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Towards Ontology-Driven User Experience Assessment of Collaborative Modeling Tools

2025· article· W4417251066 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Language
FieldComputer Science
TopicUsability and User Interface Design
Canadian institutionsMcMaster UniversityToronto Metropolitan University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsUser experience designData explorationUser interfaceSPARQLUser modelingPath (computing)

Abstract

fetched live from OpenAlex

Collaborative Modeling (CM) tools increasingly offer advanced editing features, such as live co-editing, embedded chat, and automated reasoning. Yet, the impact of these features on the user experience (UX) of modeling is less understood. In this paper, we explore the relationship between CM and UX by developing a mapping between existing CM and UX ontologies. We propose CMUX Explorer, an ontology-driven assessment tool that enables tool builders to identify CM features with UX impact. The conversational front-end allows for natural-language interactions, which CMUX Explorer translates to SPARQL queries, executes them against the ontology, and returns ranked, interpretable recommendations to guide design decisions. Importantly, our approach supports continuous, semi-automated improvement of the ontology, leading to more precise recommendations over time. Through this work, we pave a path towards computer-aided design of UX-aware collaborative modeling tools.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.833
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0020.001
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 head0.065
GPT teacher head0.369
Teacher spread0.304 · 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

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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