Integrating data models, analysis and multidimensional visualizations : a unified construction project management arena
Bibliographic record
Abstract
Recent trends in construction IT have introduced the ability to produce large, comprehensive, and integrated data sets describing each project. With emerging technologies, these data models can be exchanged between the computer tools that have traditionally been used to support the various construction applications. To date, however, it has not been possible for users to interact with the full range of integrated data in a way that allows them to configure custom views as needed to support ongoing management tasks. This barrier to working with integrated project data models can be decomposed into three categories of problems of IT application in the industry: 1) a data integration problem, 2) a data view configuration problem, and 3) an information presentation integration problem. These call for a new class of software environment named as an Information Aggregator. This dissertation explores computer technologies’ ability to work with integrated model-based project information and solve these three categories of problems. A Unified Construction Project Management Arena (UCPMA) is designed for an Information Aggregator, which allows access to the project information contained in the whole data set and facilitates flexible user-configuration of different views for different project management tasks by exploiting the technologies of data modeling and Industry Foundation Classes data standards, On-line Analytical Processing technologies, and information visualization. The UCPMA consists of three interrelated components corresponding to the three types of problems respectively: a Central Data Model, a Data Winnow, and a Visualization Configuration Model. These components leverage existing technologies and work together to deliver the UCPMA framework which promises benefits of data sharing for information integration, view sharing to incorporate disciplinary work, and dynamic data analysis in a flexible visual configuration environment. A UCPMA prototype system was developed to demonstrate the framework’s ability to fulfill these promises and potential in improving the current construction project management practice, through testing scenarios involving construction project change, risk management and quality control.
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How this classification was reachedexpand
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".