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PhilReedData merged 1 commit into from
Dec 10, 2025
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Add news item from ELIXIR BioHackathon Europe 2025 project #874

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24 changes: 24 additions & 0 deletions 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).