Aller au contenu principal

Research data management

Introduction

Consideration needs to be given to which data will be archived and which will be shared on a data repository. The Digital Curation Centre (DCC) offers a series of questions to help you decide which data to share:

  • What are my funder's requirements?
  • Is my data sufficiently documented ?
  • Is my data compliant with the FAIR principles?
  • Does my (meta)data respect confidentiality, security and legal requirements with regard to personal and sensitive data?

It is not possible to store all research data for financial and ecological reasons.

Criteria

The criteria for retaining or destroying data largely depends on the current practice in the field of digital archiving. Choosing what to keep and what can be disposed of or deleted is always going to involve a subjective judgement, as nobody knows exactly what information is going to be wanted in the future. Data is retained for sharing purposes. This is part of a global vision of enriching research on a wider scale, for the benefit of the entire scientific community2.

Data to keep4 Data to destroy2
Relevance to the mission Poor-quality data (bad or junk data)
Legal compliance: to restrict access if necessary, or to make data public if required by funders Data that cannot be used by others
Long-term scientific or historical value Data that is easily reproducible
Uniqueness of the dataset Data without good metadata
Potential for re-use: in relation to intellectual property and ethical issues Older data that is not used and has no obvious cultural or historical value
Non-replicability Pilot, test or intermediate data
Evaluate costs Proprietary data
Complete documentation Sensitive or confidential data
Level, type, format of data  

What to deposit?

Final deposit Possible deposit Not required No deposit

Raw data obtained from analysis of physical samples

Observation data that cannot be regenerated

Original datasets

Non-original data sets not readily available online

Codebook

Original software code

Intermediate versions of analyses or code if they are potentially useful for other people or if they have been used in publications or theses

Incomplete version

Dataset already available online

Any data that contains personal identification information for human subjects

How long should data be kept?

In addition to the legal aspects, the length of time researchers are asked to keep their data varies greatly depending on data retention policies. Durations may vary according to the purpose of retention. Data with historical value will have to be kept longer than purely administrative data which can be destroyed once the legal time limit has expired.

  • For the HES-SO Valais-Wallis, there are currently no criteria, but the IT department (SINF) recommends storing data on the NAS for a maximum of 5 years. (Interview P. Schneider, Teams, 14.07.2022).
  • ETHZ and Swiss National Science Foundation recommend 10 years (minimum) of data retention after the end of the project. 

References

  1. Delamadeleine, C. (2023). Guide rapide de la gestion des données de recherche (p. e0230416). HES-SO. https://www.hes-so.ch/fileadmin/documents/HES-SO/Documents_HES-SO/pdf/open-science/liens-utiles/Brochure_Guide_Rapide_V20240214.pdf
  2. Kung, J. Y. C. et Campbell, S.(2016). What not to keep: not all data has future research value. Journal of the Canadian Health Libraries Association, 37(2).  https://doi.org/10.5596/c16-013
  3. Laplante, C. (2019). Les données de recherche : comment évaluer pour mieux conserver? Papyrus. https://urlz.fr/mGw9
  4. Melly, P. (2022). Mise en place d’un processus permettant d’inventorier, de suivre et de valoriser les données de la recherche de l’Institut santé de la Haute école de santé, HES-SO Valais-Wallis. Sonar. https://sonar.rero.ch/global/documents/323070