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Ontology‐Based Metadata

2006· article· en· W2130938743 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

VenueTransactions in GIS · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicGeographic Information Systems Studies
Canadian institutionsSimon Fraser University
FundersCanadian Institutes of Health Research
KeywordsMetadataOntologyComputer scienceGeospatial metadataInformation retrievalUpper ontologyContext (archaeology)Metadata repositoryWorld Wide WebData scienceMeta Data ServicesSemantic WebGeographyEpistemology

Abstract

fetched live from OpenAlex

It is even more remarkable to some of us that up to this point, there has been no thoroughgoing discussion by GIS practitioners and theorists about the epistemology of their subject, the ontology of their objects, and the political commitments embedded in their practices. ( Pickles 1997 , p. 364) Abstract Metadata are an extant mechanism for conveying ontological information about semantic data. Metadata have the advantage of being institutionally and structurally ensconced in GIS. At present, however, they lack fields to express information beyond the technical and geometric domain. This paper describes a framework for the creation of extended metadata for non‐spatial attributes, with the goal of incorporating ontological context. We use an informatics interpretation of ontology which refers to the total universe of discourse associated with a given attribute (database field). In other words, an ontology is the possible range of meaning offered by an encoded field. Current ontology research in GIScience has focused on data structuring and modelling. Implementation of these schemes demands restructuring of existing relational database models. An alternative is to extend current metadata schemes (e.g. ISO 19115) to include context‐based and tacit information about semantic attributes. Such ontology‐based extended metadata permits data selection and interoperability decisions that are ultimately more defensible. We have developed eight preliminary fields to add to existing metadata frameworks that will enable ontological context to travel with the data. This paper illustrates a preliminary implementation based on the integration of non‐commensurate cadastral data. The results illustrate the value of ontology‐based metadata in highlighting descriptive and substantive differences between similar classification systems. Recognition of semantic heterogeneity is the basis for creating defensible data linkages between multiple datasets. The development of ontology‐based metadata is profoundly different from the current trend to incorporate ontological context at the model level in GIScience. It is pragmatic, however, in that it presents a vehicle for incorporating use‐context with data in a manner that is accessible; requires little re‐engineering; and is intuitively understood by GIS users. Moreover, ontology‐based metadata are a mechanism for addressing Pickles’ (1997 ) concern about the ontology of spatial objects in GIS.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.950
Threshold uncertainty score0.962

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.026
GPT teacher head0.298
Teacher spread0.272 · 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