Train-the-trainer Bootcamps
The qualification of trainers in OSTrails’ core areas is essential to scale the adoption of its specifications and services. To support this, two train‑the‑trainer bootcamps will be organised, offering training on the three OSTrails pillars - Data Management Plans, Scientific Knowledge Graphs, and FAIR Assessment - to prepare specialists and build a network of trainers.
Learning objectives
By participating in the Train-the-trainer Bootcamp, participants will:
- Plan and run a training session on the OSTrails specifications and services;
- Explain the OSTrails pillars (Data Management Plans, Scientific Knowledge Graphs and FAIR Assessment);
- Explain the OSTrails reference architecture and Interoperability Frameworks;
- Explain the requirements to use the OSTrails software and services;
- Demonstrate and explain the use of the OSTrails services.
Bootcamps
Two bootcamps will be organised in 2026.
March 2026
Target audience: OSTrails Pilots
Dates:
- 18 March, online session
- 25 March, f2f session
Venue: University of Minho, Braga, Portugal
Second semester of 2026
Target audience: OSTrails Pilots, trainers from National Infrastructures and Research Infrastructures (recruited from relevant competence centres and training initiatives of the European Research Area and ESFRI RIs, utilising the stakeholder network of the project partners involved in the case study pilots).
Dates and Venue: Planned for the second semester of 2026. The exact date and venue will be announced soon.
Train-the-Trainer Toolkit
Purpose of the Toolkit
This toolkit compiles key information about the OSTrails project and learning and training resources, which can be reused in capacity-building initiatives at the national, institutional and infrastructure levels. It is designed to help trainers, research support staff and data stewards to effectively introduce OSTrails tools and services at their organisations, with the purpose of enhancing researchers’ data management practices and skills.
Note: The toolkit is still being developed and contents being collected.
Introducing the OSTrails Project
OSTrails aims to transform how research is planned, tracked, and assessed by embedding the FAIR principles and interoperability at the core of research workflows. The project's overarching goal is to support researchers, institutions, and funders in building a cohesive, machine-actionable Open Science ecosystem aligned with EOSC and FAIR-by-design standards.
Know more at https://ostrails.eu/goals.
How OSTrails Tools Can Be Implemented in an Organisation
Step 1: Assess Institutional Readiness
Step 2: Identify OSTrails-Compatible Tools
Step 3: Integrate Systems
Step 4: Train and Support Researchers
Trainer’s Competency Profile
Drawing on existing competence frameworks related to RDM, FAIR and data stewardship skills, an OSTrails trainer should have the following competences per OSTrails pillar:
Required knowledge:
- Policies and funder requirements for DMPs; relation to FAIR and Open Science
- Structure and content of high-quality DMPs across disciplines (metadata, storage, access, preservation, responsibilities, costs)
- Main DMP tools and emerging maDMPs standards and workflows
Should be able to:
- Guide researchers to design project-specific, FAIR-oriented DMPs, including reuse of existing data where relevant
- Demonstrate and support use of DMP tools (e.g. templates, maDMP platforms) and integrate them into institutional processes
- Diagnose weaknesses in existing DMPs and give targeted feedback
Required knowledge of:
- Basics of semantic web / graph data: entities, relations, ontologies, identifiers, vocabularies
- How knowledge graphs support FAIRness (interoperability, rich metadata, linking across datasets and publications)
- Representative tools and platforms for building, querying, and publishing knowledge graphs in target domains
Should be able to:
- Explain with examples when and why to use knowledge graphs in research workflows
- Lead exercises where participants model a simple domain, map data to ontologies, and populate / query a graph
- Advise on selecting standards, vocabularies, and repositories so resulting graphs are FAIR and reusable
Required knowledge of:
- FAIR principles in depth and interpret them per domain
- FAIR assessment frameworks, metrics and tools (e.g. RDA FAIR Data Maturity Model, FAIRsFAIR self-assessment tools)
- Typical institutional roles and responsibilities in governing FAIR implementation and assessment
Should be able to:
- Guide participants through manual and tool-based FAIR assessments of datasets or repositories, interpreting scores and limitations
- Help design improvement plans (metadata enrichment, licensing, persistent identifiers, repository choice) based on assessment outputs
- Support institutions in embedding FAIR assessment into policies, services, and curricula, using competence frameworks like FAIRsFAIR Competences, FAIR Competence Framework for Higher Education, etc.
Reusable Training Materials per OSTrails Pillar
Trainers can reuse or adapt several resources:
Video recording
Slides
Script
Resources to be made available soon.
Resources to be made available soon.
Resources to be made available soon.
Resources to be made available soon.