Universal conceptual modeling: principles, benefits, and an agenda for conceptual modeling research
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
Abstract The paper proposes universal conceptual modeling , conceptual modeling that strives to be as general-purpose as possible and accessible to anyone, professionals and non-experts alike. The idea of universal conceptual modeling is meant to catalyze new thinking in conceptual modeling and be used to evaluate and develop conceptual modeling solutions, such as modeling languages, approaches for requirements elicitation, or modeling tools. These modeling solutions should be usable by as many people and design agents as possible and for as many purposes as possible, aspiring to the ideals of universal conceptual modeling. We propose foundations of universal conceptual modeling in the form of six principles: flexibility, accessibility, ubiquity, minimalism, primitivism, and modularity. We then demonstrate the utility of these principles to evaluate existing conceptual modeling languages and understand conceptual modeling practices. Finally, we propose future research opportunities meant to realize the ideals of universal conceptual modeling.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.000 |
| 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