The Data Steward position at the Faculty of Science aims to assist in managing research data. The primary responsibilities involve data management, data governance, and data policy enforcement.
How can a Data Steward assist you?
- Managing metadata, providing thorough documentation, creation of Data Management Plan (DMP) to support effective data management which has been a mandatory part of Horizon, GAČR and TAČR projects.
- Implementing the FAIR principles, focusing on findability, accessibility, interoperability, and reusability.
- Assist in storing research data in a trusted repository such as Figshare, Dryad, Zenodo, or university's data repository. These repositories enable public access and long-term preservation.
- Making your research data available under an appropriate license, which defines the degree of publicity and rights to use your data.
For assistance with research data and management, please contact MSc. Manali Das at
Workplace: Building C (Faculty of Science, Room Number-00055)
Office Hours: Monday (10:00 AM- 6:00 PM), Wednesday (10:00 AM -6:00 PM), Thursday (10:00 AM - 6:00 PM)
Is low-quality data hindering your research?
The key issues are reliability, accuracy, completeness and relevance.
- Poor documentation.
- Inconsistent formats, non-standard abbreviations, units, labels, formats.
- Data that lacks metadata or explanation about how it was collected, processed, or interpreted.
- Data that does not adhere to established standards or protocols.
- Data collected without proper consent or in violation of privacy laws and regulations.
High quality research data avoids these pitfalls. Good quality data facilitate reproducibility and reuse by providing organized raw data along with comprehensive supplemental documentation.
- Provide access to the raw, granular data from observations, surveys, sensors, etc.
- Use widely-compatible, non-proprietary, and machine-readable file formats that can be utilized by others.
- Data is formatted in a standardized, consistent, and structured manner.
- Contains detailed contextual documentation and descriptive variable labels/codebooks to allow others to interpret the data.
Useful Links:
- How to be FAIR with your data : https://zenodo.org/records/3405141
- Open Data: https://www.lib.jcu.cz/en/open-science/open-data
- Open Acces: https://www.lib.jcu.cz/en/open-science/open-access
- Metadata: https://www.lib.jcu.cz/en/open-science/metadata
