Afterword#

Beautiful

The Turing Way project illustration by Scriberia. Zenodo. http://doi.org/10.5281/zenodo.3332807

We hope you enjoyed the course, and you feel prepared to implement RDM best practices in your research project!

You probably found that this is a lot of information to process, don’t panic! If you have worked on the activities of the data flow maps or getting started with your DMP, you can use them to prioritise where to start.

These are our recommendations:

🔍 Start from the less challenging practices, get used to incorporating them in your daily workflows and then move on to incorporating the next maybe a bit more challenging ones
🔍 Permanently go back to your data flow map or your DMP to evaluate what is working and what needs to be improved, and update the plan accordingly
🔍 Talk about research data and software with your peers, with your supervisor. Ask others for their experiences, tips and tricks. Maybe discussing research data and software in your team/project meetings can help you and others

Thanks for following the course! Keep taking care of the data and software of your project, you do relevant research, so your data and software matter!

Provide some feedback?

If you would like to provide some feedback about this Jupyter book version of the course, please use this form (feedback is anonymous): https://forms.gle/6jzX4oV1UtKw2sgT9

Do you need further help?#

Remember that if you have additional questions, you can always contact your Faculty Data Stewards: https://www.tudelft.nl/library/research-data-management/r/support/data-stewardship/contact

You can also get in touch with the TU Delft Digital Competence Centre (DCC) for getting support on making research data FAIR, improve research software, and apply computing practices to increase the efficiency of the research process: https://www.tudelft.nl/en/library/library-for-researchers/library-for-researchers/setting-up-research/dcc

The Library also provides a website with a lot of useful information about RDM: https://www.tudelft.nl/en/library/research-data-management

More courses on research data and software#

Training for Researchers

https://shop.tudelft.nl/media/TUDelft/TU_Delft_Essentials_3.jpg

TU Delft Library in collaboration with the Faculty Data Stewards and the DCC team offer more courses, workshops and groups of practice about reproducible data and software.

Explore this website

Personal Data & Human Subjects in Research

https://irb.upenn.edu/wp-content/uploads/2023/03/Social-media-applications-on-a-phone-scaled.jpg

Recommended if you are collecting personal data in your research project. This is a self-paced and entirely online course. It is open for TU Delft researchers, PhD candidates, MSC students and support staff.

Explore this website

eScience Center

https://www.esciencecenter.nl/wp-content/uploads/2023/02/netherlands-escience-center-logo-RGB-1024x282.png

For those working with code/software, you can always check and attend the workshops of the NL eScience center.

Explore this website

R Cafe

https://d2k0ddhflgrk1i.cloudfront.net/Library/Collecties/iconen/R_cafe_logo.png

For those using R as their programming language or those who would be interested in starting to use it, you can join the R cafe sessions.

Explore this website

How to cite this course?#

Martinez-Lavanchy, P.M., van Schöll, Pim, & Zormpa, Eirini. (2022, July 8). TU Delft Research Data Management 101 course. Zenodo. https://doi.org/10.5281/zenodo.6325919

@misc{martinez_lavanchy_p_m_2022_6325919,
  author       = {Martinez-Lavanchy, P.M. and
                  van Schöll, Pim and
                  Zormpa, Eirini},
  title        = {TU Delft Research Data Management 101 course},
  month        = jul,
  year         = 2022,
  publisher    = {Zenodo},
  doi          = {10.5281/zenodo.6325919},
  url          = {https://doi.org/10.5281/zenodo.6325919}
}