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Merging Architectural, Engineering, and Construction Ontologies

2009· article· en· W2155928344 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Computing in Civil Engineering · 2009
Typearticle
Languageen
FieldComputer Science
TopicSemantic Web and Ontologies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsOntologyInteroperabilityComputer scienceUpper ontologySoftware engineeringDomain (mathematical analysis)IntegratorOntology-based data integrationHeuristicOntology alignmentProcess ontologySystems engineeringInformation retrievalWorld Wide WebEngineeringDomain knowledgeArtificial intelligenceMathematics

Abstract

fetched live from OpenAlex

Ontologies have emerged as a means of facilitating semantic interoperability among computer systems. However, recognizing that no single universally agreed-on ontology can ever be defined for a domain, a tool that allows ontologies to interoperate becomes essential to semantic interoperability. This paper presents an ontology integrator (Onto-Integrator) for facilitating ontology interoperability within the architectural, engineering, and construction (AEC) domain. The Onto-Integrator offers a heuristic for ontology merging, including the merging of concept taxonomies, relations, and axioms. Unlike existing tools, the integrator addresses ontology merging requirements that are specific to the AEC domain. The integrator heuristic was implemented into a prototype Web-based tool and was evaluated through a focus group.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.269
Threshold uncertainty score0.490

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.007
GPT teacher head0.215
Teacher spread0.208 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it