Data Management 2026 B

Welcome to the course – Data Management (2026)

FOR ALL FACULTIES: TECH, ENG, SUND, AND SSH

In this course you will get a thorough introduction to the value and importance of Data Management and how to do it. Data management is becoming more and more of a requirement by directives, institutions, and funders. The aim is to help you with your own data management by providing background, practice, and tools.

Our focus will be on 2 main topics and how they connect.

·         The FAIR-principles for research data

·         The Data Management Plan (template)

The course will introduce the FAIR principles, why they are important, and how to implement them in your research. We will go through the topics of the typical data management plan, you will work on your own as part of the homework, and we will discuss each other’s experiences.

The course is split in two workshops. 1 full day and ½ a day two weeks apart.

Before the 1^st day of teaching, 4 hours of homework is expected to get an introduction to the topics and materials. Before the 2^nd day, you are expected to do 15 hours of homework drafting a DMP and a dataset-exercise. At sign-up, you will be enrolled in both workshops, and attendance at both are required to pass.  

Teaching day #1                             

·         Welcome and introduction to the course

·         Data Management and the FAIR principles (Findable, Accessible, Interoperable and Reusable) 

·         Exercise LEGO #1

·         What is a DMP and why is it important? 

·         Introduction to AAU generic DMP template's 8 topics 

·         Exercise LEGO #2

·         Introduction to homework. 

Teaching day #2 

·         Welcome and introduction to day 2

·         Workshop and discussion on homework pt. 1: FAIRification of a dataset.

·         Workshop and discussion on homework pt. 2: Begin your own Data Management Plan 

·         Final remarks, experiences, epiphanies, concerns, and more from all.

Homework before 1^st day of teaching (estimated time requirement: 4 hours):  

To get a basic understanding of data management and the FAIR principles, please look at the following links and make the exercises prior to the first day of teaching: 

1.      Welcome to DeiC DMP. - Deic DMP is a tool for creating DMP’s including institutional and funding-oriented templates such as Horizon Europe. Please create an account before the first day of teaching. Here is a guide for creating an account and an introduction to the AAU generic DMP template: DMP AAU template.mp4.  

2.      https://howtofair.dk/what-is-fair/ - An introduction to the FAIR principles. Please read the information and watch these 3 videos: module 1 (Introduction), module 2 (FAIR principles) and module 3 (Data Management Plans). 

3.      https://howtofair.dk/why-fair/ - An introduction to the purpose of knowing and using the FAIR principles. Please read the information and watch the four videos with Susanna and Barend. 

4.      https://howtofair.dk/how-to-fair/ - An introduction to how you can make your research data more FAIR by taking you through 6 FAIRification practices. Please read the information and watch the 4 videos with research projects used as examples. Moreover, you must also read the 6 attached documents in the bottom of the link. 

5.      https://fair-office.at/lernen-sie-mehr/?lang=en – 9 videos lasting between 5-10 minutes. Please watch 8 of the 9 videos prior to the course. Skip the video on metadata, as it is in German. 

6.      https://howtofair.dk/quiz/ - in this link, you will find three quizzes. One on qualitative, one on quantitative and one on sensitive quantitative data. Please go through all three and please note, that you will not be held accountable for you correct/incorrect answers during the course. This part is only for homework.

Homework before 2^nd day of teaching (estimated time requirement: 15 hours in total): 

The following two exercises need to be done between the 1^st and 2^nd day of teaching: 

1. FAIRification of data 

For this exercise you must use this dataset; https://doi.org/10.5061/dryad.7d7wm37wp. 

Please evaluate the FAIRness of the dataset, using following guide to refresh the principles; “How FAIR are your data[1] ”; https://doi.org/10.5281/zenodo.1065991. Go through each of the letters in FAIR and assess, whether the dataset follows the four principles. 

2. Start writing your own Data Management Plan 

Start writing a DMP on your Ph.D. project. Use the AAU generic template to write your DMP. You will find the template at DMPonline. You do not have to hand in your data management plan or send us anything. We will talk about everyone's data management plans in groups on day 2 of teaching.  

We do not expect a full DMP. The first many versions of your DMP are reflections of what you know and where you are in the process. You cannot write what you do not know, but you can reflect, plan, and consider how to find out. If you need inspiration to start writing your DMP, you can have a look at the following materials for inspiration.

Materials for inspiration: 

1.    Guidance from Science Europe on what to write in your Data Management Plan:  https://scienceeurope.org/media/4brkxxe5/se_rdm_practical_guide_extended_final.pdf  

2.     Browse through existing Data Management Plans for inspiration: 

-          REPAIR draft Data Management Plan 

-          Data Management Plan: Empowering Indigenous Peoples and Knowledge Systems Related to Climate Change and Intellectual Property Rights 

Additional reading 

Below you will find suggestions for additional reading materials. This is not part of the 15 hours dedicated for homework and therefore voluntary.   

-          A FAIRy tale: https://doi.org/10.5281/zenodo.2248200      

-          FAIR Principles: Interpretations and Implementation Considerations: https://doi.org/10.1162/dint_r_00024 

-          A basic introduction to Data management; Managing and sharing research data: a guide to good practice. Corti, Louise, author. 2020; 2nd edition – you can get this book at AUB. 

Organizer:  

CLAAUDIA CLAAUDIA - Aalborg University 

Lecturers:  

Freya Vamberg Delfs
Kamilla Hall Kragelund 
Thomas Andersen 
Dennis Aagaard Pedersen 

ECTS:  1 

Date: 10 and 23 April, 2026

Place: Aalborg University

 Accommodation: There will be coffee and tea during the day. You will have to bring your own lunch. Alternatively, you can buy food at the canteen.

Number of seats:  14 

 Deadline:  20 March 2026 

Important information concerning PhD courses: 

There is a no-show fee of DKK 3,000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before the start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start of the course.

For external PhD students: This course is a general course and is prioritised for PhD Students enrolled at Aalborg University. If there are available seats, PhD students from other universities will be accepted. You will be notified shortly after the deadline if you have been accepted.

To attend courses at the Doctoral School in Medicine, Biomedical Science and Technology you must be enrolled as a PhD student.

We cannot ensure any seats before the deadline for enrolment, all participants will be informed after the deadline, approximately 3 weeks before the start of the course.

For inquiries regarding registration, cancellation or waiting list, please contact the PhD administration at phdcourses@adm.aau.dk When contacting us please state the course title and course period. Thank you.