The Landscape of Research Data Repositories in France
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This chapter discusses research data repositories in France with an analysis of the typology of repositories, their scientific domains and their quality. In 2015, most data repositories were located in four countries, namely the United States, Germany, the UK and Canada, which then accounted for 70% of the institutions in the international re3data directory. Several types of repositories can be distinguished, depending on their content, subject matter, governance or institutional affiliation. Re3data distinguishes between two types of devices: the data provider if it offers research data and its metadata, and/or the service provider if it harvests the metadata of the research data from the data providers in order to create value-added services. The ambition of the National Plan for Open Science is “to ensure that the data produced by French public research is progressively structured in accordance with the FAIR principles (Findable, Accessible, Interoperable, Reusable) preserved and, when possible, opened”.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.017 | 0.017 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it