UCT Prague Data Stewardship Support Workshop: DMP in DSW

Workshop Data Management Plan in Data Stewardhip Wizard Content of this presentation is licensed via CC BY 4.0, except where otherwise noted for content created by third-parties. Czech English B2319 Online 12. 12. 2025 16. 12. 2025 10:00 –12:30 9:30– 12:00 Jan Vališ Georgia Kutentaki Why manage data? 1. Prevent data loss/corruption/theft 2. Increase efficiency of: •your own research •datasets preparation for publication 3. Increase impact of your research 4. Establish collaboration 5. Prepare for requirements of: •journal editors •funding providers 2004–2005 citation counts of 85 trials by data availability. Heather A. et al. 2007. PLOS ONE. CC BY 4.0. 10.1371/journal.pone.0000308. 2/9 Legal landscape in the Czech Republic •Zák. č. 328/2025 Sb. o výzkumu, vývoji, inovacích a transferu znalostí •Covers publicly funded research •§82, 1) Information from research must be open, remote, free-of-charge and reusable •§83, 3) Research data must be FAIR •§82, 4) & §83, 2) Exceptions from opening 3/9 FAIR Data Findable •Metadata •Persistent Identifiers (DOI, ORCiD, ROR, IGSN…) •Registration and indexing in searchable repository Accessible •Free and open metadata •Metadata available even when data are not available Interoperable •Widely used language •Preferred formats •Vocabularies and ontologies Reusable •Rich description (Read Me File) •License •Field/Community standards Source: SangyaPundir,FAIR data principles,CC BY-SA 4.0 4/9 FAIR vs. Open •Legal exceptions from opening data: •Personal data •Sensitive data •Data protected by legitimate interests •Intellectual property •Commercialization •What then? •Anonymization/pseudonymization? •Informed consent? •Embargo? •Controlled access (only on request)? •Metadata must be always open even if data are not Source: Valis, Jan (2024). FAIR vs. Open Data (Venn diagram). doi.org/10.6084/m9.figshare.25648548.v1; License: CC BY 5/9 Scholarly publications vs. Data •Scientific findings communicated through scholarly publications: •Journal articles/papers •Monographies •Conferences etc. •Research data •= any information collected, observed, generated, or created during the research to produce and support research findings •Primary data •Directly from a given research •Quantitative (volume) vs. Qualitative (interview) •Experimental (pH) vs. Observational (bird migration) •Secondary data •From other research used for different reason Research data are not: •Project proposal, budget etc. •Evaluation report •Conference proceedings •Journal article 6/9 Data Management Plan •Describes data handling in all stages of the cycle •Mandatory in most projects after 01. 09. 2022 •Horizon Europe DMP –widely adopted template •GAČR •TAČR (all project except for contracted research VaVaI àExcel template) •AZV •INTER-EXCELENCE/COST •OP JAK, HE, MSCA •Data Stewardship Wizard •helps researchers create a draft of DMP through a questionnaire •open source, UCT Prague has its own instance Adapted from “Research Data Lifecycle“ by UK Data Service, CC BY Data Analysis Data Reusing Data Collection Data Processing Data Archiving Data Lifecycle Data Publishing 7/9 Where can I learn more? UCT Prague Data Stewardship support •Free consultations •Project proposals (data statement, FTE suggestions, OS practices) •Active projects (DMP, advice on dataset preparation for publication) •Finished projects (advice on long-term archiving etc.) •Breakfasts with Data Stewards •Informal meetings with project data stewards •Exchange of relevant information, goof practice sharing •Data Stewardship Course •Module 1 (self-paced in E-Learning) + Module 2 (in person practice) •soon also as CŽV [email protected] open.vscht.cz 8/9 Where can I learn more? NTK •Free consultations (CZ & EN) •RDM Guide (CZ & EN) Other self-study •EOSC CZ –webinars on all OS/RDM related topics (CZ & EN) •NPOS –website with useful information about OS (CZ) 9/9