Development of standard-based information requirements for the facility management of a canteen
Bibliographic record
Abstract
Facility Management (FM) is an essential practice for the operational phase of built assets. FM requires a vast range of data arising from diverse activities, which demands tools and processes for data collection and management. The Building Information Modeling (BIM) methodology implies an integrated information management process which helps in effective communication and information flow. Therefore, adopting BIM to support FM (BIM-FM) has become the subject of academic and industry interest. When BIM methodology is implemented, information models are the main information repository, while information requirements set the guidelines for their development. The EN ISO 19650 series and EN 17412-1 are currently the most recent standards in the European context to assist the development of information requirements. However, there is still a lack of research on their detailed application to real-case scenarios. In this context, the present article cooperates with the broad adoption of BIM-FM by presenting the establishment of information requirements to inform the development of an information model for the ongoing operational phase of a university canteen, focusing on developing Exchange Information Requirements (EIR), and including other activities of ISO19650’s information management process to demonstrate the applicability of the requirements. The procedure applies the Level of Information Need (EN 17412-1) as the framework for defining the extent and granularity of the information requirements, and it employs the IFC schema to establish the required alphanumerical information. The paper thoroughly discusses the decision-making process and its implications, working as a detailed demonstration of the standards applied in a case study. The results demonstrate the efficiency of the purpose-driven process based on standardization, and the information model developed from the requirements is proven to deliver the required information accurately. Ultimately, the paper results in a robust source for process replication on FM real-case scenarios.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.029 | 0.044 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".