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      Materials Cloud, a platform for open computational science

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          Abstract

          Materials Cloud is a platform designed to enable open and seamless sharing of resources for computational science, driven by applications in materials modelling. It hosts (1) archival and dissemination services for raw and curated data, together with their provenance graph, (2) modelling services and virtual machines, (3) tools for data analytics, and pre-/post-processing, and (4) educational materials. Data is citable and archived persistently, providing a comprehensive embodiment of entire simulation pipelines (calculations performed, codes used, data generated) in the form of graphs that allow retracing and reproducing any computed result. When an AiiDA database is shared on Materials Cloud, peers can browse the interconnected record of simulations, download individual files or the full database, and start their research from the results of the original authors. The infrastructure is agnostic to the specific simulation codes used and can support diverse applications in computational science that transcend its initial materials domain.

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          Most cited references 17

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          The SIESTA method forab initioorder-Nmaterials simulation

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              Materials Design and Discovery with High-Throughput Density Functional Theory: The Open Quantum Materials Database (OQMD)

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                Author and article information

                Contributors
                leopold.talirz@gmail.com
                giovanni.pizzi@epfl.ch
                nicola.marzari@epfl.ch
                Journal
                Sci Data
                Sci Data
                Scientific Data
                Nature Publishing Group UK (London )
                2052-4463
                8 September 2020
                8 September 2020
                2020
                : 7
                Affiliations
                [1 ]GRID grid.5333.6, ISNI 0000000121839049, National Centre for Computational Design and Discovery of Novel Materials (MARVEL), , École Polytechnique Fédérale de Lausanne, ; CH-1015 Lausanne, Switzerland
                [2 ]GRID grid.5333.6, ISNI 0000000121839049, Theory and Simulation of Materials (THEOS), Faculté des Sciences et Techniques de l’Ingénieur, , École Polytechnique Fédérale de Lausanne, ; CH-1015 Lausanne, Switzerland
                [3 ]GRID grid.5333.6, ISNI 0000000121839049, Laboratory of Molecular Simulation (LSMO), Institut des Sciences et Ingénierie Chimiques, Valais, , École Polytechnique Fédérale de Lausanne, ; CH-1951 Sion, Switzerland
                [4 ]GRID grid.7354.5, ISNI 0000 0001 2331 3059, nanotech@surfaces laboratory, Swiss Federal Laboratories for Materials Science and Technology (Empa), ; CH-8600 Dübendorf, Switzerland
                [5 ]GRID grid.5801.c, ISNI 0000 0001 2156 2780, Swiss National Supercomputing Centre (CSCS), ; CH-6900 Lugano, Switzerland
                [6 ]GRID grid.5801.c, ISNI 0000 0001 2156 2780, ETH, ; Zürich, Switzerland
                Article
                637
                10.1038/s41597-020-00637-5
                7479138
                6fd25414-4df5-4095-b025-ddea103370f0
                © The Author(s) 2020

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                Funding
                Funded by: FundRef https://doi.org/10.13039/501100001711, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (Swiss National Science Foundation);
                Award ID: 51NF40-182892
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/100010687, EC | EU Framework Programme for Research and Innovation H2020 | H2020 Euratom (H2020 Euratom Research and Training Programme 2014-2018);
                Award ID: 824143
                Award ID: 760173
                Award ID: 814487
                Award ID: 654360
                Award ID: 723867
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/100010663, EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Excellent Science | H2020 European Research Council (H2020 Excellent Science - European Research Council);
                Award ID: 666983
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100001943, Partnership for Advanced Computing in Europe AISBL (PRACE);
                Award ID: 2016153543
                Award ID: 2016163963
                Award Recipient :
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                © The Author(s) 2020

                materials science, databases

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