Multi-Dimensional Photoemission Spectroscopy: a concept for FAIR photoemission data
Creators: name: Pincelli, Tommaso
Publisher: name: Zenodo
Year: 2024

description: Tommaso Pincellia,b, Abeer Aroraa,c, Steinn Ymir Agustssond, Dmytro Kutnyakhove, Michael Harteltf, Andrea Albinog, Markus Kühbachg, Markus Scheidgeng, Sandor Brockhauserg, Laurenz Rettiga, Martin Aeschlimannf, Ralph Ernstorfera,b

aFritz-Haber-Institut der Max-Planck-Gesellschaft, Faradayweg 4-6, 14195 Berlin, DEbInstitut für Optik und Atomare Physik, Technische Universität Berlin, 10623 Berlin, DEcFreie Universität Berlin, Fachbereich Physik, Arnimallee 14, 14195 Berlin, DEdInstitut für Physik, Johannes Gutenberg-Universität Mainz, 55128 Mainz, DEeDeutsches Elektronen-Synchrotron DESY, 22607 Hamburg, DEfDepartment of Physics and OPTIMAS, University of Kaiserslautern, Kaiserslautern, DEgPhysics Department and IRIS Adlershof, Humboldt-Universität zu Berlin, Berlin, DE

The complexity and size of photoemission data is rapidly increasing as new technological breakthroughs have enabled multidimensional parallel acquisition of multiple observables. Furthermore, as it specializes and diversifies, photoemission is developing into a panoply of different subfields that have closely connected, but different, data and metadata requirements. Most of the community is currently using heterogeneous data formats and workflows, often developed autonomously by single research units. We propose a new data format based on NeXus [1] a hierarchically organized hdf5 structure. The aim is to enable preprocessed data and metadata shareability according to FAIR principles, employing the existing storage and archiving infrastructure such as Zenodo, OpenAIRE and Nomad/FAIRmat. Ultimately, the multidimensional photoemission spectroscopy (MPES) format is designed to allow high-performance automated access, providing experimental databases for high-throughput material search.The MPES format is based on the creation of a standardized set of classes that univocally identify experimental observables and metadata. Such dictionary is complemented by “application definitions”, i.e. ontologies that constrain the existence of specific elements in a file [2]. Application definitions are constructed in a modular, inheritance-based structure that allows sufficient granularity to match the needs of individual subfields, while maintaining a cohesive logical structure favoring interoperability.Our approach involves reaching out to the community using a website with extensive documentation of each dictionary element, open to public review. By this medium, we wish to favor acceptance, to avoid conflict with different low-level preprocessing workflows, and to create continuously updated documentation. As a demonstrator of the potential of our approach, we present the workflow we developed for our data pipeline, originating from time-resolved angularly-resolved photoemission spectroscopy [3].

References:[1] M. Könnecke et al., J. Appl. Cryst. 48, 301-305 (2015) & https://www.nexusformat.org/[2] https://github.com/OpenCOMPES & https://mpes.science/ [3] R. P. Xian et al., Scientific Data 7, 442 (2020) & R.P. Xian et al., arXiv:2005.10210

Acknowledgments:The authors acknowledge the entire FAIRmat Area B collaboration, in which this project is integrated.