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Card-index course

Data Management Plan & Open Data in Life Science - ED 43/

Responsible Faculty: Doctoral school (FBM-DOCT)

Teacher(s): Cécile Lebrand

Validity: 2018 -> 2021

No timetable defined.

Course (optional)

Annual

Teaching language(s): English
Public: Yes
Credits: 0

Objective

At the end of the course participant should be able to put in place a DMP and to share their published data in Open Access, making possible to:
-respond to the requirements of the journals and financing agencies which require shared standards for open practices in research
-anticipate in detail the management of research data, specifying how this data is going to be analysed, organised, stored, secured and shared.
-how to use the online DMP Canvas Generator tool

Content

During the first part of this workshop, participants will be taught best practices in data management and how to collect, describe, store, secure and archive research data. they will be introduced to the need for a Data Management Plan (DMP) preparation.The second half of the workshop will be dedicated to practical on Data management, where participants will learn how to fill a DMP corresponding to their research project and how to share their published data on adapted repository

Evaluation

Personal work : No
Presentation : No
Final Test : No
Participation evaluated : Yes

Bibliography

- Begley, C G, and Ioannidis, J. PA. "Reproducibility in science improving the standard for basic and preclinical research." Circulation research. 2015; 116.1: 116-126. - Chalmers I, Glasziou P. Avoidable Waste in the Production and Reporting of Research Evidence. Lancet. 2009; 374(9683): 86-89. - Freedman LP, Cockburn IM, Simcoe TS. The Economics of Reproducibility in Preclinical Research. PLoS Biol. 2015;13(6): e1002165. - Howells, D. W., Sena E.S., and Macleod, M.R. Bringing rigour to translational medicine. Nat Rev Neurol. 2014 Jan;10(1):37-43. https://www.vital-it.ch/research/software/DMPCanvasGenerator https://mantra.edina.ac.uk/ https://zenodo.org/

Programme requirements

!!! You should come to the course with a detailed list of the research data you will acquire and analyze during your thesis work, the formats associated with your data, and the equipment and software used !!!

Knowledge / competencies
To be involve in Life Sciences research
Technical
Please bring your personal laptop as we will use it for the practical part of the course

- Une deuxième édition de ce cours se tiendra le 17.10.2019/A second edition of this course will be held on 17.10.2019 -

Grant requirements

Active participation certified by the teacher.

Access requirements

Registration via the Doctoral School. Series 1.

Additional information

https://www.bium.ch/en/publication-open-access/data-management/

Unicentre - CH-1015 Lausanne - Suisse
Tél. +41 21 692 11 11
Canton de Vaud
Swiss University