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Record W2143594197 · doi:10.1109/policy.2011.20

Lifecycle Management of Relational Records for External Auditing and Regulatory Compliance

2011· article· en· W2143594197 on OpenAlexaff
Ahmed A. Ataullah, Frank Wm. Tompa

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicBusiness Process Modeling and Analysis
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsComputer scienceBusiness processBusiness ruleWorkflowData integrityBusiness process managementBusiness process modelingDatabaseAuditArtifact-centric business process modelBusiness logicRelational databaseProcess managementWork in processBusiness

Abstract

fetched live from OpenAlex

Transactional business records are subject to a wide array of regulatory and auditing requirements. The problem of converting task specific business policies to database level constraints is challenging due to the immense complexity of corporate workflows and record lifecycles. In this paper we present a modeling framework for identifying business processes and record lifecycles within relational database systems that supports the automatic generation, implementation and verification of low level data management constraints. Our modeling language allows users to identify states of business processes within a relational database system and subsequently to enforce a broad set of conditional business rules based on the particular path that a business process has taken in the model. Our approach is unique in that it offers a single unified layer for process modeling and implementing complex workflow based constraints, temporal access control constraints, and records retention restrictions. Furthermore we propose the notion of "business process integrity" as a layer above traditional database integrity constraints, which combines conditional access control and general purpose temporal integrity constraints, to assure external auditors that each business record in the database has followed a legal path to its current state.

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.

How this classification was reachedexpand

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: Empirical
Teacher disagreement score0.535
Threshold uncertainty score0.363

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 communication0.0000.000
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 head0.091
GPT teacher head0.248
Teacher spread0.157 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2011
Admission routes1
Has abstractyes

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