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Record W2132412756 · doi:10.1109/iwsess.2009.5068457

Metamodel for privacy policies within SOA

2009· article· en· W2132412756 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

Venuenot available
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicBusiness Process Modeling and Analysis
Canadian institutionsWestern University
Fundersnot available
KeywordsService-oriented architectureInteroperabilityMetamodelingComputer scienceOASIS SOA Reference ModelArchitecturePrivacy policyInformation privacyPrivacy by DesignComputer securityService (business)Web serviceWorld Wide WebSoftware engineeringBusiness

Abstract

fetched live from OpenAlex

As Service-Oriented Architecture (SOA) continues to grow as a viable approach to systems development, so too does the number of services available. The strength of services in an SOA environment to provide interoperability comes at the cost of reduced privacy, as more interactions between autonomous services require more information to be exchanged. In this paper we define a metamodel for privacy policy creation and comparison based on fair information practices introduced around the world to protect the privacy of individuals. We develop criteria for the comparison of the elements that compose the policies, creating hierarchical relationships between those elements that could not otherwise be directly compared. An example of two policies being compared is presented to demonstrate how this comparison can be done. We believe this definition of how to create and compare privacy policies forms a strong foundation from which a comprehensive solution to SOA privacy can be built.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.770
Threshold uncertainty score0.513

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 communication0.0000.001
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 head0.039
GPT teacher head0.265
Teacher spread0.227 · 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

Citations24
Published2009
Admission routes1
Has abstractyes

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