Journal:The NOMAD Artificial Intelligence Toolkit: Turning materials science data into knowledge and understanding
| Full article title | The NOMAD Artificial Intelligence Toolkit: Turning materials science data into knowledge and understanding |
|---|---|
| Journal | npj Computational Materials |
| Author(s) | Sbailò, Luigi; Fekete, Ádám; Ghiringhelli, Luca M.; Scheffler, Matthias |
| Author affiliation(s) | Humboldt-Universität zu Berlin, Max-Planck-Gesellschaft |
| Primary contact | Email: ghiringhelli at fhi dash berlin dot mpg dot de |
| Year published | 2022 |
| Volume and issue | 8 |
| Article # | 250 |
| DOI | 10.1038/s41524-022-00935-z |
| ISSN | 2057-3960 |
| Distribution license | Creative Commons Attribution 4.0 International |
| Website | https://www.nature.com/articles/s41524-022-00935-z |
| Download | https://www.nature.com/articles/s41524-022-00935-z.pdf (PDF) |
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This article should be considered a work in progress and incomplete. Consider this article incomplete until this notice is removed. |
Abstract
We present the Novel Materials Discovery (NOMAD) Artificial Intelligence (AI) Toolkit, a web-browser-based infrastructure for the interactive AI-based analysis of materials science data under FAIR (findable, accessible, interoperable, and reusable) data principles. The AI Toolkit readily operates on FAIR data stored in the central server of the NOMAD Archive, the largest database of materials science data worldwide, as well as locally stored, user-owned data. The NOMAD Oasis, a local, stand-alone server can also be used to run the AI Toolkit. By using Jupyter Notebooks that run in a web-browser, the NOMAD data can be queried and accessed; data mining, machine learning (ML), and other AI techniques can then be applied to analyze them. This infrastructure brings the concept of reproducibility in materials science to the next level by allowing researchers to share not only the data contributing to their scientific publications, but also all the developed methods and analytics tools. Besides reproducing published results, users of the NOMAD AI Toolkit can modify Jupyter Notebooks toward their own research work.
Keywords: computational methods, theory and computation, artificial intelligence, materials science, FAIR principles
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This presentation is faithful to the original, with only a few minor changes to presentation. In some cases important information was missing from the references, and that information was added.
