This repository contains the materials for a remote study course on Open Science and Research Data Management.
This file provides a basic overview of the course. For more details, see the course handbook.
If you want to get an overview of the course:
- check out the course outline,
- read the notes from each seminar, or
- read the summary of our experience in implementing open science.
This course is intended for early-stage researchers in STEM subjects and their supervisors.
Supervisors are strongly recommended to accompany the course.
- To educate students about modern approaches to open science data management.
- To enable and motivate students to implement these approaches in their projects.
- Students are able to recognize “open” and “closed” science and communicate the advantages of open science.
- Students can identify the main steps in the FOSTER diagram.
- Students are able to publish interconnected data objects, boosting their visibility and impact to the scientific community.
- Students are able to list the main tools for open science that enable them to achieve the FAIR and R5 goals. (e.g. F - DOIs, A - GitHub, I - modular software, R - ...).
- Students create a data management plan for their projects.
Figure 1. Promoting openness at different stages of the research process (Open Science and Research Initiative, 2014)
The course includes 5 lectures, 6 self-directed study activities, a workshop, and two deliverables.
The course lasts approximately 12 weeks.
The basic course requires 61 hours of study time:
- 11 contact hours, and
- 50 self-study hours.
Depending on the university policy, this workload can be translated to 2.5 ECTS points.
The extended course adds 30 hours of self-study to the basic course. It is designed for students who need to add hours for ECTS points requirements.
These extra activities are listed in the table below under the heading, Extra credit hours and described in each self-study readme.md under the heading, For extra credit. It should be possible to complete the extended course in the same time window as the basic course.
| Week | Seminar | Self-study | Assignment | Contact Hours | Self-study hours | Extra credit hours |
|---|---|---|---|---|---|---|
| 0 | Introducing open science | 1 | 1 | |||
| Background reading | 4 | 4 | ||||
| 2 | Guiding principles | 1 | 1 | |||
| Is your group’s work FAIR? | 4 | 4 | ||||
| 4 | Open science and intellectual property | 1 | 1 | |||
| Implementing Open Science | 4 | 4 | ||||
| 6 | If a tree falls in the forest... Communicating your science | 1 | 1 | |||
| Communications strategies | 4 | 4 | ||||
| Implementation case study | 8 | 4 | ||||
| 8 | What are data management plans and why do they matter? | 2 | 1 | |||
| Draft your data management plan | 1 | 12 | 6 | |||
| 10 | Workshop: Your experiences of implementing open science | 4 | 4 | |||
| Revise your data management plan | 4 | 4 | ||||
| 12 | Data management plan | 1 | ||||
| TOTAL | 11 | 50 | 30 |
You are welcome to reuse or remix the material in this repository under the terms of the license(s) applied to that material.
- The GitHub repository including e.g.
README.mdfiles is licensed under the MIT license (see the license file for details). - Presentations for each seminar may be separately licensed by their contributors. Please check those documents for license terms. Note that the license for the presentations should be considered to extend to the source material for compiled documents (i.e. LaTeX source code is covered under the license for the PDF). Please also contact the author(s) directly to discuss reuse of their materials.
If you need help reusing the materials, or would like to check if you can use it, please raise an issue.
- Andy Clifton, U. Stuttgart
https://orcid.org/0000-0001-9698-5083
- Nikola Vasiljevic, DTU
https://orcid.org/0000-0001-9698-5083