Merge pull request #874 from BioSchemas/biohackeu25-report

Add news item from ELIXIR BioHackathon Europe 2025 project

Author: PhilReedData

pages/_news/2025-12-09-BHEUPreprint.md

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+---
+layout: post
+title: "BioHackEU25 report: Mining the potential of knowledge graphs for metadata on training"
+tags:
+- BHEU2025
+- Preprint
+- BioHackrXiv
+---
+
+We are pleased to announce another [BioHackrXiv](https://biohackrxiv.org) preprint from 2025. It reports on the work done during the past [BioHackathon Europe 2025](https://biohackathon-europe.org/) by the group [Mining the potential of knowledge graphs for metadata on training](https://github.com/elixir-europe/biohackathon-projects-2025/blob/main/18.md).
+
+Abstract:
+
+> Training metadata in the life‑science community is increasingly standardized through Bioschemas, yet remains fragmented and under‑utilized. 
+> In this work we harvested training records from ELIXR’s TeSS platform and the Galaxy Training Network, converting them into a unified knowledge graph. 
+> A dedicated pipeline parses RDF/Turtle dumps, deduplicates entries, and builds rich indexes (keyword, provider, location, date, topic) that power a Model Context Protocol (MCP) server. 
+> The MCP offers live and offline search tools—including keyword, provider, location, date, topic, and SPARQL queries—enabling natural‑language access to training resources via LLM‑driven clients. 
+> User‑story driven evaluations demonstrate the system’s ability to generate custom learning paths, assemble trainer profiles, and link training data to external repositories. 
+> Findings highlight gaps in persistent identifiers (ORCID, ROR) and location granularity, informing recommendations for metadata providers. 
+> The project showcases how knowledge‑graph‑backed metadata can enhance discoverability, interoperability, and AI‑assisted exploration of scientific training materials.
+
+Citation and link:
+
+D. Panouris, H. Gupta, V. Emonet, J. Miranda, J. Bolleman, P. Reed, F. Bacall, G. van Geest, Mining the potential of knowledge graphs for metadata on training, (2025). [doi:10.37044/osf.io/gv2ac_v1](https://doi.org/10.37044/osf.io/gv2ac_v1).