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Record W4403967408 · doi:10.16995/dm.17137

Transforming the Vocabulaire de la Sigillographie into a Semantic Web Resource

2024· article· en· W4403967408 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueDigital Medievalist · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicIntellectual Property Law
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

This paper describes the current situation in the area of digital sigillography that focuses on creating data sets. It observes the possibility of aligning these data sets and suggests developing the Vocabulaire Internationale de la Sigillographie (created in 1990) further for this purpose. It presents the conversion of the printed version into an SKOS (Simple Knowledge Organisation System) resource. It highlights the opportunities offered by Semantic Web technologies, which can begin with sharing descriptive vocabularies. Data interchange between the various European sigillographic resources can be further promoted by shared semantics. This paper proposes a CIDOC-CRM-compliant OWL ontology built on top of the VIS. This is organized around the events of creating the matrix, applying the matrix, handling the impression (e.g., destroying, cutting off), conservation and description. The proposed basic entities map well to existing major seal databases, with the effect that the French Sigilla and the British DigiSig database could merge, and a common European database of medieval seals seems possible.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.921
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0010.000
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 head0.014
GPT teacher head0.289
Teacher spread0.276 · 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