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Record W4293213091 · doi:10.17705/1cais.05037

Information Systems Analysis and Design: Past Revolutions, Present Challenges, and Future Research Directions

2022· article· en· W4293213091 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

VenueCommunications of the Association for Information Systems · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicBusiness Process Modeling and Analysis
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsField (mathematics)Data scienceAgile software developmentInformation systemDevOpsComputer scienceProcess (computing)Key (lock)Management scienceSystems engineeringEngineeringSoftware engineeringSoftware deployment

Abstract

fetched live from OpenAlex

Systems Analysis and Design (SAND) is undoubtedly a pillar in the field of Information Systems (IS). Some researchers have even claimed that SAND is the field that defines the Information Systems discipline and is the core of information systems. The past decades have seen the development of Structured SAND methodologies and Object-Oriented Methodologies. In the early 1990s, key players in the field collaborated to develop the Unified Modeling Language and the Unified Process. Agile approaches followed, as did other dynamic methods. These approaches remain heavily employed in the development of contemporary information systems. At the same time, new approaches such as DevOps and DevSecOps continue to emerge. This paper curates these trends in SAND. It reviews past and present SAND research, discusses current challenges, and provides insights that can assist SAND researchers in identifying future SAND research streams and important future research directions.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.977
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.000
Scholarly communication0.0000.003
Open science0.0010.001
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 head0.072
GPT teacher head0.290
Teacher spread0.218 · 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