Perspectives on Open Science and scientific data sharing:an interdisciplinary workshop.
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
Looking at Open Science and Open Data from a broad perspective. This is the idea behind "Scientific data sharing: an interdisciplinary workshop", an initiative designed to foster dialogue between scholars from different scientific domains which was organized by the Istituto Italiano di Antropologia in Anagni, Italy, 2-4 September 2013.We here report summaries of the presentations and discussions at the meeting. They deal with four sets of issues: (i) setting a common framework, a general discussion of open data principles, values and opportunities; (ii) insights into scientific practices, a view of the way in which the open data movement is developing in a variety of scientific domains (biology, psychology, epidemiology and archaeology); (iii) a case study of human genomics, which was a trail-blazer in data sharing, and which encapsulates the tension that can occur between large-scale data sharing and one of the boundaries of openness, the protection of individual data; (iv) open science and the public, based on a round table discussion about the public communication of science and the societal implications of open science. There were three proposals for the planning of further interdisciplinary initiatives on open science. Firstly, there is a need to integrate top-down initiatives by governments, institutions and journals with bottom-up approaches from the scientific community. Secondly, more should be done to popularize the societal benefits of open science, not only in providing the evidence needed by citizens to draw their own conclusions on scientific issues that are of concern to them, but also explaining the direct benefits of data sharing in areas such as the control of infectious disease. Finally, introducing arguments from social sciences and humanities in the educational dissemination of open data may help students become more profoundly engaged with Open Science and look at science from a broader perspective.
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 | 0.064 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.050 | 0.107 |
| Open science | 0.056 | 0.173 |
| 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