SKM 2023 – wissenschaftliches Programm

Bereiche | Tage | Auswahl | Suche | Aktualisierungen | Downloads | Hilfe

TT: Fachverband Tiefe Temperaturen

TT 56: Focus Session: Making Experimental Data F.A.I.R. – New Concepts for Research Data Management I (joint session O/TT)

TT 56.7: Topical Talk

Donnerstag, 30. März 2023, 17:00–17:30, WIL A317

Open Research Data for Photons and Neutrons: Applications in surface scattering and machine learning — •Linus Pithan — Universität Tübingen, Institut für Angewandte Physik - DAPHNE4NFDI

Open (F.A.I.R.) research data is becoming a key ingredient for data driven machine learning (ML) applications that requires access to existing data of preceding experiments - which goes well beyond data collected in the context of one's own experiments which one might keep in a secret drawer. We will discuss current possibilities as well as future opportunities and challenges with special emphasis on surface scattering. Embedded in the DAPHNE4NFDI (DAta from PHoton and Neutron Experiments) consortium we present efforts on how data catalogs may serve as backbone for F.A.I.R. datasets provided by synchrotron and neutron sources or through community efforts. Besides suitable metadata collection also the harmonization of data- and metadata formats are issues still to be tackled especially for systematic access to fully analyzed, experimental datasets (e.g. by adopting NeXus community conventions). After a broader overview and shining light on the SciCat meta-data catalog system,[1] we discuss as application examples efforts in the field of reflectometry (XRR, NR) [2,3] and X-Ray scattering and diffraction (WAXS, GIWAXS and XPCS).[1,4]

[1] V. Starostin, L. Pithan et al. 2022, SRN, Vol. 35, No. 4

[2] A. Greco et al. 2022, J. Appl. Cryst. 55 362

[3] L. Pithan et al., Refl. dataset, 10.5281/zenodo.6497438

[4] V. Starostin et al. 2022, npj Comp. Mat. 8, 101