Grid-Enabling the Global Geodynamics Project: Automatic RDF Extraction from the ESML Data Description and Representation via GRDDL
Bibliographic record
Abstract
An eXtensible Markup Language (XML) based data model for the Global Geodynamics Project (GGP) has been previously developed. Mindful of the need to incorporate metadata into the description and representation, a Resource Description Framework (RDF) based approach is introduced that extends the previous data model. Specifically, use of RDF allows relationships to be described and represented, and will eventually result in an ‘informal ontology’. The bottom-up approach makes use of GRDDL (Gleaning Resource Descriptions from Dialects of Languages) - a vehicle that allows for the extraction of RDF from XML according to rules. Because there exists some latitude in such extractions, complimentary top-down approaches will be required - especially when reconciling with formal ontologies. From this ‘information science’ perspective, GGP data has the potential to factor in the broader context being defined by the ‘new geoinformatics’.
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.
How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".