C3750 Data management

Faculty of Science
Autumn 2025
Extent and Intensity
1/0/0. 2 credit(s). Type of Completion: k (colloquium).
In-person direct teaching
Teacher(s)
doc. RNDr. Radka Svobodová, Ph.D. (lecturer)
Mgr. Vladimír Horský, Ph.D. (lecturer)
Mgr. Adrián Rošinec (lecturer)
Mgr. Ing. Tomáš Svoboda (lecturer)
Guaranteed by
doc. RNDr. Radka Svobodová, Ph.D.
National Centre for Biomolecular Research – Faculty of Science
Contact Person: RNDr. Tomáš Raček, Ph.D.
Supplier department: National Centre for Biomolecular Research – Faculty of Science
Prerequisites
None, as this is an introductory course.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
The course aims to introduce students to the fundamental aspects of scientific data management, i.e., data lifecycle planning, data access control, methods of long-term and short-term data storage, and data description through metadata.
Learning outcomes
Upon completion of the course, the student will be able to:
- understand the fundamental aspects of data management and storage,
- describe the life cycle of scientific data from various domains and create a data management plan for it,
- select appropriate software tools for sub-aspects of managing data of a specific type and size, and
- publish the results of their research so that the results can be reproduced.
Syllabus
  • Motivation for data management. FAIR data. Research data lifecycle.
  • Metadata and metadata schemas. General schemas versus domain-specific schemas. Ontologies. Laboratory notebooks.
  • Data management systems (Onedata, iRODS).
  • Data planning and acquisition. Data access control. Sensitive data. Practical examples of systems deployed in CEITEC central laboratories.
  • Data computations (Kubernetes, Jupyter notebooks). Provenance, tools for ensuring the reproducibility of research results (GitHub, Zenodo, FigShare). Containerization.
  • Data archiving and sharing. Data and metadata repositories. National repository. Persistent identifiers. Searching.
Literature
  • Shoshani, A., & Rotem, D. (Eds.). (2009). Scientific data management: challenges, technology, and deployment. CRC Press.
  • Briney, K. (2015). Data management for researchers: Organize, maintain and share your data for research success. Pelagic Publishing Ltd.
Teaching methods
Lectures accompanied by real data management examples.
Assessment methods
Colloquial debate on the topics discussed.
Language of instruction
Czech
Further Comments
The course is taught annually.
The course is taught every week.
  • Enrolment Statistics (recent)
  • Permalink: https://is.muni.cz/course/sci/autumn2025/C3750