MétaCan
Menu
Back to cohort
Record W176454583

Requirements elicitation using BPM notations: focusing on the strategic level representation

2011· article· en· W176454583 on OpenAlexaffabout
Carlos Monsalve, Alain April, Alain Abran

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicBusiness Process Modeling and Analysis
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsProcess managementRequirements elicitationComputer scienceProcess (computing)Business processBusiness process managementKnowledge managementRequirements engineeringBusinessWork in processEngineeringOperations managementSoftware
DOInot available

Abstract

fetched live from OpenAlex

Abstract:- Business process models (BPM) can be useful for requirements elicitation, among other uses. Since the active participation of all stakeholders is a key factor for successful requirements engineering, it is important that BPM be shared by all stakeholders. Unfortunately, organizations may end up with inconsistent BPM not covering all stakeholders ’ needs and constraints. The use of multiple levels of abstraction (MLA), such as at the strategic, tactical and operational levels, is often used in various process-oriented initiatives to facilitate the consolidation of various stakeholders ’ needs and constraints. This article surveys the use of MLA in recent BPM research publications and reports on a BPM action-research case study conducted in a Canadian organization, with the aim of exploring the usefulness of the strategic level.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.034
metaresearch head score (Gemma)0.055
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.034
Threshold uncertainty score0.180

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0340.055
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.003
Science and technology studies0.0020.002
Scholarly communication0.0060.008
Open science0.0010.005
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0020.001

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 head0.546
GPT teacher head0.333
Teacher spread0.213 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

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

Citations15
Published2011
Admission routes2
Has abstractyes

Explore more

Same topicBusiness Process Modeling and AnalysisFrench-language works237,207