More than open data: towards a FAIR data and simulation infrastructure with AiiDA and Materials Cloud

High-throughput computational materials discovery studies can generate sheer amounts of interconnected data. Making such data open and FAIR is only possible with proper workflow tools that not only automate the simulations, but also deal appropriately with data management. I will discuss how we addr...

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Main Author: Pizzi, Giovanni
Format: Conference Object
Language:English
Published: 2023
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Online Access:https://zenodo.org/record/8388969
https://doi.org/10.5281/zenodo.8388969
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spelling ftzenodo:oai:zenodo.org:8388969 2023-10-29T02:39:22+01:00 More than open data: towards a FAIR data and simulation infrastructure with AiiDA and Materials Cloud Pizzi, Giovanni 2023-09-29 https://zenodo.org/record/8388969 https://doi.org/10.5281/zenodo.8388969 eng eng doi:10.1038/s41597-020-00638-4 doi:10.1038/s41597-020-00637-5 doi:10.1038/s41524-021-00594-6 doi:10.5281/zenodo.8388968 https://zenodo.org/communities/nffa-europe-workshop-fair-2023 https://zenodo.org/record/8388969 https://doi.org/10.5281/zenodo.8388969 oai:zenodo.org:8388969 info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0/legalcode info:eu-repo/semantics/lecture presentation 2023 ftzenodo https://doi.org/10.5281/zenodo.838896910.1038/s41597-020-00638-410.1038/s41597-020-00637-510.1038/s41524-021-00594-610.5281/zenodo.8388968 2023-10-03T23:02:23Z High-throughput computational materials discovery studies can generate sheer amounts of interconnected data. Making such data open and FAIR is only possible with proper workflow tools that not only automate the simulations, but also deal appropriately with data management. I will discuss how we address these challenges with the open-source high-throughput infrastructure AiiDA [1], an automated and scalable solution for workflow management, data provenance storage and reproducibility, supported by a broad community of developers (over 120 different simulation engines are supported by AiiDA, see the AiiDA plugin registry [2]). After introducing AiiDA, I will discuss how we can achieve FAIR data sharing when combining AiiDA with our Materials Cloud platform [3]. I will then focus on how we can go beyond "just" open FAIR data, toward making also simulations FAIR. We target accessibility of advanced HPC workflows with the development of AiiDA common workflow (ACWF) interfaces, to perform routine material-science tasks with a single input/output interface [4]. We demonstrate how any user can perform in a reproducible way, e.g., structural relaxations via a single common interface with 11 different codes (Abinit, BigDFT, CASTEP, CP2K, FLEUR, Gaussian, NWChem, ORCA, Quantum ESPRESSO, Siesta VASP). These workflows only require the user to provide an input crystal or molecular structure, and all other numerical inputs are automatically selected appropriately for each code. Accessibility is then further increased combining AiiDA's workflows with the AiiDAlab graphical interface [5]. The value of the ACWF approach is demonstrated by our recent collaborative effort [6] to test precision and transferability of DFT methods across chemistries (all elements from hydrogen to curium, in 10 prototypical crystal structures), resulting in a reference dataset of 960 equations of state cross-checked between two all-electron codes, then used to verify and improve 9 other pseudopotential methods. I will conclude discussing efforts to ... Conference Object Orca Zenodo
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description High-throughput computational materials discovery studies can generate sheer amounts of interconnected data. Making such data open and FAIR is only possible with proper workflow tools that not only automate the simulations, but also deal appropriately with data management. I will discuss how we address these challenges with the open-source high-throughput infrastructure AiiDA [1], an automated and scalable solution for workflow management, data provenance storage and reproducibility, supported by a broad community of developers (over 120 different simulation engines are supported by AiiDA, see the AiiDA plugin registry [2]). After introducing AiiDA, I will discuss how we can achieve FAIR data sharing when combining AiiDA with our Materials Cloud platform [3]. I will then focus on how we can go beyond "just" open FAIR data, toward making also simulations FAIR. We target accessibility of advanced HPC workflows with the development of AiiDA common workflow (ACWF) interfaces, to perform routine material-science tasks with a single input/output interface [4]. We demonstrate how any user can perform in a reproducible way, e.g., structural relaxations via a single common interface with 11 different codes (Abinit, BigDFT, CASTEP, CP2K, FLEUR, Gaussian, NWChem, ORCA, Quantum ESPRESSO, Siesta VASP). These workflows only require the user to provide an input crystal or molecular structure, and all other numerical inputs are automatically selected appropriately for each code. Accessibility is then further increased combining AiiDA's workflows with the AiiDAlab graphical interface [5]. The value of the ACWF approach is demonstrated by our recent collaborative effort [6] to test precision and transferability of DFT methods across chemistries (all elements from hydrogen to curium, in 10 prototypical crystal structures), resulting in a reference dataset of 960 equations of state cross-checked between two all-electron codes, then used to verify and improve 9 other pseudopotential methods. I will conclude discussing efforts to ...
format Conference Object
author Pizzi, Giovanni
spellingShingle Pizzi, Giovanni
More than open data: towards a FAIR data and simulation infrastructure with AiiDA and Materials Cloud
author_facet Pizzi, Giovanni
author_sort Pizzi, Giovanni
title More than open data: towards a FAIR data and simulation infrastructure with AiiDA and Materials Cloud
title_short More than open data: towards a FAIR data and simulation infrastructure with AiiDA and Materials Cloud
title_full More than open data: towards a FAIR data and simulation infrastructure with AiiDA and Materials Cloud
title_fullStr More than open data: towards a FAIR data and simulation infrastructure with AiiDA and Materials Cloud
title_full_unstemmed More than open data: towards a FAIR data and simulation infrastructure with AiiDA and Materials Cloud
title_sort more than open data: towards a fair data and simulation infrastructure with aiida and materials cloud
publishDate 2023
url https://zenodo.org/record/8388969
https://doi.org/10.5281/zenodo.8388969
genre Orca
genre_facet Orca
op_relation doi:10.1038/s41597-020-00638-4
doi:10.1038/s41597-020-00637-5
doi:10.1038/s41524-021-00594-6
doi:10.5281/zenodo.8388968
https://zenodo.org/communities/nffa-europe-workshop-fair-2023
https://zenodo.org/record/8388969
https://doi.org/10.5281/zenodo.8388969
oai:zenodo.org:8388969
op_rights info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/4.0/legalcode
op_doi https://doi.org/10.5281/zenodo.838896910.1038/s41597-020-00638-410.1038/s41597-020-00637-510.1038/s41524-021-00594-610.5281/zenodo.8388968
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