Training and skills development are essential components of ELIXIR CZ’s mission to provide researchers, clinicians, data stewards, and developers with the knowledge and capabilities required to use national and European bioinformatics infrastructures effectively. As the life sciences enter an era defined by high-throughput data generation, AI-driven analytics, and complex heterogeneous datasets, training becomes a fundamental mechanism for ensuring that the broader scientific community can fully benefit from the tools, services, and data produced within ELIXIR CZ.
The training programme is designed to serve both beginners and advanced users, offering clear learning pathways that span introductory sessions, specialised workshops, expert seminars, and hands-on courses. Importantly, training is not an isolated activity but deeply connected to tool and service adoption: each tool included in the ELIXIR CZ portfolio must be accompanied by well-developed tutorials, documentation, and user-support material.
By 2030, ELIXIR CZ aims to establish a comprehensive, structured, and sustainable national training ecosystem that not only supports its users but also significantly contributes to European training efforts through TeSS (Training e-Support System), Galaxy Training Network, ELIXIR Communities, and EOSC training initiatives. This programme will position the Czech Republic as a leader in skills development, strengthening research excellence and ensuring equitable access to advanced computational methods.
Current Situation and Identified Strengths
The Czech bioinformatics and data-science community is supported by a vibrant training landscape, with numerous workshops, tutorials, and courses already being delivered by ELIXIR CZ institutions. Training on Data Stewardship Wizard, FAIR data principles, structural bioinformatics, genomics, molecular visualisation, and basic computational skills has been available for several years, forming a solid baseline for the next strategic phase.
A major strength is the combination of expert knowledge and diversity of tools across ELIXIR CZ domains. Each domain — from structural bioinformatics to chemical biology, genomics, FAIR data, and AI/ML — has active researchers capable of delivering high-quality training, mentoring, and community support. These experts have strong connections to European initiatives such as the ELIXIR Training Platform, ELIXIR Communities, and Staff Exchange programmes, enabling cross-node knowledge transfer.
Technological support is another clear asset. ELIXIR CZ benefits from access to HPC facilities, GPU-enabled nodes, cloud infrastructure, and interactive platforms (JupyterHub, Galaxy, custom portals), all of which support effective hands-on courses and reproducible training environments. Existing digital resources, including the ELIXIR CZ YouTube channel and DSW training videos, offer a foundation for building modern e-learning modules.
Finally, Czech institutions have strong existing collaborations with the Galaxy Training Network, EOSC training pilots, and the Slovenian ELIXIR training platform, which provide proven frameworks for organising, delivering, and sustaining training activities. These relationships will be instrumental when scaling up the national programme.
As part of its effort to strengthen data stewardship’s leading role on the European scene, ELIXIR CZ created and promoted a set of instructional Data Management video series, available online from Youtube. These resources are intended to serve as a launchpad for the development of more complex training activities in Data Management and FAIR data principles during the upcoming strategic period. By introducing these video materials, ELIXIR CZ aims to standardise and make fundamental know-how easily accessible to ensure good data management habits from the early stages of a scientific career.
Challenges and New Directions
As ELIXIR CZ expands its portfolio of tools and services, training must evolve to ensure that users can adopt and apply increasingly sophisticated methods. The diversity of user backgrounds — ranging from students and early-career researchers to experienced bioinformaticians, data stewards, clinicians, and industrial partners — requires training to be modular, multi-level, and accessible to audiences with varied expertise and expectations.
- One pressing challenge is the fragmentation of materials across different platforms and repositories, which reduces discoverability and complicates onboarding for new users. A unified training platform is needed to consolidate materials, host e-learning modules, and provide structured access to documentation and interactive content.
- The rapid emergence of AI/ML and multimodal analytics demands continuous updates to training modules. Users require guidance on how to responsibly apply AI methods, prepare AI-ready datasets, understand model limitations, and evaluate outputs. Integrating AI training across all domains is essential to ensure that the Czech community remains competitive.
- Another challenge is the growing need for specialised training for sensitive data analytics, including TRE-based workflows for genomic and clinical data. This requires new training formats, including restricted-access environments, accredited training for clinicians, and courses on privacy-preserving analytics.
- Furthermore, as ELIXIR CZ tools expand, training materials must be systematically maintained, versioned, and updated to match new tool releases. Ensuring sustainability — through documentation standards, automated testing of training workflows, and community contributions — will be crucial.
- Finally, training must evolve toward hybrid and scalable formats, making use of video materials, self-paced e-learning modules, and automated interactive tutorials. These formats will make training accessible to a wider audience and reduce the dependency on fully in-person delivery.
