OGC Web Processing Service and Table Joining Service: A land suitability rating system implementation case
Bibliographic record
Abstract
In the geospatial domain, the Open Geospatial Consortium (OGC) has recently released two new web service interface specifications designed to enable spatial data provision, calculations and modeling on the Internet. These specifications are known as the Web Processing Service (WPS) and Table Joining Service (TJS). A WPS can be used to enable access to any sort of calculation or model, although it is primarily intended to operate on spatially referenced data. The data required by the service can be available locally, or delivered across a network. There is no limit on the complexity of model which can be delivered via WPS. WPS specifies a standardized way to make a model available as all three conventional types of web services, namely KVP GET, XML POST, and as SOAP. As such, it allows the client to choose their preferred method of implementation. WPS essentially defines a way to wrap a model so that it can be executed over a network. It has been implemented in JAVA, Python, and Ruby, and has recently started to become popular in the geospatial GRID computing community. TJS specifies an XML encoding of tabular polygon attribute data that is known as geolinkable data. This encoding includes a substantial amount of metadata that completely describes the data contents. The xml based geolinkable data format is thus useful as a way to store and exchange data suitable for polygon-based modeling. The Land Suitability Rating System for Canada (LSRS) assesses climate, landscape, and soil factors in order to rate the suitability of land for growing crops. Currently, the list of crops includes alfalfa, brome, canola, corn, soybeans, and spring-seeded small grains. LSRS has been under development since the mid 1980's, and implemented in a variety of desktop software. Recently, the model was rewritten and deployed as suite of web services, based in part on recent and emerging standards from the OGC. This paper will use the LSRS use case to demonstrate the utility of the WPS and TJS and to describe the principles and generic approaches using OGC web services for computer network based modeling and modeling chaining.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.005 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".