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CERN Analysis Preservation and Reuse Framework: FAIR research data services for LHC experiments

In this paper we present the CERN Analysis Preservation service as a FAIR (Findable, Accessible, Interoperable and Reusable) research data preservation repository platform for LHC experiments. The CERN Analysis Preservation repository allows LHC collaborations to deposit and share the structured inf...

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Detalles Bibliográficos
Autores principales: Fokianos, Pamfilos, Feger, Sebastian, Koutsakis, Ilias, Lavasa, Artemis, Maciulaitis, Rokas, Naim, Kamran, Okraska, Jan, Papadopoulos, Antonios, Rodríguez, Diego, Šimko, Tibor, Trzcinska, Anna, Tsanaktsidis, Ioannis, van de Sandt, Stephanie
Lenguaje:eng
Publicado: 2020
Materias:
Acceso en línea:https://dx.doi.org/10.1051/epjconf/202024506011
http://cds.cern.ch/record/2752852
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author Fokianos, Pamfilos
Feger, Sebastian
Koutsakis, Ilias
Lavasa, Artemis
Maciulaitis, Rokas
Naim, Kamran
Okraska, Jan
Papadopoulos, Antonios
Rodríguez, Diego
Šimko, Tibor
Trzcinska, Anna
Tsanaktsidis, Ioannis
van de Sandt, Stephanie
author_facet Fokianos, Pamfilos
Feger, Sebastian
Koutsakis, Ilias
Lavasa, Artemis
Maciulaitis, Rokas
Naim, Kamran
Okraska, Jan
Papadopoulos, Antonios
Rodríguez, Diego
Šimko, Tibor
Trzcinska, Anna
Tsanaktsidis, Ioannis
van de Sandt, Stephanie
author_sort Fokianos, Pamfilos
collection CERN
description In this paper we present the CERN Analysis Preservation service as a FAIR (Findable, Accessible, Interoperable and Reusable) research data preservation repository platform for LHC experiments. The CERN Analysis Preservation repository allows LHC collaborations to deposit and share the structured information about analyses as well as to capture the individual data assets associated to the analysis. We describe the typical data ingestion pipelines, through which an individual physicist can preserve and share their final n-tuples, ROOT macros, Jupyter notebooks, or even their full analysis workflow code and any intermediate datasets of interest for preservation within the restricted context of experimental collaboration. We discuss the importance of annotating the deposited content with high-level structured information about physics concepts in order to promote information discovery and knowledge sharing inside the collaboration. Finally, we describe techniques used to facilitate the reusability of preserved data assets by capturing and re-executing reproducible recipes and computational workflows using the REANA Reusable Analysis platform.
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institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2020
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spelling oai-inspirehep.net-18321852021-03-01T20:16:23Zdoi:10.1051/epjconf/202024506011http://cds.cern.ch/record/2752852engFokianos, PamfilosFeger, SebastianKoutsakis, IliasLavasa, ArtemisMaciulaitis, RokasNaim, KamranOkraska, JanPapadopoulos, AntoniosRodríguez, DiegoŠimko, TiborTrzcinska, AnnaTsanaktsidis, Ioannisvan de Sandt, StephanieCERN Analysis Preservation and Reuse Framework: FAIR research data services for LHC experimentsComputing and ComputersIn this paper we present the CERN Analysis Preservation service as a FAIR (Findable, Accessible, Interoperable and Reusable) research data preservation repository platform for LHC experiments. The CERN Analysis Preservation repository allows LHC collaborations to deposit and share the structured information about analyses as well as to capture the individual data assets associated to the analysis. We describe the typical data ingestion pipelines, through which an individual physicist can preserve and share their final n-tuples, ROOT macros, Jupyter notebooks, or even their full analysis workflow code and any intermediate datasets of interest for preservation within the restricted context of experimental collaboration. We discuss the importance of annotating the deposited content with high-level structured information about physics concepts in order to promote information discovery and knowledge sharing inside the collaboration. Finally, we describe techniques used to facilitate the reusability of preserved data assets by capturing and re-executing reproducible recipes and computational workflows using the REANA Reusable Analysis platform.oai:inspirehep.net:18321852020
spellingShingle Computing and Computers
Fokianos, Pamfilos
Feger, Sebastian
Koutsakis, Ilias
Lavasa, Artemis
Maciulaitis, Rokas
Naim, Kamran
Okraska, Jan
Papadopoulos, Antonios
Rodríguez, Diego
Šimko, Tibor
Trzcinska, Anna
Tsanaktsidis, Ioannis
van de Sandt, Stephanie
CERN Analysis Preservation and Reuse Framework: FAIR research data services for LHC experiments
title CERN Analysis Preservation and Reuse Framework: FAIR research data services for LHC experiments
title_full CERN Analysis Preservation and Reuse Framework: FAIR research data services for LHC experiments
title_fullStr CERN Analysis Preservation and Reuse Framework: FAIR research data services for LHC experiments
title_full_unstemmed CERN Analysis Preservation and Reuse Framework: FAIR research data services for LHC experiments
title_short CERN Analysis Preservation and Reuse Framework: FAIR research data services for LHC experiments
title_sort cern analysis preservation and reuse framework: fair research data services for lhc experiments
topic Computing and Computers
url https://dx.doi.org/10.1051/epjconf/202024506011
http://cds.cern.ch/record/2752852
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