TU Delft Research Data Management 101 course
Authors/Creators
- 1. Delft University of Technology
Contributors
Other (18):
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Plomp, Esther1
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Turkyilmaz-van der Velde, Yasemin n1
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Andrews, Heather1
- Love, Jeff1
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Ilamparuthi, Santosh1
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Dintzner, Nicolas1
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Wang, Yang1
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den Heijer, Kees1
- Barrera Coronel, Maribel1
- Singotani, Roséane Cathy1
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Dunning, Alastair1
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Teperek, Marta1
- Will, Nicole1
- Jones, Sian1
- Romero Herrera, Natalia1
- Agahari, Wirawan1
- Dedoussi, Irene1
- New Media Centre | TU Delft1
- 1. Delft University of Technology
Description
Regardless of the research field, there are various ways of collecting and documenting data. Poor data management can result in losing time trying to locate data files, loss of data on a larger and smaller scale, failure to keep track of new versions and updates, failure to provide accessibility of data to other researchers for reproducibility and replicability, etc. All this can lead to more effort and frustration for researchers. Therefore, it is essential for all researchers to start thinking about managing research data correctly at the outset of any research project.
This six-module course called Research data Management 101 (RDM 101), is aimed at PhD candidates (especially in their first year) who require a hands-on introduction to Research Data Management (RDM) and Data Management Plans (DMPs).
The course was created in a collaborative effort of the Research Data Services team of TU Delft Library with TU Delft Data Stewards, the Education Support team at TU Delft Library, the TU Delft New Media Centre and TU Delft researchers.
This is a three weeks blended course, which has been offered since October 2020 by the Research Data Services of TU Delft Library in an online mode (due to COVID measures).
The course has been delivered using the Learning Management System (LMS) Brightspace. However, the aim of publishing all the structure, content and materials of the course is to facilitate the adoption and adaptation to other learning platforms.
The RDM 101 course is structured in six successive modules that can be taken at the own pace of the course participant within 3 weeks. i.e. two modules per week. Each week also includes an assignment (data flow map: https://doi.org/10.5281/zenodo.6325938) and a virtual class to engage the participants in practice and to discuss the highlights of each module.
The Modules of the RDM 101 course are:
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Module 1. The importance of RDM
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Module 2. The Essentials of research data
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Module 3. FAIR principles
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Module 4. Realizing FAIR data
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Module 5. How to plan for RDM (using a DMP tool)
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Module 6. Reflection on RDM strategy
Parts of the content of this course are based on:
Holmstrand, K.F., den Boer, S.P.A., Vlachos, E., Martínez-Lavanchy, P.M., Hansen, K.K. (Eds.) (2019). Research Data Management (eLearning course). doi: 10.11581/dtu:00000047
The assignment of this course is based on the ‘Data Flow Kit’ - https://dataflowtoolkit.dk/. A separate publication of the assignment is found at https://doi.org/10.5281/zenodo.6325938
Files
RDM101_Course_Material.zip
Additional details
Related works
- Is supplemented by
- Lesson: 10.5281/zenodo.6325938 (DOI)
References
- Holmstrand, K.F., den Boer, S.P.A., Vlachos, E., Martínez-Lavanchy, P.M., Hansen, K.K. (Eds.) (2019). Research Data Management (eLearning course). doi: 10.11581/dtu:00000047
- Research Cycle - Edinburgh Napier University. https://staff.napier.ac.uk/services/information-services/research-cycle/pages/home.aspx
- ReadMe file template - Research Data Management Service group - Cornell University - https://data.research.cornell.edu/content/readme
- Data Flow Kit - https://dataflowtoolkit.dk/