Defining Enterprise Architecture: A Systematic Literature Review
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.
Bibliographic record
Abstract
In recent years, there has been an increasing interest among researchers and practitioners concerning Enterprise Architecture (EA). Despite this increase, several studies have reported a lack of common understanding in EA. Some specific expressions like lack of common terminology, lack of shared meaning and fragmented literature have been frequently used to describe this lack. However, very few systematic studies have been conducted to gain a better understanding about the nature and the extend of these definition differences. This study presents a Systematic Literature Review considering journal articles that contain explicit definitions of EA. 145 definitions were identified and analyzed in order to determine their similarities and differences. The analysis was guided by concepts from the field of terminology. The findings of this study show that there are significant divergences of multiple kind between definitions. The next steps for the EA community would be to achieve something comparable to MacGregor's Theory X and Theory Y model or Mintzberg's schools of thought.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it