An operation-based approach to the communication of spatial data quality in GIS
Bibliographic record
Abstract
Spatial data used in Geographic Information Systems (GIS) are prone to uncertainties that can undermine their usability. Improving the GIS users' awareness of these uncertainties requires improvements in the management and communication of the quality information provided with spatial data. Current tools for communicating data quality information in commercial GIS are rudimentary, and alternative tools--mainly developed and applied in academia--remain to be implemented in commercial GIS. -- This work develops an alternative operation-based approach to the communication of quality information in GIS. Communicating quality information is studied in the context of GIS operations. A review of GIS operations, one of the main components in GIS applications is performed. Based on the study of GIS operations and quality information, a conceptual link is established between the two components. Using this link, a system is designed to retrieve and communicate applicable quality elements to GIS users. The designed system is then implemented as a prototype in a commercial GIS software, and its usefulness is tested among GIS users.
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.
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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.005 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".