The school’s program includes the development of competencies related to the digital transformation of science, research data management and research workflows (RDM & research workflows) and the use of artificial intelligence in scientific research. The program is modular and flexible, which allows its scope to be adapted to the needs of institutions and participants. The training program is implemented in Polish and English, and selected elements of the offer can also be conducted in German, which allows participants from different countries to participate and fosters international cooperation.
EOSS offers a variety of forms of education and competence development, including:
- Data Steward School – a comprehensive program of education for specialists in the field of research data management, consisting of:
- intensive stationary and online courses
- specialization courses conducted in the stationary or remote formula
- practical workshops and thematic training
- webinars and expert lectures
- individual mentoring and mentoring programs
- peer-to-peer learning and exchange of experiences between participants
- on-the-job training, enabling the acquisition of competencies in the environment
- study visits to research institutions and infrastructures
- tailor-made courses for scientific institutions and public administrations
As part of these forms of education, training is carried out covering various aspects of the digital transformation of science. Examples of thematic blocks include:
Block 1: Digital science and research infrastructures
- digitization of science and data-driven science
- national and European Open Science policies and strategies, national and European research infrastructures and data ecosystems
- European Open Science Cloud (EOSC) and European Data Spaces
- digital research workflows and tools supporting the research process
Block 2: Research Data Management
- Research Data Management (RDM) and organization of research workflows
- Data Management Plan (DMP) – preparation, implementation and reporting
- FAIR and CARE standards for research data
- Data repositories, research infrastructures and data services
- metadata, PIDs
- Data quality assurance
- data archiving
- reuse of research data
Block 3: Legal, ethical and security aspects of digital science
- licensing of research data and management of intellectual property rights
- managing sensitive data and personal data in research
- data security, information protection and sovereignty of research data
- scientific integrity and ethics of scientific research, including responsible research conduct and transparency of research methods
- legal and ethical aspects of the use of AI in research, including the responsible, transparent and compliant use of AI tools in the research process
Block 4: Artificial intelligence and advanced analytical methods
- AI in science
- the use of AI tools in scientific data analysis
- computational and analytical methods supporting data-driven research
The program includes both basic training and specialized courses, including training on data management and research workflows in specific fields and scientific disciplines. Trainings can also be designed in a tailor-made formula, tailored to the needs of specific institutions, research teams or professional groups.