Truly FAIR Service for the International XAS Community: A Materials Overview through IXDB

X-ray absorption spectroscopy (XAS) has a long history of data sharing, and so databases have been constructed and cross-referenced for a long time. We introduce the "International XAFS DB Portal" (https://ixdb.jxafs.org/), an initiative to connect XAS databases scattered around the world and make all data findable. Currently, IXDB provides a multi-scale overview of materials by exploring related XAS spectra from databases around the world and linking them to crystallographic information and various physical properties. This talk was held in the course of the DAPHNE4NFDI TA1 Data for science lecture series on January, 28 2025.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-01-28
DOI
https://doi.org/10.5281/zenodo.14778589
Primary Topic
Machine Learning in Materials Science
Type
article
Field-Weighted Citation Impact
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article

Truly FAIR Service for the International XAS Community: A Materials Overview through IXDB

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

Truly FAIR Service for the International XAS Community: A Materials Overview through IXDB

article en

Abstract

X-ray absorption spectroscopy (XAS) has a long history of data sharing, and so databases have been constructed and cross-referenced for a long time. We introduce the "International XAFS DB Portal" (https://ixdb.jxafs.org/), an initiative to connect XAS databases scattered around the world and make all data findable. Currently, IXDB provides a multi-scale overview of materials by exploring related XAS spectra from databases around the world and linking them to crystallographic information and various physical properties. This talk was held in the course of the DAPHNE4NFDI TA1 Data for science lecture series on January, 28 2025.

Zenodo (CERN European Organization for Nuclear Research)
National Institute for Materials Science (JP)
Partnerships for the goals, Industry, innovation and infrastructure
Openalex Percentile: Top 65%
Machine Learning in Materials Science
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