Meetings

Recent preprints

• Jan 26, 2026

  BH25DE report: On the path to machine-actionable training materials

  The fragmentation of training materials across research infrastructures often results in unsustainable resource duplication and significant barriers to upskilling. This work aims to enable developers to build systems that effectively discover relevant materials by promoting a federated, FAIR-compliant strategy for open training. The project operated across three interrelated streams: metadata interoperability, material analysis, and the definition and representation of learning paths in a machine readable manner.We demonstrated content federation via the mTeSS-X platform, enabling cross-instance exchange and preparing for future integration with the EOSC federation. To enhance interoperability, we indexed relevant ontologies and curated semantic crosswalks between established metadata models, specifically MoDALIA and Schema.org/Bioschemas. These mappings were implemented within the open-source OERbservatory Python package, providing a facility for exchanging data between platforms such as DALIA and TeSS. For material analysis, we utilised Large Language Models (LLMs) and explored vectorisation techniques to calculate similarity, allowing for the identification of related materials and the potential for future deduplication of records across registries.To address the lack of machine-actionable trajectories across related or sequential materials, we proposed new Bioschemas profiles specifically for learning paths. By extending Schema.org types, including Course and Syllabus, we developed a schema that supports modular and linear orderings of training materials. This model was validated using SPARQL queries on knowledge graphs derived from real-world examples like the Galaxy Training Network. Such advancements provide a foundation for automated path generation and improved discoverability within training catalogues, and serves as a use case and strategy with broader applicability beyond those materials. 1 minute read
• Jan 22, 2026

  METRICS - Monitoring of Key Performance Indicators for ELIXIR Services

  Key Performance Indicators (KPIs) are increasingly requested by a diverse range of stakeholders across the research ecosystem. Funders want to measure the impact of projects and related services they fund, or research organisations want to track the service use for informed decision making. Service providers themselves are also interested in monitoring their services to gather feedback and improve service quality. KPIs are a simple, but powerful tool for these purposes.As part of the BioHackathon Europe 2025, we report on the activities of the METRICS project, which addresses the need for consistent and transparent evaluation of services across ELIXIR and related initiatives using KPIs. The project brings together experts from multiple ELIXIR Nodes and scientific domains to identify, harmonise, and semantically model KPIs that reflect service quality, usage, sustainability, and impact. By exploring existing evaluation frameworks, and processes, the team aims to design a flexible yet coherent foundation for KPI monitoring of ELIXIR services. This report summarises the project’s motivation, current landscape analysis, and initial steps toward developing an ontology-driven framework for KPI representation, fostering interoperability and supporting evidence-based management of life science infrastructures. 1 minute read
• Jan 6, 2026

  QPX: Pathway analysis environment

  Building on our work at DBCLS BioHackathon 2023 (BH23), where we introduced QPX and promoted pathway modeling with WikiPathways (Pico et al., 2008) using PathVisio (Kutmon et al., 2015), we now focused on creating new pathway diagrams for diverse species and registering them in WikiPathways with functional annotations. In parallel, we deployed WikiPathways node data into Elasticsearch to enable fast and flexible search and integration of pathway information. less than 1 minute read
• Dec 31, 2025

  BioHackEU25 Report Project 16: MiCoReCa (Microbiome Community Resource Catalogue) - Towards Centralized Curation And Integration Of Microbiome Bioinformatics Resources

  The rapid growth of microbiome research has led to the development of numerous bioinformatics tools and databases, but information about them remains fragmented across disparate, often outdated cataloging efforts, hindering resource discovery and utilization. To address this critical gap, the ELIXIR Microbiome Community proposes the development of MiCoReCa (Microbiome Community Resource Catalogue), a comprehensive, dynamic, open-access catalogue of microbiome-related bioinformatics resources (tools, workflows, training, standards, and databases). Leveraging our community’s expertise, this initiative will utilize standardized ontologies like EDAM and cross-reference established platforms like bio.tools and WorkflowHub to create a centralized, findable inventory. A key feature is the community-driven process for identifying and curating missing ontological terms and metadata, ensuring MiCoReCa’s accuracy and relevance in collaboration with partner platforms. Furthermore, the catalogue will integrate links to training materials from TeSS to support appropriate tool usage, and connect with OpenEBench for benchmarking capabilities. This project will not only provide a vital resource for the microbiome field, enhancing research efficiency and reproducibility, but will also establish a sustainable, adaptable infrastructure potentially applicable to other ELIXIR Communities. This effort represents a significant contribution by the ELIXIR Microbiome Community to streamline microbiome bioinformatics. 1 minute read
• Dec 23, 2025

  Enhancement of the Interoperability of Trait Data on Genetic Resources between Japan and France

  Japan’s National Agriculture and Food Research Organization initiated a collaborative research project with France’s National Research Institute for Agriculture, Food and Environment to evaluate wheat genetic resources and to identify materials with desirable traits using standardized criteria. This paper presents the current status of trait data standardization between the two organizations and outlines a direction for standardization. Trait data for genetic resources in Japan and France are managed using independently developed standards. The lack of mapping standards hinders data integration and interoperability. To support experts in the mapping process, we developed a tool that translates trait terms. A generative AI-based translation tool appears to be applicable for collecting relevant information to support mapping between trait terms, as well as translating newly submitted Japanese trait terms into English. less than 1 minute read
• Dec 19, 2025

  Increasing FAIRness in agrosystem sciences and plant phenomics

  As part of the de.NBI BioHackathon 2023, we here report about our progress on increasingFAIR-compliance in agrosystem sciences and plant phenomics. Through the collaborative effortsof the agrosystem and plant sciences communities, research data are available through variousdata repositories and infrastructures. To foster these developments and increase the value forthe communities, enabling FAIR-compliance for scientific datasets is one top priority strategicaim. Due to the heterogeneity of the sub-domains and their requirements, we addressedthree challenges with direct relation to specific FAIR principles: Increasing findability of digitalagrosystem resources by extending Schema.org, Enabling easy creation of MIAPPE-compliantISA metadata for Plant Phenotyping Experiments, and Increasing Plant Data Accessibility andCollaboration with FAIDARE. less than 1 minute read
• Dec 17, 2025

  Decoding Complex Genotype-Phenotype Interactions by Discretizing the Genome

  Background: Despite the ease and affordability of genome sequencing in biomedical research, the genetic causes of many diseases or their subtypes remain unknown due to diverse biological mechanisms that complicate genotype-phenotype relationships. Most previous studies have focused on single variants or sets of variants presumed to be directly causal for the disease. However, incomplete penetrance, in which some individuals carry disease-associated variants yet exhibit no phenotype, suggests that these variants, the genomic background and other secondary factors combine to shape the susceptibility to the disease. 1 minute read