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Record W2139629857 · doi:10.1109/re.2007.32

Goal-Oriented Conceptual Database Design

2007· article· en· W2139629857 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
FieldComputer Science
TopicAdvanced Software Engineering Methodologies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsComputer scienceDatabase schemaConceptual schemaDatabase designSoftware engineeringRequirements analysisDatabaseSchema (genetic algorithms)Conceptual designData modelingProgramming languageSoftwareInformation retrievalHuman–computer interaction

Abstract

fetched live from OpenAlex

We present details of a goal-oriented process for database requirements analysis. This process consists of a number of steps, spanning the spectrum from high-level stakeholder goal analysis to detailed conceptual schema design. The paper shows how goal modeling contributes to systematic scoping and analysis of the application domain, and subsequent formal specification of database requirements based on this domain analysis. Moreover, a goal-oriented design strategy is proposed to structure the transformation from the domain model to the conceptual schema, according to a set of user defined design issues, also modeled as goals. The proposed process is illustrated step-by-step using a running example from the design of a real-world, industrial biological database. We also report early progress towards building full tool support, by presenting a prototype that captures and stores design sessions in a queryable form. This facility makes it possible to answer questions that are hard, if not impossible, to answer using existing methodologies for database design.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.814
Threshold uncertainty score0.388

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.066
GPT teacher head0.316
Teacher spread0.250 · 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