WorldFAIR (D2.3) Cross-Domain Interoperability Framework (CDIF) (Report Synthesising Recommendations for Disciplines and Cross-Disciplinary Research Areas)
Bibliographic record
Abstract
The Cross-Domain Interoperability Framework (CDIF) is designed to support FAIR implementation by establishing a ‘lingua franca’, based on existing standards and technologies to support interoperability, in both human- and machine-actionable fashion. CDIF is a set of implementation recommendations, based on profiles of common, domain-neutral metadata standards which are aligned to work together to support core functions required by FAIR. This report presents a core set of five CDIF profiles, which address the most important functions for cross-domain FAIR implementation. Discovery (discovery of data and metadata resources) Data access (specifically, machine-actionable descriptions of access conditions and permitted use) Controlled vocabularies (good practices for the publication of controlled vocabularies and semantic artefacts) Data integration (description of the structural and semantic aspects of data to make it integration-ready) Universals (the description of ‘universal’ elements, time, geography, and units of measurement). Each of these profiles is supported by specific recommendations, including the set of metadata fields in specific standards to use, and the method of implementation to be employed for machine-level interoperability. A further set of topics is examined, establishing the priorities for further work. These include: Provenance (the description of provenance and processing) Context (the description of ‘context’ in the form of dependencies between fields within the data and a description of the research setting) Perspectives on AI (discussing the impacts of AI and the role that metadata can play) Packaging (the creation of archival and dissemination packages) Additional Data Formats (support for some of the data formats not fully supported in the initial release, such as NetCDF, Parquet, and HDF5). In each of these topics, current discussions are documented, and considerations for further work are provided. Visit WorldFAIR online at http://worldfair-project.eu. WorldFAIR is funded by the EC HORIZON-WIDERA-2021-ERA-01-41 Coordination and Support Action under Grant Agreement No. 101058393.
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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 | 0.066 | 0.058 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.008 |
| Bibliometrics | 0.017 | 0.021 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.024 | 0.019 |
| Open science | 0.013 | 0.014 |
| Research integrity | 0.032 | 0.011 |
| Insufficient payload (model declined to judge) | 0.034 | 0.036 |
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".