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Scalable Declarative HEP Analysis Workflows for Containerised Compute Clouds
/ Šimko, Tibor (CERN) ; Heinrich, Lukas Alexander (CERN) ; Lange, Clemens (CERN) ; Lintuluoto, Adelina Eleonora (CERN ; Helsinki U.) ; MacDonell, Danika Marina (Victoria U.) ; Mečionis, Audrius (CERN) ; Rodríguez Rodríguez, Diego (CERN) ; Shandilya, Parth (CERN ; LNM Inst. Info. Tech.) ; Vidal García, Marco (CERN)
We describe a novel approach for experimental High-Energy Physics (HEP) data analyses that is centred around the declarative rather than imperative paradigm when describing analysis computational tasks. The analysis process can be structured in the form of a Directed Acyclic Graph (DAG), where each graph vertex represents a unit of computation with its inputs and outputs, and the graph edges describe the interconnection of various computational steps. [...]
2021 - 12 p.
- Published in : 10.3389/fdata.2021.661501
Fulltext: PDF;
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CERN Analysis Preservation and Reuse Framework: FAIR research data services for LHC experiments
/ Fokianos, Pamfilos (CERN) ; Feger, Sebastian (CERN) ; Koutsakis, Ilias (CERN) ; Lavasa, Artemis (CERN) ; Maciulaitis, Rokas (CERN) ; Naim, Kamran (CERN) ; Okraska, Jan (CERN) ; Papadopoulos, Antonios (CERN) ; Rodríguez, Diego (CERN) ; Šimko, Tibor (CERN) et al.
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. [...]
2020 - 9 p.
- Published in : EPJ Web Conf. 245 (2020) 06011
Fulltext: PDF;
In : 24th International Conference on Computing in High Energy and Nuclear Physics, Adelaide, Australia, 4 - 8 Nov 2019, pp.06011
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Support for HTCondor high-throughput computing workflows in the REANA reusable analysis platform
/ Maciulaitis, Rokas (Ministere des affaires etrangeres et europeennes (FR)) ; Brener, Paul (University of Notre Dame (US)) ; Hampton, Scott (University of Notre Dame (US)) ; Hildreth, Mike (University of Notre Dame (US)) ; Hurtado Anampa, Kenyi Paolo (University of Notre Dame (US)) ; Johnson, Irena (University of Notre Dame (US)) ; Kankel, Cody (University of Notre Dame (US)) ; Okraska, Jan (University of Warsaw (PL)) ; Rodriguez Rodriguez, Diego (CERN) ; Simko, Tibor (CERN)
REANA is a reusable and reproducible data analysis platform allowing researchers to structure their analysis pipelines and run them on remote containerised compute clouds. REANA supports several different workflows systems (CWL, Serial, Yadage) and uses Kubernetes’ job execution backend. [...]
CERN-IT-2019-004.-
Geneva : CERN, 2019 - 2 p.
Fulltext: PDF;
In : 15th eScience IEEE International Conference, San Diego, United States, 24 - 27 Sep 2019, pp.eScience
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Support for HTCondor High-Throughput Computing Workflows in the REANA Reusable Analysis Platform
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Beyond repositories: enabling actionable FAIR open data reuse services in particle physics
/ Rodriguez Rodriguez, Diego (CERN) ; Simko, Tibor (CERN) ; Dallmeier-Tiessen, Sunje (CERN) ; Feger, Sebastian Stefan (Universitaet Stuttgart (DE)) ; Fokianos, Pamfilos (CERN) ; Kousidis, Konstantinos ; Lavasa, Artemis (CERN) ; Maciulaitis, Rokas (Ministere des affaires etrangeres et europeennes (FR)) ; Okraska, Jan (University of Warsaw (PL)) ; Trzcinska, Anna (CERN) et al.
We describe experiences from building and operating the CERN Open Data repository platform that manages and disseminates more than one petabyte of open data from particle physics. We discuss the education and research use cases of the platform and we argue that in order to make the FAIR open data fully actionable and reusable by a variety of users, the research data repositories should evolve from focusing on resource-hosting present towards integrated service-provisioning future. [...]
IT-TALK-2019-002.-
Geneva : CERN, 2019
Slides: PDF;
In : Open Repositories 2019, Hamburg, Hamburg, Germany, 10 - 14 Jun 2019
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7.
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Open is not enough
/ Chen, Xiaoli (CERN ; Sheffield U.) ; Dallmeier-Tiessen, Sünje (CERN) ; Dasler, Robin (CERN) ; Feger, Sebastian (CERN ; Stuttgart U.) ; Fokianos, Pamfilos (CERN) ; Gonzalez, Jose Benito (CERN) ; Hirvonsalo, Harri (CERN ; Helsinki Inst. of Phys.) ; Kousidis, Dinos (CERN) ; Lavasa, Artemis (CERN) ; Mele, Salvatore (CERN) et al.
The solutions adopted by the high-energy physics community to foster reproducible research are examples of best practices that could be embraced more widely. This first experience suggests that reproducibility requires going beyond openness..
2019 - 7 p.
- Published in : Nature Phys. 15 (2019) 113-119
Fulltext from Publisher: PDF;
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8.
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Publisher Correction: Open is not enough
/ Chen, Xiaoli ; Dallmeier-Tiessen, Sünje ; Dasler, Robin ; Feger, Sebastian ; Fokianos, Pamfilos ; Gonzalez, Jose Benito ; Hirvonsalo, Harri ; Kousidis, Dinos ; Lavasa, Artemis ; Mele, Salvatore et al.
In the version of this Perspective originally published, one of the authors’ names was incorrectly given as Kati Lassili-Perini, it should have been Kati Lassila-Perini. This has been corrected in all versions of the Perspective..
2019 - 7 p.
- Published in : Nature Phys. 15 (2019) 197
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REANA: A System for Reusable Research Data Analyses
/ Šimko, Tibor (CERN) ; Heinrich, Lukas (New York University) ; Hirvonsalo, Harri (CSC) ; Kousidis, Dinos (CERN) ; Rodríguez, Diego (CERN)
IT-TALK-2018-008.-
Geneva : CERN, 2018
Fulltext: PDF;
In : 23rd International Conference on Computing in High Energy and Nuclear Physics, CHEP 2018, Sofia, Bulgaria, 9 - 13 Jul 2018
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REANA: A system for reusable research data analyses
/ Šimko, Tibor (CERN) ; Heinrich, Lukas (New York U. (main)) ; Hirvonsalo, Harri (Espoo, Sci. Computing Ctr.) ; Kousidis, Dinos (CERN) ; Rodríguez, Diego (CERN)
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. [...]
CERN-IT-2018-003.-
Geneva : CERN, 2019 - 8 p.
- Published in : EPJ Web Conf. 214 (2019) 06034
Fulltext from publisher: PDF; Preprint: PDF;
In : 23rd International Conference on Computing in High Energy and Nuclear Physics, CHEP 2018, Sofia, Bulgaria, 9 - 13 Jul 2018, pp.06034
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