A metadata schema for chemical X-ray diffraction data in Dataverse

Single-crystal X-ray diffraction~(SC-XRD) is central to molecular structure determination. Refined crystal structures are well supported by established standards such as the Crystallographic Information Framework~(CIF) and by dedicated repositories including the Cambridge Structural Database~(CSD) and the Crystallography Open Database~(COD). In contrast, the corresponding raw diffraction images remain less well covered. Raw images are often deposited in generic or institutional repositories that lack structured, crystallography-specific metadata fields. This results in incomplete or inconsistent metadata, limiting the findability, interpretability, and reusability of raw diffraction datasets. This poster presents a metadata schema for describing crystallographic raw diffraction data in Dataverse.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-06-25
DOI
https://doi.org/10.5281/zenodo.20715538
Primary Topic
Machine Learning in Materials Science
Type
article
Field-Weighted Citation Impact
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article

A metadata schema for chemical X-ray diffraction data in Dataverse

Alexander Minges
Zenodo (CERN European Organization for Nuclear Research)
Machine Learning in Materials Science
article

A metadata schema for chemical X-ray diffraction data in Dataverse

Alexander Minges
article en

Abstract

Single-crystal X-ray diffraction~(SC-XRD) is central to molecular structure determination. Refined crystal structures are well supported by established standards such as the Crystallographic Information Framework~(CIF) and by dedicated repositories including the Cambridge Structural Database~(CSD) and the Crystallography Open Database~(COD). In contrast, the corresponding raw diffraction images remain less well covered. Raw images are often deposited in generic or institutional repositories that lack structured, crystallography-specific metadata fields. This results in incomplete or inconsistent metadata, limiting the findability, interpretability, and reusability of raw diffraction datasets. This poster presents a metadata schema for describing crystallographic raw diffraction data in Dataverse.

Zenodo (CERN European Organization for Nuclear Research)
Thüringer Universitäts- und Landesbibliothek (DE)
Openalex Percentile: Top 15%
Machine Learning in Materials Science
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A metadata schema for chemical X-ray diffraction data in Dataverse — Alexander Minges · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS