Fondement de la modélisation conceptuelle des bases de données géospatiales 3D
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
For the last 15 years, designing 2D databases has benefited from new or extended formalisms proposed by the GIS research community. However, three-dimensional representations have been significantly more frequent in the recent years, especially in 3D computer graphics and in 3D GIS. In spite of this fact, there exist a lot of confusion in fundamental notions and there has been insofar no proposal for solutions aimed at facilitating the conceptual modeling of 3D geospatial databases as required for GIS applications. The first difficulty met when someone wants to design a database model for 3D applications may seem bizarre but is in fact very fundamental: the very definitions of « 3 » and of « D » ! This paper proposes fundamental notions and a solution to create conceptual models of geospatial databases for 3D applications: theoretical concepts, 3D extensions for UML, integration with Perceptory spatial and spatio-temporal PVL, simple and complex cases. MOTS CLES: definitions 3D, SIG 3D, base de donnees geospatiales, modelisation conceptuelle, UML 3D, PVL 3D, Perceptory.
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 | 0.001 | 0.000 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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