Training courses on developing researchers’ competences in data management – introductory course

Course programme

Module 1. Introduction to Open Science and Research Data Management (Week 1)

• Basics of Open Science
• The role and importance of open research data for the development of science and the building of researchers’ academic achievements
• National and international Open Science policies and guidelines for Open Science – introduction
• FAIR principles
• Research data in the context of the development of the European Open Science Cloud (EOSC)

Module 2. Planning and organisation – Part 1. (Week 2)

• The life cycle of research data in a scientific project
• Types of data and databases
• Types of data repositories and selection criteria
• Data Management Plans – objectives and principles of creation
• Data Management Plans as a requirement in projects funded by Research Funding Organisations (National Science Centre Poland, European Commission)

Module 3. Planning and organisation – Part 2. (Week 3)

• Data management in the context of discipline and adopted research methodology
• Data organisation and version management
• Non-digital data and FAIR principles
• Legal restrictions on the sharing of research data
• Data management, legal and ethical issues, and scientific integrity in research projects
• Management of highly sensitive data

Module 4. Research data storage (Week 4)

• Secure Data Storage
• Principles of Depositing Data in a Repository
• Persistent Identifiers and rules for their use
• Open data formats
• Metadata in the context of disciplinary standards

Module 5. Research data sharing (Week 5)

• Sharing data for the widest possible reuse
• Reuse of existing reliable data in a research project
• Research data documentation for research replication
• Tools supporting the quality control of shared data
• Tools supporting data sharing in accordance with the FAIR principles

Module 6. Tasks and resources in Research Data Management (Week 6)

• University and research institution units engaged in project data management
• Data Steward and their importance in a research project
• Strategic frameworks for Open Science and Research Data Management

Expected learning outcomes

After completing the course, participants will:

• be able to describe the basic principles of Open Science and understand the place of research data in this area;
• understand the need for Research Data Management and its benefits, as well as its relationship to scientific integrity and domain standards;
• be able to identify the requirements of research funders in terms of data management and Open Access;
• be able to develop a research data management plan taking into account the requirements of research funders, good practices and recommendations relevant to the discipline;
• be able to explain the FAIR principles and apply them in practice;
• understand the place of data management in the research project life cycle;
• be able to identify the principles of secure data storage and apply them in practice;
• be able to use research data repositories, know their basic functions and advantages;
• understand the importance of metadata and data documentation and be able to apply discipline-appropriate data description standards;
• be able to share data using tools and solutions appropriate for the discipline and specific research project;
• be able to identify the basic legal options for sharing and reusing research data;
• be able to apply legal tools for open sharing of research data;
• be able to identify legal and ethical aspects relevant to restrictions on data sharing;
• understand the tasks of a data steward and their role in a research institution;
• know where to find additional information on Research Data Management.