Development of a web-based collaborative PPGIS to support municipal planning
Bibliographic record
Abstract
The use of computing technologies to support workflows related to the planning and development of a municipality dates back to the late 1950s. The main boosts of computing technologies and applications, Geographic Information System (GIS) and Geographic Information Technology (GIT), in relation to a planning and decision-making context, became evident when the use of Public Participation GIS (PPGIS) started in the 1980s. Collaboration is an important part of many tasks involving people from different organizations, in which maps often play a central role in informing and improving debates and facilitating the decision-making process. It allows diverse stakeholders to share and view maps or spatial images interactively over the Web in real-time, among other platforms. The geospatial collaboration technology not only provides an effective solution to decision makers, but also facilitates scientific and public debates with real-time geospatial information. More recently, some efforts have been made using open map services to develop simple map-sharing applications. However, little has been done on designing and developing such online open source tools in the context of municipal planning and management. Further, a literature review indicates the lack of scientific publications on empirical studies of their practical applications. Web-based PPGIS applications, among others, have now been widely recognized as an efficient and integral part of sound planning and development processes to support public participation. However, GIS alone cannot make the planning process more participative. Demands for Web-based PPGIS tools, integrated with other information and computer-supported cooperative work (CSCW) tools, have rapidly become increasingly important for supporting collaborative participation during a decision-making process. Therefore, the establishment of public participation in GIS-based applications is an optimistic step taken by the researchers that are progressively working on municipal planning projects that incorporate public participation. The main aim of this research is to provide a Collaborative PPGIS (Co-PPGIS) to enhance public participation in municipal planning related workflows. A research prototype has been developed and its usability is evaluated by adopting the evaluation criteria for the research prototype, as only proper testing will demonstrate whether the prototype is usable or the Co-PPGIS design framework is successful in meeting end-users’ requirements.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.007 |
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".