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48613-01 - Vorlesung mit Übungen: Research Data Management 2 KP

Semester Frühjahrsemester 2023
Angebotsmuster Jedes Frühjahrsem.
Dozierende Aurelio Di Pasquale (aurelio.dipasquale@unibas.ch)
Manuel Hetzel (manuel.hetzel@unibas.ch, BeurteilerIn)
Malin Michelle Ziehmer-Wenz (malin.ziehmer@unibas.ch)
Inhalt Research data management concerns the organisation of data, from the time of data generation through the entire research cycle leading to archiving of data and dissemination of findings. Research data management can be a complex issue, but done correctly from the start, it will save a lot of time and hassle at the time when the data has to be analysed for a publication or thesis.

In this course we will discuss and illustrate with practical examples ways to create, organise, share, and look after your research data. Our focus will be on quantitative research data and epidemiological field studies - though the principles apply to other types of data as well. We will contextualise the topics with requirements of funding bodies regarding the driving principle of data as a public good and ethical issues such as data protection and confidentiality.

Summary of the course content:
- Data flow and audit trail
- Data collection, cleaning, storing
- Electronic data capture incl. form design in ODK
- Database formats, relational databases
- Version control, GitHub
- Data Management Plan
- Data protection and integrity
- Data storage, repositories, publishing, Open Science
- Data visualization
Lernziele Accurate, reliable and accessible research data forms the basis of our scientific work. In this course, students will learn the essentials of managing research data starting from data collection (with a focus on electronic data capture) to data cleaning, analysis, publishing and archiving.
Literatur Useful literature:
- S. Juul: Take good care of your data. Aarhus University, 2011. (available online: https://ph.au.dk/fileadmin/ph/Uddannelse/Software/TakeCareJan2011.pdf)
- S. Juul & M. Frydenberg: An Introduction to Stata for Health Researchers. (Chapter 18)
- C.O. Wilke: Fundamentals of Data Visualization. O'Reilly 2019. (available online: https://serialmentor.com/dataviz)
Bemerkungen Additional lecturers:
Moniek Bresser
Marek Kwiatkowski
Alexandra Kulinkina


Teilnahmebedingungen 1) Students need their own laptop with Stata software installed
2) Basic working knowledge of Stata (e.g. from course 'Biostatistics') is a requirement. As an alternative, students who are well versed in R can use this software - though less support will be provided in this course.
Unterrichtssprache Englisch
Einsatz digitaler Medien kein spezifischer Einsatz


Intervall Block
Datum 20.04.2023 – 12.05.2023
Zeit Siehe Detailangaben
Datum Zeit Raum
Donnerstag 20.04.2023 09.15-17.00 Uhr Swiss TPH Neubau, Seminarraum 4
Freitag 21.04.2023 09.15-13.00 Uhr Swiss TPH Neubau, Seminarraum 4
Donnerstag 27.04.2023 09.15-17.00 Uhr Swiss TPH Neubau, Seminarraum 5
Freitag 05.05.2023 09.15-17.00 Uhr Swiss TPH Neubau, Seminarraum 5
Freitag 12.05.2023 09.15-17.00 Uhr Swiss TPH Neubau, Seminarraum 5
Module Doktorat Epidemiologie: Empfehlungen (Promotionsfach Epidemiologie)
Lehrveranstaltungen Masterstudium Infektionsbiologie (Masterstudium: Infektionsbiologie)
Modul: Biostatistics and Computing (Masterstudium: Epidemiologie)
Leistungsüberprüfung Lehrveranst.-begleitend
Hinweise zur Leistungsüberprüfung Satisfactory completion of assignments. Students have to complete and submit all assignments satisfactorily and in time to be awarded the credit points.
An-/Abmeldung zur Leistungsüberprüfung Anm.: Belegen Lehrveranstaltung; Abm.: stornieren
Wiederholungsprüfung keine Wiederholungsprüfung
Skala Pass / Fail
Wiederholtes Belegen beliebig wiederholbar
Zuständige Fakultät Philosophisch-Naturwissenschaftliche Fakultät, studiendekanat-philnat@unibas.ch
Anbietende Organisationseinheit Schweizerisches Tropen- und Public Health-Institut