SKM 2023 – wissenschaftliches Programm
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TT: Fachverband Tiefe Temperaturen
TT 68: Focus Session: Making Experimental Data F.A.I.R. – New Concepts for Research Data Management II (joint session O/TT)
TT 68.10: Vortrag
Freitag, 31. März 2023, 12:15–12:30, WIL A317
FAIR Data Infrastructure for Computation: Mapping out the Space of Density Functionals — •Nathan Daelman1, Joseph F. Rudzinski1,2, José M. Pizarro1, Luca M. Ghiringhelli1, Miguel A. L. Marques3, Silvana Botti4, and Claudia Draxl1 — 1Institut für Physik und IRIS-Adlershof, Humboldt-Universität zu Berlin, Berlin — 2Max-Planck-Institut für Polymer Forschung, Mainz — 3Institut für Physik, Martin-Luther-University Halle-Wittenberg, Halle — 4Friedrich Schiller Universität Jena, Jena
The NOMAD Laboratory [1] holds over 135 million computational results, the vast majority of which stem from density-functional theory (DFT). The platform provides adequate querying and data analytics tools (e.g., machine-learning modelling) for processing such Big Data. However, the exchange-correlation (xc) functional with which the data was generated, limits the analysis scope of most thermodynamic and kinetic properties. Here, we present a strategy rooted in semantics for extending method interoperability. We will showcase our map of the entire xc-functional space that, in the context of the FAIRmat consortium [2], is built to be widely accessible and facilitate findability. Lastly, we will discuss the integration of this xc-functionals map into the NOMAD data platform, as well as its publication in ontology format as an effort towards a community-wide vocabulary standard.
[1] C. Draxl and M. Scheffler, MRS Bulletin 43, 676-682 (2018).
[2] M. Scheffler, M. et al., Nature 604, 635-642 (2022).