Willing or unwilling to share primary biodiversity data: results and implications of an international survey
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
Abstract Biodiversity science and conservation increasingly depend on the sharing and integration of large amounts of data, but many researchers resist sharing their primary biodiversity data. We recently conducted an international survey to ascertain the attitudes, experiences, and expectations regarding biodiversity data sharing and archiving of researchers. The results show that whereas most respondents are willing to share article‐related biodiversity data, more than 60% of respondents are unwilling to share primary data before publishing. Results indicate an underdeveloped culture of data sharing and several major technological and operational barriers. A major concern for researchers is appropriate benefits from data sharing. Most respondents would accept data archiving policies of journals. Researchers also express concerns about how to easily and efficiently deal with data and data quality in public databases. Expectations for biodiversity databases include standardization of data format, user‐friendly data submission tools, formats for different types of data, and coordination among databases. The survey results provide suggestions for improving data sharing and archiving by individual scientists, organizations, journals, and databases.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.028 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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