Workflow-Based Construction Research Data Management and Dissemination
Bibliographic record
Abstract
Sharing research data is necessary for collaboration within a research network and is required by funding agencies, such as the National Science Foundation (NSF), that enforce the scientific method and ethics associated with data management and sharing. However, methods and infrastructure for supporting construction research data management are currently underdeveloped; emphasizing the need for developing effective and efficient means for managing and sharing research data. A review of existing data management models reveals that there is currently no effective universal system for sharing the data obtained from construction research endeavours. This paper presents electronic product and process management systems (EPPMS) as a construction research data management and sharing approach. The developed EPPMS is a web-based system that utilizes workflows that can automate the collection, authorization, and dissemination of construction research data. A comparative analysis of the developed system to the existing web-based cloud and web-based share point systems indicates that an EPPMS offers a more fitting solution for construction research data management.
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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 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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".