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| 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 | Wochentag | Zeit | Raum |
|---|---|---|---|
| Block | Siehe Einzeltermine | ||
| 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 | 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 |