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1000
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Abstract/Summary
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This poster motivates and depicts the work path towards a FAIR data collection and processing at large scale X-ray infrastructure, especially for the X-ray reflectivity use case. The envisioned procedure is, the experimental data and meta data is collected by means of human input and automatic aggregation during the experiment. The (meta) data is stored in an open and standardized format and the meta data is made publicly available in a meta data catalogue. The sample related information is conserved in a sample registry and uniquely indentifiable by a PID, e.g. IGSN. During the experiment an automatic, machine learning based analysis is indentifying experimental and data quality related issues and reports these back to the human experimenters.
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