Data Steward

The data steward, a newly established role in research data management, plays a crucial part in ensuring the quality and integrity of data throughout the research cycle. This includes the responsible handling of data, from its creation and preparation to use and storage to archiving and sharing or reuse. The data steward's role is to ensure that data management is carried out in accordance with defined principles, policies and rules that support data quality and integrity.

Data steward's agenda

Creating a data management plan and updating it regularly
Managing research data following FAIR principles
Selection of appropriate data and metadata schemas
Ensuring data and metadata quality
Compliance with institutional policies and industry standards (Data Compliance)
Ensuring data protection (Data Security)
Selecting an appropriate data repository
Support for open data sharing "as open as possible, as closed as necessary"

community of Data Stewards in Czechia Map of Data Stewards in Czechia Beginner’s Guide for Data Stewards

Data steward core competencies

Knowledgeable about research topics and the processes involved
Knows the tools and practices available for data management, including standards, vocabularies, infrastructure, storage and backup
Understands FAIR principles and can apply them effectively in practice
Is familiar with research data management best practices within their institution

Data steward's role in the institution

The data stewards act as liaisons between different departments in the institution. Data stewards work closely with and provide expert advice to key data creators and users, including researchers and students. They oversee the proper data handling per the institution's policies and ensure data management standards and procedures are followed.

Why the data steward is a key member of the research team

Validates, documents and checks the quality of data, leading to more reliable research results
Helps comply with legislation (e.g. GDPR) and ethical principles of scientific research, protecting the institution, sensitive data and the research participants themselves
Efficiently automates research processes, data organization and storage, saving time, increasing research visibility and facilitating data reuse
Is available to researchers during the planning and execution of research
Assists in the development of a data management plan and its application in practice
Reduces the risk of losing essential data through thorough planning and implementation of backup procedures
Institutions that manage their data effectively and adhere to data management and sharing standards build a reputation as leaders in scientific transparency and quality, increasing their prestige and attractiveness to other researchers

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13 Jun

Summer School in Ostrava: AI Unlocks New Opportunities for Data Stewards

From June 3–5, Ostrava hosted a summer school for data stewards, focused on modern approaches to managing and sharing scientific data. Participants expanded both their expertise and their network within the Czech community, now numbering over 350 professionals.

29 Apr

Discover the World of Data Stewards: A Series on a Key Role in Modern Research

Proper data handling is the foundation of modern science. In the series Data Stewards: Mission FAIR, you will discover who data stewards are, what their work entails, and what tools and educational opportunities they can use.

16 Apr

Data Stewards Meeting in Brno Brought New Energy and Valuable Discussions

On April 7, the data steward community gathered at Masaryk University in Brno, where participants had the opportunity not only to learn about the latest developments in research data but also to engage in discussions on the ethical and legal aspects of data management and other research data-related topics.

17 Feb

News from the Online Data Stewards Meeting

The Czech data steward community met online on February 4 to discuss key updates, including the release of the Beginner’s Guide for Data Stewards, an ongoing campaign, and an open survey on the use of AI tools in practice.