1.5 EC
Semester 2, period 5, 6
5224PSDM2Y
This course is part of the Professional Skills learning trajectory and it focuses on the soft skills around data handling and has two parts: data management and data visualization.
Data management
These days, proper and safe data management is important in many professions and a data management plan can help with that. In this course you will learn about the principles and best practices in order to be able to develop or adjust your own data management plan and put it in the context of open science.
Data visualization
Effective and accurate data visualization, independent of the technical details, is often not explicitly thought and with the same data set different stories can be told. In this course you will learn about the design principles (the good, the bad and the ugly) that can be used and make better informed choices when visualizing data.
|
Activity |
Hours |
|
|
Seminars |
6 |
|
|
Self study |
36 |
|
|
Total |
42 |
(1.5 EC x 28 uur) |
Requirements of the programme concerning attendance (OER-B):
Additional requirements for this course:
Attendance is mandatory, absence has to be reported to the coordinator to find a solution.
| Item and weight | Details |
|
Final grade | |
|
Research Data Management Plan | Must be ≥ pass |
|
exercise 2.2 reflection | Must be ≥ pass |
|
Data visualization | Must be ≥ pass |
|
exercise 4.2 reflection | Must be ≥ pass |
A pass must be obtained for both assignments and reflections exercises.
Through a rubric in Canvas.
If students want additional feedback on their assignment, they can email the coordinator.
Planning (study load: 4-6 hours a week)
There are 4 exercises (for practice), 2 assignments (for a grade) and 2 reflections. Please note there are weeks in between when there is no class due to holidays (see datanose.nl for the schedule).
The 'Regulations governing fraud and plagiarism for UvA students' applies to this course. This will be monitored carefully. Upon suspicion of fraud or plagiarism the Examinations Board of the programme will be informed. For the 'Regulations governing fraud and plagiarism for UvA students' see: www.student.uva.nl
Week 1
In the first week, we'll discuss data management, through an in-class exercise (exercise 1.1 ReproHack) you'll find out why this is so important to researchers and organizations. In the second half of our first seminar you'll start working on your own data management plan (assignment 1) using either your own (old) data or a fictional set. This is the first assignment that you'll be graded on. Please familiarize yourself with the rubric.
Week 2
Work on your assignment and prepare for the second seminar by reading the texts on data management and open science in the syllabus and complete exercise 2.1a. During the seminar, we'll discuss the principles of open science (exercise 2.1b) and you'll use these insights to improve your research data management plan. In the second half of our second seminar there will be time to get feedback on your assignment. There are reflective questions (exercise 2.2).
Week 3
By the third week, your assignment is due and we expect you to prepare for the third seminar by reading the texts on types of graphs and design principles in the syllabus and completing exercise 3.1a. In this exercise you'll look for examples of data visualizations; one you deem good, one bad and one ugly. These you'll present and discuss in the third seminar. During the third seminar we'll discuss many examples of data visualizations in order to come up with a joint language of effective design principles of data visualization (exercise 3.1b). You'll use these principles to draw up and discuss your own data visualization in the second half of the third seminar (exercise 3.2). This can form the basis of the data story that you'll make for the last assignment. A data story includes visuals and text and it conveys the story you want to tell with your data. Examples of data stories are a scientific poster presentation (Links to an external site.), a corona dashboard (Links to an external site.), an infographic in the newspaper (Links to an external site.) (use your UvA VPN if at home).
Week 4
Before the fourth and final seminar you'll have to come up with a first draft to get feedback on from a fellow student in class (exercise 4.1a). And of course, you yourself will review a fellow student's data story and give feedback (exercise 4.1b). Did you get your data story across effectively? In the second half of the seminar there will be time to ask questions and make changes to your data story (assignment 2). Afterwards, you should complete the final reflective questions (exercise 4.2).
Week 5
Your last assignment is due. Also, please fill in the evaluation form as this is the first time we are providing this course and we want to improve on it in the years to come.
The schedule for this course is published on DataNose.