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Strumenti per l'interoperabilita : qualita dei dati, apertura, interdisciplinarita

2022· article· en· W6927686644 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
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

VenueArchivio Istituzionale della Ricerca (Universita Degli Studi Di Milano) · 2022
Typearticle
Languageen
FieldComputer Science
TopicLibrary Science and Information Systems
Canadian institutionsnot available
Fundersnot available
KeywordsMetadataInteroperabilityOpenness to experienceRelevance (law)Field (mathematics)Data management planDigital libraryPlan (archaeology)

Abstract

fetched live from OpenAlex

The article is focused on the concept of interoperability, whose relevance is also demonstrated by the existence of the Guidelines on technical interoperability of Public Administrations on which the Threeyear plan for IT in Public Administration is based. The essential condition for interoperability is the existence of metadata that exactly describe an object; this is especially important in the digital environment. There are different types of metadata – descriptive, administrative, structural, preservation, usage – and scientific communities have developed different metadata schemes that, if maintained by organisations such as the International Organisation for Standardisation, assume the status of standards. Data quality and openness are fundamental requirements for the exchange of information. Since the Ontario New Universities Library Project - ONULP (1963), libraries have been using metadata for automatic data processing; the article reviews the MARC format, Dublin Core Metadata Initiative (DCMI), the national and international standard (ISO 23950) Z39.50, the Open archival information system (OAIS). Interoperability is a recent field of study and it has not yet been fully achieved; in the digital environment, interdisciplinarity has led to the search for exchange with other contexts.

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), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.536
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0000.004
Open science0.0040.006
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.024
GPT teacher head0.238
Teacher spread0.215 · 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