Data Archive
Generating research data and software, as well as publishing scientific results, requires significant time and effort. It is therefore important to properly archive research outputs. Archiving data ensures that the definitive version of the data is preserved in a secure location for the long term and retained in accordance with the applicable retention periods.
A data archive is a service that provides long-term preservation, curation, and access to research data collections with ongoing value. An archive (noun) refers to the data collection itself, while to archive (verb) refers to engaging in the activities that ensure that data is properly selected, stored accessed, and mantained for keeping the data integrity and usability over time.
Retention Periods​
Retention period refers to the time or date, starting from the completion of the study, when data could be disposed.
| Type of data | Recommended retention period |
|---|---|
| Research data underpinning a publication | Minimum of 10 years |
| Medical / clinical research data | 20 years |
| Personal data (GDPR) | Once personal data is no longer necessary, permanently and completely destroy or anonymize it. Check also the information box below. |
| Data from student projects | To be discussed with supervisor. In principle, data can be deleted after project completion. For student thesis and reports, check the page on TU/e retention periods for education. |
When personal data underpins a publication, the research-integrity retention obligation can extend retention beyond what data minimisation would allow on its own. This retention period should be informed to participants via the informed consent form.
If there is any uncertainty about the appropriate retention period, please consult a Data Steward, particularly when special-category personal data is involved.
Available solutions​
RAPS​
RAPS or Research Archival Package Solution is a closed TU/e data archive for the data underpinning peer-reviewed journal publications.
For RAPS, the information in the data package should correspond to the information in the same article that reports the results.
FAQ​
If I am co-author of a publication, am I also responsible for archiving that data, or is the main author responsible?​
You should keep, at least, an archive of your own contribution (input and output). Ideally, the main author or corresponding institution maintains a complete archive that co-authors can point to. Coordinate where possible to avoid fragmentation across institutions.
What is the difference between raw, processed, and analysed data?​
Raw data are the original data that you have collected but have not yet processed or analysed. For instance: audio files, archives, observations, field notes and data from experiments. Data you have not collected yourself and that you are reusing, may be considered raw data.
Processed data are the data that you have digitised, translated, transcribed, cleaned, validated, checked and/or anonymised.
Analysed data are the models, graphs, tables, texts and so on that you have created based on the raw and the processed data, and that are intended to aid in the discovery of useful information, the presentation of conclusions, and decision-making.
For more information, please see Research Data page.
Does TU/e have an archive for research data used in scientific publications?​
Yes. Data and other relevant documents associated with scientific publication can be archived in the TU/e Research Archival Package Solution.