Towards the Semantic Grid: A State of the Art Survey of Semantic Web Services and their Applicability to Collaborative Design, Engineering, and Procurement
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
Today, organizations within the engineering and manufacturing domains place as much emphasis on the management and flow of knowledge through a value chain as they do commodities that are more tangible in nature. For example, parts suppliers in the Canadian automotive sector are often asked to collaborate with auto manufacturers in designing and engineering their product, instead of simply producing and supplying it. Such fundamental changes in the overarching economics of this industry have led to a greater focus on collaboration, both in terms of communicating across geographic divides to design components, as well as new requirements to merge heterogeneous data stores in order to manage this distributed procurement process. Our work on this project centred on finding solutions to the above by surveying the state of the industry, as well as assessing the potential employability of related tools in the workplace. It was concluded that the Access Grid (a low-cost, open-source videoconferencing platform) held significant potential to facilitate the high-quality sharing of audiovisual material, while semantic technologies (the “semantic web” and “semantic web services”) represented a feasible solution to the issues of data integration. When combined, these technologies form the “semantic grid”, the focus of this paper. Overall, it is concluded that the past and present business success of this ICT in the information management sector may, with future work, link databases with the visualization interface to provide concurrent cost-benefit analyses.
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 | 0.002 | 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 | 0.003 | 0.002 |
| 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 it