Training

We offer you various forms of training in research data management. All courses are free.

General open trainings

We offer regular courses via the course database provided by the university's Talent acquisition and development unit (in the category "Wissenschaftsorganisation"). Those courses are free for academic and non-academic staff.

  • 02.10.2023, 10:00 - 12:00: Datenmanagementprojekte mit PHAIDRA, German, online
  • 16.10.2023, 10:00 - 12:00, Implement Data Management Projects with PHAIDRA, English, online
  • 08.11.2023, 10:00 - 12:30. Mein ucris-Profil: Einführung in das Forschungsinformationssystem u:cris für Wissenschafter*innen, German, main building, university library, lecture room
  • 14.11.2023, 10:00 - 13:00, Praktische Einführung in das Repositorium PHAIDRA, German, online
  • 15.11.2023, 09:00 - 12:00, Creating Data Management Plans, English, online
  • 16.11.2023, 09:00 - 16:00, Forschungsdatenmanagement an der Universität Wien, German, Hofburg, Jura-Soyfer-Saal [cancelled]
  • 12.12.2023, 10:00 - 13:00, Practical Introduction into the repository PHAIDRA, English, online
  • 13.12.2023, 10:00 - 12:00, Make the Most of Your u:cris Profile: Introduction to the Research Information System u:cris for Researchers, English, online
  • 14.12.2023, 09:00 - 12:00, Datenmanagementpläne schreiben, German, online
  • 09.01.2024, 09:00 - 16:00, Research Data Management at the University of Vienna, English, UBB, Seminarraum 1.6
  • 16.01.2024, 13:00 - 16:00, Creating Data Management Plans, English, Hofburg, Jura-Soyfer-Saal

Trainings for PhD students in the humanities

We offer specific courses in research data management for PhD students of PhilKult faculty. After these introductory courses, you can arrange individual sessions for your personal questions. Courses in winter semester 2023/24:

  • 07.11.2023, 14:00 - 16:30, Einführung ins FDM für Doktorand*innen der PhilKult, main building, UB Vortragsraum, German
  • 20.11.2023, 14:30 - 16:00 Uhr, Introduction to Research Data Management for PhilKult Doctoral Students, online, English
  • 30.11.2023 and 1.12.2023, 10:00 - 11:30, Einführung ins FDM für Doktorand*innen der PhilKult, online in two parts, German
  • 20.02.2023 and 22.02.2023, 16:30 - 18:00, Einführung ins FDM für Doktorand*innen in den Geisteswissenschaften, online in two parts, German

If you don't write your dissertation at PhilKult or HistKult, but in a related discipline, and want to take part in a course, please contact us beforehand. Usually it's no problem. You could also take part in one of the trainings for doctoral students from all faculties:

  • 07.12.2023, 10:00 - 12:30 Uhr, Research Data Management for PhD Students: Introduction to Data Planning Collection and Analysis, online, English
  • 16.01.2024, 14:00-16:30, Research Data Management for PhD Students: Introduction to Data Archiving Publishing and Reuse, online, English

The trainings take place via Moodle and Zoom or on-site. You can register on our central RDM website. All doctoral students can take part regardless of which phase their dissertation is in and they don't need to be employed by the university.

 

Individual trainings

If you need training with an discipline-specific focus or training for specific questions from your project or department, please contact us to speak about the details. These courses are free for university employees and students. If they take place within a research project, also members of the project partners can take part. By answering the three questions on our website "Build a Custom Workshop", you can define an individual training for your needs and send us a request. Examples:

  • ten-minute presentation of the research data management policy and the data stewardship programme at a staff meeting
  • half-hour introduction to data management planning for FWF projects
  • two-hour hands-on workshop on data organisation and documentation
  • two-hour workshop on the most important FDM services of the University of Vienna
  • guest lecture as part of a course for Master's students or doctoral candidates, etc.

 

Related courses by the University of Vienna

The Computer Centre (ZID) offers a wide variety of courses in the field of data management in the broader sense - e.g. data analysis with Python, introduction to R, MAXQDA Basics, reference management systems Citavi and Zotero... You can find these in the course database under the menu item "ZID-Kurse". Those courses are fee-based.

In the course database you will also find training courses in the area of data protection, e.g. a two-hour introduction to the GDPR. https://kursdatenbank.univie.ac.at/.

The MediaLab of the Faculty of Philological and Cultural Studies regularly offers courses in recording and editing audio and video files, motion capture and eye tracking. These courses are free of charge for PhilKult staff, but a small fee is charged for students and staff from other institutions. You can find the current programme at https://medialab.univie.ac.at/workshops/.

The Center for Doctoral Studies offers various "Transferable Skills" workshops für PhD students, e.g. "Research Data Management for PhD Students: Introduction to Data Planning, Collection and Analysis" and "Creative Commons: Die (richtige) Verwendung von CC-Lizenzen in der Wissenschaft". For more information and registration, see https://forschung.univie.ac.at/services/veranstaltungen-trainings/phd-candidates/trainings-for-phd-candidates/

Self-learn courses from outside the university

The community-base website Programming Historian offers a variety of free courses for humanists working with data on different skill levels, from "Introduction to the Principles of Linked Open Data", "Cleaning Data with OpenRefine" or "Preserving Your Research Data". https://programminghistorian.org/en/

The ACDH-CH offers interactive learning material for the Digital Humanities, such as data management and long-term archiving. https://howto.acdh.oeaw.ac.at/de

if you are interested in cooperative self-learning, please contact us. We would like to develop innovative course formats. Example: 30 minutes of individual self-learning alternate with discussion in the group.