. and Colonnelli, Iacopo and Gallo, Matej and Ohta, Tazro and Suetake, Hirotaka and Capella-Gutierrez, Salvador and family=Wit, given=Renske, prefix=de, useprefix=false and Kinoshita, Bruno P. and Soiland-Reyes, Stian},
abstract = {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.},
title = {Recording Provenance of Workflow Runs with {{RO-Crate}}},
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author = {Leo, Simone and Crusoe, Michael R. and Rodr\'{\i}guez-Navas, Laura and Sirvent, Ra\"{u}l and Kanitz, Alexander and Geest, Paul De and Wittner, Rudolf and Pireddu, Luca and Garijo, Daniel and Fern\'{a}ndez, Jos\'{e} M. and Colonnelli, Iacopo and Gallo, Matej and Ohta, Tazro and Suetake, Hirotaka and Capella-Gutierrez, Salvador and family=Wit, given=Renske, prefix=de, useprefix=false and Kinoshita, Bruno P. and Soiland-Reyes, Stian},
abstract = {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.},
title = {{{PLANTdataHUB}}: A Collaborative Platform for Continuous {{FAIR}} Data Sharing in Plant Research},
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shorttitle = {{PLANTdataHUB}},
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author = {Weil, Heinrich Lukas and Schneider, Kevin and Tsch\"{o}pe, Marcel and Bauer, Jonathan and Maus, Oliver and Frey, Kevin and Brilhaus, Dominik and Martins Rodrigues, Cristina and Doniparthi, Gajendra and Wetzels, Florian and Lukasczyk, Jonas and Kranz, Angela and Gr\"{u}ning, Bj\"{o}rn and Zimmer, David and De\ss{}loch, Stefan and family=Suchodoletz, given=Dirk, prefix=von, useprefix=true and Usadel, Bj\"{o}rn and Garth, Christoph and M\"{u}hlhaus, Timo},
abstract = {In modern reproducible, hypothesis-driven plant research, scientists are increasingly relying on research data management (RDM) services and infrastructures to streamline the processes of collecting, processing, sharing, and archiving research data. FAIR (i.e., findable, accessible, interoperable, and reusable) research data play a pivotal role in enabling the integration of interdisciplinary knowledge and facilitating the comparison and synthesis of a wide range of analytical findings. The PLANTdataHUB offers a solution that realizes RDM of scientific (meta)data as evolving collections of files in a directory – yielding FAIR digital objects called ARCs – with tools that enable scientists to plan, communicate, collaborate, publish, and reuse data on the same platform while gaining continuous quality control insights. The centralized platform is scalable from personal use to global communities and provides advanced federation capabilities for institutions that prefer to host their own satellite instances. This approach borrows many concepts from software development and adapts them to fit the challenges of the field of modern plant science undergoing digital transformation. The PLANTdataHUB supports researchers in each stage of a scientific project with adaptable continuous quality control insights, from the early planning phase to data publication. The central live instance of PLANTdataHUB is accessible at (https://git.nfdi4plants.org), and it will continue to evolve as a community-driven and dynamic resource that serves the needs of contemporary plant science.},
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langid = {english},
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keywords = {ARC Annotated research context,ARC Annotated Research Context,DataHUB,FAIR,FAIR digital object,research data management}
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}
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@software{dataplant2025ARCSpec,
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title = {Nfdi4plants/{{ARC-specification}}: {{Annotated Research Context Specification}} v3.0-Draft.2},
abstract = {Annotated Research Context Specification version 3.0.0-draft.2 This draft release mainly bundles changes which further align the experimental provencance (ISA) with the computational provencance (CWL). For this, isa.run.xlsx and isa.workflow.xlsx files were specified which follow the structural conventions of the ISA-XLSX specification, but describe computational entities stemming from the CWL context. It includes the specification of the ISA-XLSX format at the same version and is marked as draft to allow bundling subsequent breaking changes into a single major release (3.x) ARC Specification changes Add isa.run.xlsx to run folder by \@HLWeil in https://github.com/nfdi4plants/ARC-specification/pull/157 Add isa.workflow.xlsx to workflow folder by \@HLWeil in https://github.com/nfdi4plants/ARC-specification/pull/159 Allow datamap only as own file by \@HLWeil in https://github.com/nfdi4plants/ARC-specification/pull/142 ISA-XLSX Specification changes NEW RUN Section Define RUN section and RUN file by \@HLWeil in https://github.com/nfdi4plants/ARC-specification/pull/157 NEW WORKFLOW Section Define WORKFLOW section and WORKFLOW file by \@HLWeil in https://github.com/nfdi4plants/ARC-specification/pull/159 STUDY Section Datamap may no longer be a worksheet in the isa.study.xlsx file by \@HLWeil in https://github.com/nfdi4plants/ARC-specification/pull/142 ASSAY Section Datamap may no longer be a worksheet in the isa.assay.xlsx file by \@HLWeil in https://github.com/nfdi4plants/ARC-specification/pull/142 Assay section now has new properties Identifier, Title and Description by \@HLWeil in https://github.com/nfdi4plants/ARC-specification/pull/154 DATAMAP Section Added Label column by \@HLWeil in https://github.com/nfdi4plants/ARC-specification/pull/155 Other Fixed dead link to specification file from readme by \@floWetzels in https://github.com/nfdi4plants/ARC-specification/pull/148 Changes for v3.0-draft.2 - Workflow and Run ISA integration by \@HLWeil in https://github.com/nfdi4plants/ARC-specification/pull/162 Full Changelog: https://github.com/nfdi4plants/ARC-specification/compare/3.0.0-draft.1...3.0.0-draft.2},
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organization = {Zenodo},
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version = {3.0.0-draft.2},
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keywords = {annotated research context,FAIR,FAIR data,metadata,RDM,research data management}
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