Archiving Primary Data: Solutions for Long-Term Studies
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
The recent trend for journals to require open access to primary data included in publications has been embraced by many biologists, but has caused apprehension amongst researchers engaged in long-term ecological and evolutionary studies. A worldwide survey of 73 principal investigators (Pls) with long-term studies revealed positive attitudes towards sharing data with the agreement or involvement of the PI, and 93% of PIs have historically shared data. Only 8% were in favor of uncontrolled, open access to primary data while 63% expressed serious concern. We present here their viewpoint on an issue that can have non-trivial scientific consequences. We discuss potential costs of public data archiving and provide possible solutions to meet the needs of journals and researchers. The recent trend for journals to require open access to primary data included in publications has been embraced by many biologists, but has caused apprehension amongst researchers engaged in long-term ecological and evolutionary studies. A worldwide survey of 73 principal investigators (Pls) with long-term studies revealed positive attitudes towards sharing data with the agreement or involvement of the PI, and 93% of PIs have historically shared data. Only 8% were in favor of uncontrolled, open access to primary data while 63% expressed serious concern. We present here their viewpoint on an issue that can have non-trivial scientific consequences. We discuss potential costs of public data archiving and provide possible solutions to meet the needs of journals and researchers. Public data archiving is the archiving of primary data used in publications so that they can be preserved and made accessible to all online. Public data archiving is increasingly required by journals. However, the costs of public data archiving might be underestimated, in particular with respect to long-term studies. Long-term studies have been responsible for the answers to many important questions in evolution and ecology which could only be answered through following the life-histories of individuals for decades. Several papers have been published in favor of public data archiving, but a more balanced viewpoint is necessary to allow a discussion to emerge on a code of ethics and ways to preserve and protect the data, encourage the initiation and continuation of long-term studies, and meet the requirements of the whole scientific community. Public data archiving is the archiving of primary data used in publications so that they can be preserved and made accessible to all online. Public data archiving is increasingly required by journals. However, the costs of public data archiving might be underestimated, in particular with respect to long-term studies. Long-term studies have been responsible for the answers to many important questions in evolution and ecology which could only be answered through following the life-histories of individuals for decades. Several papers have been published in favor of public data archiving, but a more balanced viewpoint is necessary to allow a discussion to emerge on a code of ethics and ways to preserve and protect the data, encourage the initiation and continuation of long-term studies, and meet the requirements of the whole scientific community.
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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.014 |
| Open science | 0.006 | 0.009 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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