Published April 28, 2026 | Version v1
Poster Open

CDIF-4-XAS: Describing X-Ray Spectroscopy Data for Cross-Domain Use

  • 1. ROR icon Cardiff University
  • 2. ROR icon Committee on Data of the International Science Council
  • 3. ROR icon Helmholtz-Zentrum Berlin für Materialien und Energie
  • 4. ROR icon Science and Technology Facilities Council
  • 5. CODATA (Committee on Data of the International Science Council)
  • 6. ROR icon Royal Netherlands Academy of Arts and Sciences

Description

CDIF-4-XAS: OSCARS Project on Interoperability
Authors: Abraham Nieva de la Hidalga, Arofan Gregory, Heike Goerzig, Leandro Liborio,
Markus Kubin, Patrick Austin, Rolf Krahl, Simon Hodson, Vyacheslav Tykhonov

X-ray Absorption Spectroscopy (XAS) research has expanded to become a set of widely used scientific
methods with applications across Physics, Chemistry, Surface Science, Nanoscale Science, Biology, and
Environmental and Earth Sciences. Over time, various scientific communities, research facilities, device
providers, and software developers have created different formats and applications to store XAS data
and describe it with metadata. These custom data formats are very often developed ad-hoc they serve
their immediate needs and they are integrated with local workflows but they are not easily integrated
or interoperable outside their immediate usage. While some standards such as XAFS Data Interchange
(XDI) format and NeXus HDF5 format have been developed, add-hoc formats are a widely implemented
and practical interoperability across the full range of systems has yet to be realized. This project looks
at using the WorldFAIR Cross-Domain Interoperability Framework (CDIF), in combination with existing
domain standards and ontologies, to show that real interoperability can be achieved. CDIF utilizes
common cross-domain standards such as Schema.org, SKOS, and DDI-CDI to support FAIR exchange of
data. The project includes drafting the CDIF profile and mappings from existing standards, and
implementation of CDIF tools and workflows inside the EOSC Galaxy infrastructure, including the use of
generative AI to enhance metadata capture. This presentation will present the profile and mappings and
discuss how this approach may be applied to other use cases. We will also discuss and demo the
implementation in Galaxy and the wider applicability of these solutions.

Files

01-314-Poster-CDIF-4-XAS.V4.pdf

Files (28.8 MB)

Name Size Download all
md5:a0f71f581d902d7ab6f022429283d3da
2.8 MB Preview Download
md5:88045a3648405c911b9b33d20cbdfec3
25.9 MB Download

Additional details

Related works

Is derived from
Poster: 10.5281/zenodo.18839666 (DOI)

Funding

European Commission
OSCARS - O.S.C.A.R.S. - Open Science Clusters’ Action for Research and Society 101129751
UK Research and Innovation
PSDI Phase 1b EP/X032663/1