{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T05:08:08Z","timestamp":1755839288854,"version":"3.38.0"},"reference-count":35,"publisher":"China Science Publishing & Media Ltd.","issue":"2","license":[{"start":{"date-parts":[[2022,3,7]],"date-time":"2022-03-07T00:00:00Z","timestamp":1646611200000},"content-version":"vor","delay-in-days":65,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["direct.mit.edu"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2022,4,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>In this paper we present the derivation of Canonical Workflow Modules from current workflows in simulation-based climate science in support of the elaboration of a corresponding framework for simulation-based research. We first identified the different users and user groups in simulation-based climate science based on their reasons for using the resources provided at the German Climate Computing Center (DKRZ). What is special about this is that the DKRZ provides the climate science community with resources like high performance computing (HPC), data storage and specialised services, and hosts the World Data Center for Climate (WDCC). Therefore, users can perform their entire research workflows up to the publication of the data on the same infrastructure. Our analysis shows, that the resources are used by two primary user types: those who require the HPC-system to perform resource intensive simulations to subsequently analyse them and those who reuse, build-on and analyse existing data. We then further subdivided these top-level user categories based on their specific goals and analysed their typical, idealised workflows applied to achieve the respective project goals. We find that due to the subdivision and further granulation of the user groups, the workflows show apparent differences. Nevertheless, similar \u201cCanonical Workflow Modules\u201d can be clearly made out. These modules are \u201cData and Software (Re)use\u201d, \u201cCompute\u201d, \u201cData and Software Storing\u201d, \u201cData and Software Publication\u201d, \u201cGenerating Knowledge\u201d and in their entirety form the basis for a Canonical Workflow Framework for Research (CWFR). It is desirable that parts of the workflows in a CWFR act as FDOs, but we view this aspect critically. Also, we reflect on the question whether the derivation of Canonical Workflow modules from the analysis of current user behaviour still holds for future systems and work processes.<\/jats:p>","DOI":"10.1162\/dint_a_00127","type":"journal-article","created":{"date-parts":[[2022,3,7]],"date-time":"2022-03-07T18:06:44Z","timestamp":1646676404000},"page":"212-225","update-policy":"https:\/\/doi.org\/10.1162\/mitpressjournals.corrections.policy","source":"Crossref","is-referenced-by-count":4,"title":["Canonical Workflows in Simulation-based Climate\n                    Sciences"],"prefix":"10.3724","volume":"4","author":[{"given":"Ivonne","family":"Anders","sequence":"first","affiliation":[{"name":"German Climate Computing Center (DKRZ), Bundesstra\u00dfe 45a, D-20146 Hamburg, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Karsten Peters-von","family":"Gehlen","sequence":"additional","affiliation":[{"name":"German Climate Computing Center (DKRZ), Bundesstra\u00dfe 45a, D-20146 Hamburg, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hannes","family":"Thiemann","sequence":"additional","affiliation":[{"name":"German Climate Computing Center (DKRZ), Bundesstra\u00dfe 45a, D-20146 Hamburg, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"2026","published-online":{"date-parts":[[2022,4,1]]},"reference":[{"key":"2022042714422377600_ref1","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1007\/978-3-642-59992-7_2","article-title":"Three dimensional numerical simulation of climate: The\n                        fundamentals.","volume-title":"Anthropogenic Climate Change","author":"Washington","year":"1999"},{"volume-title":"The atmospheric general circulation model ECHAM 5","author":"Roeckner","key":"2022042714422377600_ref2"},{"issue":"687","key":"2022042714422377600_ref3","doi-asserted-by":"crossref","first-page":"563","DOI":"10.1002\/qj.2378","article-title":"The ICON (ICOsahedral Non-hydrostatic) modelling framework of\n                        DWD and MPI-M: Description of the non-hydrostatic dynamical\n                        core","volume":"141","author":"Z\u00e4ngl","year":"2015","journal-title":"Quarterly Journal of the Royal Meteorological\n                        Society"},{"issue":"9","key":"2022042714422377600_ref4","doi-asserted-by":"crossref","first-page":"3659","DOI":"10.5194\/gmd-11-3659-2018","article-title":"Requirements for a global data infrastructure in support of\n                        CMIP6","volume":"11","author":"Balaji","year":"2018","journal-title":"Geoscientific Model Development\n                        Discussions"},{"issue":"1","key":"2022042714422377600_ref5","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s40645-019-0304-z","article-title":"DYAMOND: The DYnamics of the atmospheric general circulation\n                        modeled on non-hydrostatic domains","volume":"6","author":"Stevens","year":"2019","journal-title":"Progress in\n                        Earth and Planetary Science"},{"volume-title":"Workshop: Building reproducible workflows for\n                        earth sciences","author":"ECMWF","key":"2022042714422377600_ref6"},{"issue":"1-2","key":"2022042714422377600_ref7","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1162\/dint_a_00026","article-title":"Making data and workflows findable for\n                        machines","volume":"2","author":"Weigel","year":"2020","journal-title":"Data Intelligence"},{"issue":"10","key":"2022042714422377600_ref8","doi-asserted-by":"crossref","first-page":"6225","DOI":"10.5194\/bg-10-6225-2013","article-title":"Multiple stressors of ocean ecosystems in the 21st century:\n                        Projections with CMIP5 models","volume":"10","author":"Bopp","year":"2013","journal-title":"Biogeosciences"},{"issue":"2","key":"2022042714422377600_ref9","doi-asserted-by":"crossref","first-page":"391","DOI":"10.3390\/cli3020391","article-title":"Detailed urban heat island projections for cities worldwide:\n                        Dynamical downscaling CMIP5 global climate models","volume":"3","author":"Lauwaet","year":"2015","journal-title":"Climate"},{"key":"2022042714422377600_ref10","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1016\/j.renene.2016.08.036","article-title":"Potential impacts of climate change on European wind energy\n                        resource under the CMIP5 future climate projections","volume":"101","author":"Carvalho","year":"2017","journal-title":"Renewable Energy"},{"issue":"50","key":"2022042714422377600_ref11","doi-asserted-by":"crossref","first-page":"19691","DOI":"10.1073\/pnas.0701890104","article-title":"Adapting agriculture to climate 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Storch","key":"2022042714422377600_ref14"},{"issue":"6","key":"2022042714422377600_ref15","doi-asserted-by":"crossref","first-page":"408","DOI":"10.1038\/s41561-020-0582-5","article-title":"Artificial intelligence reconstructs missing climate\n                        information","volume":"13","author":"Kadow","year":"2020","journal-title":"Nature Geoscience"},{"issue":"7743","key":"2022042714422377600_ref16","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1038\/s41586-019-0912-1","article-title":"Deep learning and process understanding for data-driven earth\n                        system science","volume":"566","author":"Reichstein","year":"2019","journal-title":"Nature"},{"key":"2022042714422377600_ref17","doi-asserted-by":"crossref","first-page":"400","DOI":"10.1016\/j.future.2013.07.002","article-title":"The earth system grid federation: An open infrastructure for\n                        access to distributed geospatial 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        transition","volume":"11","author":"Bauer","year":"2021","journal-title":"Nature Climate Change"},{"issue":"5","key":"2022042714422377600_ref21","doi-asserted-by":"crossref","first-page":"1799","DOI":"10.5194\/gmd-11-1799-2018","article-title":"Crossing the chasm: How to develop weather and climate\n                        models for next generation computers?","volume":"11","author":"Lawrence","year":"2018","journal-title":"Geoscientific Model Development"},{"volume-title":"Canonical Workflow Framework for Research (CWFR)\u2014position\n                        paper\u2014 version 2, December 2020","author":"Hardisty","key":"2022042714422377600_ref22"},{"key":"2022042714422377600_ref23","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1007\/978-3-030-23584-0_1","article-title":"FAIR principles and digital objects: Accelerating\n                        convergenceona data infrastructure.","volume-title":"Data Analytics and Management in Data Intensive 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Management"},{"issue":"1","key":"2022042714422377600_ref31","article-title":"Bringing citations and usage metrics together to make data\n                        count","volume":"18","author":"Cousijn","year":"2019","journal-title":"Data Science Journal"},{"issue":"1","key":"2022042714422377600_ref32","article-title":"The time efficiency gain in sharing and reuse of research\n                        data","volume":"18","author":"Pronk","year":"2019","journal-title":"Data Science Journal"},{"key":"2022042714422377600_ref33","doi-asserted-by":"crossref","DOI":"10.1038\/s43247-020-00085-4","article-title":"Limits of reproducibility and hydrodynamic noise in\n                        atmospheric regional modelling","volume":"2","author":"Geyer","year":"2021","journal-title":"Communications Earth\n                        & Environment"},{"key":"2022042714422377600_ref34","first-page":"895","volume-title":"Seamless management of ensemble climate prediction experiments on\n                        HPC platforms","author":"Manubens-Gil","year":"2016"},{"key":"2022042714422377600_ref35","first-page":"49","volume-title":"A case for portability and reproducibility of HPC\n                        containers","author":"Canon","year":"2019"}],"container-title":["Data Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/direct.mit.edu\/dint\/article-pdf\/4\/2\/212\/2012394\/dint_a_00127.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/direct.mit.edu\/dint\/article-pdf\/4\/2\/212\/2012394\/dint_a_00127.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,3,14]],"date-time":"2025-03-14T07:43:45Z","timestamp":1741938225000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.sciengine.com\/doi\/10.1162\/dint_a_00127"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"references-count":35,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2022,4,1]]}},"URL":"https:\/\/doi.org\/10.1162\/dint_a_00127","relation":{},"ISSN":["2641-435X"],"issn-type":[{"type":"electronic","value":"2641-435X"}],"subject":[],"published-other":{"date-parts":[[2022]]},"published":{"date-parts":[[2022]]}}}