Tento webinář proběhe v angličtině. / This webinar is held in english.
Annotation
Using a STEM-specific example, this seminar will demonstrate good practice in data management planning using the Data Stewardship Wizard (dmp.eosc.cz), as well as in preparing datasets and metadata for long-term preservation. Although the example (spectroscopy) is specific to one field, the key lessons can be applied across a range of STEM disciplines.
Benefits for participants, what they will learn
Participants will gain insight into completing a Data Management Plan (DMP) using a real-world STEM example. As some aspects of a DMP are not discipline-specific, researchers from other fields will also benefit from this part of the seminar, as many of the questions are relevant across disciplines.
Level
All levels
Language
English
Prerequisites
It is helpful if participants have a basic awareness of the data management requirements for their projects, so that they can relate what they learn to their own use cases.
Tutors
Georgia Koutentaki
MEng, is a chemical engineer from Greece. She works as a data steward for STEM fields at the National Repository Platform in Czechia, operated by the Faculty of Information Technology (FIT) at the Czech Technical University in Prague (CTU), and is a member of the Data Stewardship Support Team at the University of Chemistry and Technology, Prague (UCT Prague). She is the international coordinator of the Czech Data Stewards Community and the founder of the STEM Data Stewards subcommunity. She is also an artist and is currently completing her doctoral studies at UCT Prague.
Jan Vališ
MSc, is a Czech analytical chemist at the University of Chemistry and Technology, Prague (UCT Prague), where he develops diagnostic tools combining spectroscopy and machine learning. He is also a faculty data steward at UCT Prague and an institutional data steward at the Institute of Macromolecular Chemistry of the Czech Academy of Sciences (CAS). In addition, he provides methodological support and consultations on research data management and open science as part of the NCIP VaVaI project at the National Library of Technology.
