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

Semester Frühjahrsemester 2022
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. The focus will be on quantitative research data. 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, dissemination 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
Nina Brunner
Marek Kwiatkowski

 

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
Unterrichtssprache Englisch
Einsatz digitaler Medien kein spezifischer Einsatz

 

Intervall Block
Datum 21.04.2022 – 02.06.2022
Zeit Siehe Detailangaben
Datum Zeit Raum
Donnerstag 21.04.2022 09.00-17.00 Uhr Swiss TPH Neubau, Seminarraum 2
Freitag 29.04.2022 09.00-17.00 Uhr Swiss TPH Neubau, Seminarraum 2
Donnerstag 05.05.2022 09.00-17.00 Uhr Swiss TPH Neubau, Seminarraum 2
Freitag 06.05.2022 09.00-13.00 Uhr Swiss TPH Neubau, Seminarraum 2
Donnerstag 02.06.2022 09.00-17.00 Uhr Swiss TPH Neubau, Seminarraum 2
Module Doktorat Epidemiologie: Empfehlungen (Promotionsfach Epidemiologie)
Lehrveranstaltungen Masterstudium Infektionsbiologie (Masterstudium: Infektionsbiologie)
Modul: Biostatistics and Computing (Masterstudium: Epidemiologie)
Leistungsüberprüfung Lehrveranst.-begleitend
Hinweise zur Leistungsüberprüfung Assignments. Students are expected to complete and submit all assignments in time to be awarded the credit points.
An-/Abmeldung zur Leistungsüberprüfung An-/Abmelden: Belegen resp. Stornieren der Belegung via MOnA
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

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