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Record W2014425628 · doi:10.1109/sera.2010.16

Representing Unique Stakeholder Perspectives in BPM Notations

2010· article· en· W2014425628 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 institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsComputer scienceNotationStakeholderMathematicsPolitical scienceArithmetic

Abstract

fetched live from OpenAlex

Evidence shows that proposals for new modeling notations emerge and evolution of current ones are becoming more complex, often in an attempt to satisfy the many different modeling perspectives required by each stakeholder. This paper presents a method to identify the specific notation construct requirements, at multiple levels of abstraction, which satisfy the needs of a stakeholder when performing a specific task. Initially the focus is on two different stakeholders: software engineers (SE) and business analysts(BA), and one specific software engineering activity: requirements eliciting and analysis. The specific body of knowledge of the two stakeholders (Software Engineering Book of Knowledge (SWEBOK) for the SE, and Business Analysis Body of Knowledge (BABOK) for the BA) are used to identify each stakeholder specific notation construct requirements, at multiple levels of abstraction, in order to propose a simplification of their notation and constructs set. This paper presents solution avenues to simplify business process modeling notations by identifying the specific constructs preferred by different stakeholders.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.695
Threshold uncertainty score0.667

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.052
GPT teacher head0.261
Teacher spread0.209 · 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

Citations16
Published2010
Admission routes1
Has abstractyes

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