Advancing Open Science through Trusted Data Repository Intersections at the World Data System
Bibliographic record
Abstract
The World Data System (WDS), a member of the International Science Council, serves a membership of over 150 trusted data repositories and related organizations. It builds on the data sharing legacy of World Data Centers that were initiated seven decades ago. Governed by a Scientific Committee, the WDS consists of an International Program Office (WDS-IPO) based in Oak Ridge, Tennessee, USA, and an International Technology Office (WDS-ITO) based in Victoria, BC, Canada. The WDS mission is to enhance the capabilities, impact, and sustainability of our member data repositories and data services. In this presentation, we outline the 2025 to 2027 Action Plan objectives, highlighting activities and collaborations that are underway or planned to progress open science, integrated data infrastructures and FAIR/CARE/TRUST Principles.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.083 | 0.110 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.009 | 0.011 |
| Scholarly communication | 0.034 | 0.056 |
| Open science | 0.005 | 0.044 |
| Research integrity | 0.005 | 0.010 |
| Insufficient payload (model declined to judge) | 0.009 | 0.006 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".