4th BioHackathon Germany, Walsrode, Germany
BH25DE
2025-12-01
- 2025-12-05
https://www.denbi.de/de-nbi-events/1840-4th-biohackathon-germany
Website
Previous BioHackathon Germany preprints
YAML instructions
biohackathon_name: "4th BioHackathon Germany"
biohackathon_url: "https://www.denbi.de/de-nbi-events/1840-4th-biohackathon-germany"
biohackathon_location: "Walsrode, Germany"
Preprints
Aug 27, 2026
https://doi.org/10.37044/osf.io/9mj78_v1
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As part of the BioHackathon Germany 2025, we report here about the progress of Project 8 -Enhancing e!DAL-PGP: A Modern Data Submission Platform for Plant Science Research Dataduring the event.The increasing volume of data generated in plant research underscores the necessity for efficient data management and sharing solutions. The de.NBI Service e!DAL-PGP (Arend et al., 2016, p. Arend2020) serves as a critical research data repository, facilitating the storage, management, and dissemination of plant research data. However, the current implementation faces significant challenges concerning the submission process and the provision of a submission tool for different operating systems, which complicate user interactions and hinder data contribution. A primary issue with the existing e!DAL-PGP service is the cumbersome nature of maintaining and deploying a submission tool across various OS environments. This requirement necessitates extensive effort to build, test, and provide the application for each platform. Consequently, this fragmentation can lead to delays and inconsistencies in the submission process, ultimately hindering researchers from effectively submitting their valuable data to the repository. To address these challenges, this project proposes the development of a unified and user-friendly web submission tool that streamlines the data submission process to eliminate the complexities associated with OS-specific requirements and to ensure that all users can submit their data seamlessly. This simplifies the submission process and enhances usability by focussing onimproving the design and functionality. A well-structured and user-centric form is essential for facilitating accurate and complete data submissions. The current interface lacks features that enhance user experience, such as lookup services, contextual help, and clear instructions. By incorporating these elements, we aim to create a more efficient and engaging submission experience, encouraging researchers to contribute their valuable data without unnecessary complexity. This initiative aligns closely with the goals of de.NBI, which emphasizes the provision of high-quality bioinformatics services and the facilitation of FAIR Research Data Management (RDM). Enhancing the e!DAL-PGP service will streamline the data submission process andpromote a culture of collaboration and data sharing within the plant research community.
1 minute read
Aug 10, 2026
https://doi.org/10.37044/osf.io/dfwm9_v1
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State of the art life science training features steep learning curves due to dense technical specifications and complex data formats, often causing cognitive overload and low learner retention. While gamification can enhance engagement, implementing it without trivializing scientific content remains challenging. As part of the Biohackathon Germany 2025, we explored strategies to adapt gamification for bioinformatics education. We curated a resource matrix evaluating 20 digital tools based on cost, implementation effort, and pedagogical impact. To guide instructors, we formulated the “Ten Simple Rules for Gamification in Bioinformatics and Life Sciences Education,” emphasizing a shift from superficial point systems to deep, competency-driven mechanics rooted in authentic data and high-stakes narratives. We validated this framework through two pilot implementations: translating an introductory R programming course into interactive console tutorials using swirl accelerated by Large Language Models (LLMs), and deploying browser-based Research Data Management (RDM) quizzes via Wordwall to reinforce FAIR principles. Our findings reveal that while specialized tools fit specific niches easily, broader open-source frameworks offer greater flexibility, with implementation workloads significantly mitigated by generative AI workflows. Ultimately, gamification serves as a powerful pedagogical asset when balanced correctly, transforming abstract computational workflows into engaging, collaborative simulations that bridge virtual training and professional scientific competency.
1 minute read
Jan 26, 2026
https://doi.org/10.37044/osf.io/un6cd_v1
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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