Digital data scholarship for wetlab scientists

Target audience

Wet-lab scientists - from industry and academia - and graduate students in the Life Sciences who wish to improve their digital scholarship on data handling. Some basic experience with programming and scripting languages like python, perl, R, matlab, etc. are an advantage, but not needed. The  course is also relevant for Data Stewards who have to support Life Science Researchers.

Course description

The course will introduce the trainees to important concepts of data stewardship. We start with a general introduction covering the data life cycle, the FAIR principles and a definition of data stewardship and data stewards.

We will pass the stages of the data life cycle in more detail in the training modules of this 3 day course.

  • Day 1: Why use a datamanagement plan and what for? On day one trainees will investigate data management plans, which types are there and how they should be used.
  • Day 2: Mastering the data chaos during the research phase. On day two the course highlights how to work with data during the research phase, explaining how to create well formatted data which helps in the second module of day two to make data interoperable already during the active research phase.
  • Day 3: Boost your visibility and get cited for your data! On day three trainees will have an in-depth at persistent identifiers, different use cases and types of identifiers. Finally we are closing the data life cycle by making data fit for sharing, archiving and publishing. The training is organised by DTL and delivered as a joint effort by DTL partners.

The full programme of the Course can be found under the Course Programme Tab

Objectives

Gaining knowledge on:

  • Research data management Life Cycle
  • FAIR principles
  • FAIR data stewardship

Practical experience in:

  • Data management planning
  • Cleaning data (Step 1 of making data FAIR)
  • Semantic interoperability between data
  • Archiving and publishing of data
  • Persistent identifiers and their use cases

Required skills

Some basic experience with programming and scripting languages like python, perl, R, matlab, etc. are an advantage, but not needed.

Required software

Please bring your own laptop. For day 1 and 3 you will need a web browser. Day 2 requires to install some software: 

Further preparatory instructions for day 2 will follow shortly before the course starts.

Trainers (name, affiliation)

  • Jasmin Boehmer, UMCU Bioinformatics Expertise Core, Center for Molecular Medicine, University Medical Center Utrecht
  • Cees Hof, DANS
  • Celia van Gelder, Dutch Techcentre for Life Sciences
  • Christine Staiger, Dutch Techcentre for Life Sciences
  • Santosh Ilamparuthi, Faculty of Electrical Engineering, Mathematics and Computer Science, TU Delft
  • Esther Plomp, Faculty of Applied Sciences, TU Delft
  • Andra Waagmeester, Owner of Micelio
  • Frederieke Ehrhart, Department of Bioinformatics NUTRIM School of Nutrition and Translational Research in Metabolism Faculty of Health, Medicine and Life Sciences, Maastricht University

Partners for this course

This course is part of the Data Analysis and Stewardship theme of Helis Academy and is organised by DTL and DTL collaborators.  The partners in this Helis Academy theme are:  DTL, VIB, TU/e and Maastricht University and info about other courses in the theme of Data Analysis and Stewardship can be found on the Helis Academy website and on the Helis Academy page on the DTL website.

Courses in the other 5 themes of Helis Academy can be found via the Helis Academy website

Registration form

The registration form for the Course can be found under the Register Tab

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Source: https://www.aanmelder.nl/helis-fair-data-stewardship-course