Streamlining XAFS Research – From Manual Preparation to Automated Data FAIRness
Authors/Creators
Description
The path from sample preparation to FAIR-compliant publication is often highly compartmentalized. Even with evolving standards like NeXus, research pipelines remain vulnerable to metadata loss due to systemic fragmentation between synthesis, measurement, and analysis. This heterogeneity affects both large-scale facilities and laboratory-based instrumentation.
At the Berlin Laboratory for innovative X-ray technologies (BLiX) in the frame of DAPHNE4NFDI, we have developed a guided, partially automated workflow for laboratory-based X-ray Absorption Fine Structure (XAFS) spectroscopy which is used both for regular scientific research as well as teaching purposes. A python-based GUI replaces manual entries during sample preparation, enforcing a fixed template to ensure completeness and reproducibility. To link samples to data within the database, a BLiX-unique barcode is generated for long-term sample identification. All metadata is automatically pushed via a python API to the electronic-lab-notebook (ELN) eLabFTW and a central database. Upon scanning the barcode on the sample at the XAFS spectrometer, the LabVIEW-based instrument software retrieves all relevant sample information. Post-measurement, spectrum data is previsualized, uploaded into the database and automatically linked to the sample entry in the ELN. While this workflow is already fully operational for XAFS, it is also being developed for other X-ray spectroscopy methods within the Kanngießer group at TU Berlin.
This automation eliminates manual transcription errors and provides researchers with "ready-to-evaluate" data. Furthermore, eLabFTW acts as a collaborative interface where external partners can input synthesis parameters directly and receive live updates during analysis. By capturing metadata at the point of origin, we create a pre-standardized environment. This facilitates seamless data uploads to repositories like RefXAS or Zenodo, ensuring that as standards like NeXus evolve, BLiX data remains mappable, accessible, and future-proof.
ELabFTW: https://www.elabftw.net/
DAPHNE4NFDI: https://www.daphne4nfdi.de/index.php