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48613-01 - Lecture with practical courses: Research Data Management 2 CP

Semester spring semester 2023
Course frequency Every spring sem.
Lecturers Aurelio Di Pasquale (aurelio.dipasquale@unibas.ch)
Manuel Hetzel (manuel.hetzel@unibas.ch, Assessor)
Malin Michelle Ziehmer-Wenz (malin.ziehmer@unibas.ch)
Content 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
Learning objectives 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.
Bibliography 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)
Comments Additional lecturers:
Moniek Bresser
Marek Kwiatkowski
Alexandra Kulinkina

 

Admission requirements 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.
Language of instruction English
Use of digital media No specific media used

 

Interval Weekday Time Room
Block See individual dates

Dates

Date Time Room
Thursday 20.04.2023 09.15-17.00 Swiss TPH Neubau, Seminarraum 4
Friday 21.04.2023 09.15-13.00 Swiss TPH Neubau, Seminarraum 4
Thursday 27.04.2023 09.15-17.00 Swiss TPH Neubau, Seminarraum 5
Friday 05.05.2023 09.15-17.00 Swiss TPH Neubau, Seminarraum 5
Friday 12.05.2023 09.15-17.00 Swiss TPH Neubau, Seminarraum 5
Modules Courses: Master Infection Biology (Master's Studies: Infection Biology)
Doctorate Science Epidemiology: Recommendations (PhD subject: Epidemiology)
Module: Biostatistics and Computing (Master's Studies: Epidemiology)
Assessment format continuous assessment
Assessment details Satisfactory completion of assignments. Students have to complete and submit all assignments satisfactorily and in time to be awarded the credit points.
Assessment registration/deregistration Reg.: course registration, dereg: cancel course registration
Repeat examination no repeat examination
Scale Pass / Fail
Repeated registration as often as necessary
Responsible faculty Faculty of Science, studiendekanat-philnat@unibas.ch
Offered by Schweizerisches Tropen- und Public Health-Institut

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