Kies de Nederlandse taal
Course module: B-MINRDM
Introduction to Research Data Management for Life Sciences
Course infoSchedule
Course codeB-MINRDM
ECTS Credits3
Category / LevelM (M (Master))
Course typeCourse
Language of instructionEnglish
Offered byFaculty of Science; Graduate School of Life Sciences; Graduate School of Life Sciences;
Contact persondr. ir. B. van Breukelen
dr. ir. B. van Breukelen
Other courses by this lecturer
Course contact
dr. ir. B. van Breukelen
Other courses by this lecturer
Teaching period
JAAR  (05/09/2016 to 31/08/2017)
Teaching period in which the course begins
Time slot-: Timeslot not applicable
Study mode
RemarkSend an e-mail to the course coordinator (Armel Lefebvre,
Enrolment periodfrom 30/05/2016 up to and including 28/08/2017
Enrolling through OSIRISNo
Enrolment open to students taking subsidiary coursesNo
Waiting listNo
Course goals
At the end of the course, students should have a profound understanding of:
1) Build simple entity-relationships and relational data models
2) Query data with SQL
3) Retrieving information from a relational database via a programming language (Python)
4) Working with public datasets, transferring data from repositories or supplementary material and being able integrate them in a data model.
The course Introduction to Research Data Management gives practical insights on Data Management for scientists. Basic knowledge of relational databases, entity-relationships models, relational models and SQL with MySQL is provided during the course. The programming language used to process data from and to the database is Python.
Proper management of research data is a requirement by funding agencies, publishers or academic institutions. This course provides the technical keys to understand how to model, structure and query data. Benefits of having these skills are numerous: a better insight on how to manage research data and comply with research data management policies, more efficiently store and reuse important data for computational experiments and awareness of the current techniques available to make these tasks easier. The modeling part of the course is focused on communicating the important aspects of datasets to colleagues or an audience via simple models that can be included in posters or other types of publications.   
The course is divided into six modules:
  1. Research Data Management and Databases
  2. Data and Models
  3. Starting with MySQL and Workbench
  4. Structuring and Querying Data
  5. Storing and Processing Data with Python
  6. Working with data repositories
Next, more practical insights are given, mainly about:
  • Data modeling with E-R and relational schemas
  • SQL (mainly DML)
  • Working with MySQL and Workbench (modeling)
  • Working with publicly available data by modeling, importing and integrating data into relational databases.
  • Working with data schemas and public repositories
The final grade consists of:
  • Online quizzes (10%), three attempts per quiz. Min. score is 6 per quiz.
  • Two minor assignments (20%), No minimum score. There is one opportunity to resubmit one of the two minor assignments to improve its grade.
  • A final assignment (70%), Min. score is 5. There is one opportunity to resubmit the final assignment is the grade is less than 6.
Min. final grade to pass the course: 5.5

Literature/study material used:
Course content and material is hosted on
A virtual machine (Ubuntu Linux) containing all the necessary software is available for students.
Alternatively, students may choose to install the required software on their own machine. In that case, they will need a computer environment with:
  • Minimum: Python 2.7.9 or Python 3.4.x/3.5.x
  • Jupyter (IPython) notebook
  • MySQL 5.7.X branch
  • MySQL Workbench CE 6.3.X
  • Python pandas (
  • Windows users can install WinPython ( containing all the necessary modules by default
Entry requirements
You must meet the following requirements
  • Enrolled for a degree programme of faculty Faculty of Science
Prerequisite knowledge
Python basics: type of variables (int, string…), data structures (tables, lists, dictionaries), functions, control statements (if, while…). The knowledge of any other programming language at an identical level is sufficient.
Command line basics: the course requires some command line manipulation. Having some experience with working in a shell (bash, powershell…) will help.
Required materials
Instructional formats
Computer practical





Final result
Test weight100
Minimum grade5.5

Kies de Nederlandse taal