<?xml version='1.0' encoding='UTF-8'?><metadata xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcterms="http://purl.org/dc/terms/" xmlns="http://dublincore.org/documents/dcmi-terms/"><dcterms:title>Quinex and Data Extraction from Scientific Publications</dcterms:title><dcterms:identifier>https://doi.org/10.26165/JUELICH-DATA/HFGWDB</dcterms:identifier><dcterms:creator>Jan Göpfert</dcterms:creator><dcterms:creator>Patrick Kuckertz</dcterms:creator><dcterms:creator>Titan Hartono</dcterms:creator><dcterms:creator>Jann Michael Weinand</dcterms:creator><dcterms:publisher>Jülich DATA</dcterms:publisher><dcterms:issued>2026-09-07</dcterms:issued><dcterms:modified>2026-09-07T07:25:17Z</dcterms:modified><dcterms:description>This presentation introduces Quinex, an open-source framework for the automated extraction of quantitative information from scientific literature. It demonstrates how quantitative statements embedded in publications can be transformed into structured, reusable datasets to support literature analysis, research data management, and data-driven scientific workflows.&#xd;
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The presentation was given by Patrick Kuckertz as part of the 90th Jour Fixe FDM organized by fdm.nrw.&#xd;
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&lt;h3>Acknowledgements&lt;/h3>&#xd;
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The authors would like to thank the German Federal Government, the German State Governments, and the Joint Science Conference (GWK) for their funding and support as part of the NFDI4Ing consortium. Funded by the German Research Foundation (DFG) - project number: 442146713.&#xd;
This work was also supported by the Helmholtz Association under the program "Energy System Design".</dcterms:description><dcterms:subject>Computer and Information Science</dcterms:subject><dcterms:subject>quantitative information extraction</dcterms:subject><dcterms:subject>scientific literature mining</dcterms:subject><dcterms:subject>small language models</dcterms:subject><dcterms:subject>automated literature review</dcterms:subject><dcterms:subject>structured data extraction</dcterms:subject><dcterms:subject>scientific NLP</dcterms:subject><dcterms:isReferencedBy>Göpfert, Jan, et al. "Quinex: Quantitative information extraction from text using open and lightweight LLMs." The Innovation (2026)., doi, 10.1016/j.xinn.2026.101391, https://doi.org/10.1016/j.xinn.2026.101391</dcterms:isReferencedBy><dcterms:contributor>Kuckertz, Patrick</dcterms:contributor><dcterms:dateSubmitted>2026-06-22</dcterms:dateSubmitted><dcterms:license>CCBY</dcterms:license></metadata>