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)
Mgr. Vladimír Horský, Ph.D. (lecturer)
doc. RNDr. Radka Svobodová, Ph.D. (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
  • Research data lifecycle. The process of planning, describing, and communicating the data lifecycle.
  • Findability, accessibility, interoperability, and reusability of data. Open data as a part of open science. Open science at Masaryk University.
  • Data management plan (DMP). Software for creating DMP and supporting the planning process. Examples of DMP from practice.
  • Data management systems. Practical examples of deployed systems in CEITEC central laboratories.
  • Metadata and metadata schemas. General schemas versus domain-specific schemas. Ontologies. National Metadata Directory.
  • Data archiving and repository platforms. National Repository. Persistent identifiers. Tools to ensure reproducibility of research results.
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