WMO Hydrological Observing System (WHOS) broker: implementation progress and outcomes
Bibliographic record
Abstract
<p>The WMO Hydrological Observing System (WHOS) is a service-oriented System of Systems (SoS) linking hydrological data providers and users by enabling harmonized and real time discovery and access functionalities at global, regional, national and local scale. WHOS is being realized through a coordinated and collaborative effort amongst:</p><ul><li>National Hydrological Services (NHS) willing to publish their data to the benefit of a larger audience,</li> <li>Hydrologists, decision makers, app and portal authors willing to gain access to world-wide hydrological data,</li> <li>ESSI-Lab of CNR-IIA responsible for the WHOS broker component: a software framework in charge of enabling interoperability amongst the distributed heterogeneous systems belonging to data providers (e.g. data publishing services) and data consumers (e.g. web portals, libraries and apps),</li> <li>WMO Commission of Hydrology (CHy) providing guidance to WMO Member countries in operational hydrology, including capacity building, NHSs engagement and coordination of WHOS implementation.</li> </ul><p>In the last years two additional WMO regional programmes have been targeted to benefit from WHOS, operating as successful applications for others to follow:</p><ul><li>Plata river basin,</li> <li>Arctic-HYCOS.</li> </ul><p>Each programme operates with a “view” of the whole WHOS, a virtual subset composed only by the data sources that are relevant to its context.</p><p><strong>WHOS-Plata</strong> is currently brokering data sources from the following countries:</p><ul><li>Argentina (hydrological & meteorological data),</li> <li>Bolivia (meteorological data; hydrological data expected in the near future),</li> <li>Brazil (hydrological & meteorological data),</li> <li>Paraguay (meteorological data; hydrological data in process),</li> <li>Uruguay (hydrological & meteorological data).</li> </ul><p><strong>WHOS-Arctic</strong> is currently brokering data sources from the following countries:</p><ul><li>Canada (historical and real time data),</li> <li>Denmark (historical data),</li> <li>Finland (historical and real time data),</li> <li>Iceland (historical and real time data),</li> <li>Norway (historical and real time data),</li> <li>Russian (historical and real time data),</li> <li>United States (historical and real time data).</li> </ul><p>Each data source publishes its data online according to specific hydrological service protocols and/or APIs (e.g. CUAHSI HydroServer, USGS Water Services, FTP, SOAP, REST API, OData, WAF, OGC SOS, …). Each service protocol and API in turn implies support for a specific metadata and data model (e.g. WaterML, CSV, XML , JSON, USGS RDB, ZRXP, Observations & Measurements, …).</p><p>WHOS broker implements mediation and harmonization of all these heterogeneous standards, in order to seamlessly support discovery and access of all the available data to a growing set of data consumer systems (applications and libraries) without any implementation effort for them:</p><ul><li>52North Helgoland (through SOS v.2.0.0),</li> <li>CUAHSI HydroDesktop (through CUAHSI WaterOneFlow),</li> <li>National Water Institute of Argentina (INA) node.js WaterML client (through CUAHSI WaterOneFlow),</li> <li>DAB JS API (through DAB REST API),</li> <li>USGS GWIS JS API plotting library (through RDB service),</li> <li>R scripts (through R WaterML library),</li> <li>C# applications (through CUAHSI WaterOneFlow),</li> <li>UCAR jOAI (through OAI-PMH/WIGOS metadata).</li> </ul><p>In particular, the support of WIGOS metadata standard provides a set of observational metadata elements for the effective interpretation of observational data internationally.</p><p>In addition to metadata and data model heterogeneity, WHOS needs to tackle also semantics heterogeneity. WHOS broker makes use of a hydrology ontology (made available as a SPARQL endpoint) to augment WHOS discovery capabilities (e.g. to obtain translation of a hydrology search parameter in multiple languages).</p><p>Technical documentation to exercise WHOS broker is already online available, while the official public launch with a dedicated WMO WHOS web portal is expected shortly.</p>
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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 | 0.054 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.044 | 0.018 |
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".