{"id":43133,"date":"2026-10-15T08:52:37","date_gmt":"2026-10-15T06:52:37","guid":{"rendered":"https:\/\/smartdatamodels.org\/?p=43133"},"modified":"2026-10-14T23:55:18","modified_gmt":"2026-10-14T21:55:18","slug":"saref4watr-saref4grid-join-smart-data-models-89-candidate-models-for-water-and-smart-grid-metering","status":"publish","type":"post","link":"https:\/\/smartdatamodels.org\/index.php\/saref4watr-saref4grid-join-smart-data-models-89-candidate-models-for-water-and-smart-grid-metering\/","title":{"rendered":"SAREF4WATR &#038; SAREF4GRID Join Smart Data Models: 89 Candidate Models for Water and Smart Grid Metering"},"content":{"rendered":"<p>Smart Data Models&#8217; <a href=\"https:\/\/github.com\/smart-data-models\/Candidates\">Candidates repository<\/a> now includes two more ETSI <strong>SAREF<\/strong> extensions, both built around smart metering: <strong><code>saref4watr<\/code><\/strong> and <strong><code>saref4grid<\/code><\/strong>, together contributing<br \/>\n<strong>89 candidate models<\/strong> \u2014 the largest pair in this translation round. Both ship the full Candidates artifact set \u2014 a JSON Schema, an NGSI-LD<code> @context<\/code>, and all four example serializations \u2014 validated against its own schema.<\/p>\n<h2 id=\"saref4watr-49-models\">SAREF4WATR \u2014 49 models<\/h2>\n<p><a href=\"https:\/\/saref.etsi.org\/saref4watr\/v2.1.1\/\">SAREF4WATR<\/a> (ETSI TS 103 410-10) spans the entire water domain: natural water bodies (rivers, lakes, aquifers, glaciers), the infrastructure that moves and treats water (distribution systems, treatment plants, gauging stations, hydroelectric plants), individual field assets (pipes, valves, pumps, fire hydrants, manholes), and smart water meters with their tariff models.<\/p>\n<table>\n<thead>\n<tr>\n<th>Category<\/th>\n<th>Models<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>Natural water bodies<\/td>\n<td><code>Water<\/code>, <code>Aquifer<\/code>, <code>Estuary<\/code>, <code>Glacier<\/code>, <code>Lagoon<\/code>, <code>Lake<\/code>, <code>Ocean<\/code>, <code>River<\/code>, <code>Sea<\/code><\/td>\n<\/tr>\n<tr>\n<td>Water infrastructure<\/td>\n<td><code>DistributionSystem<\/code>, <code>StorageInfrastructure<\/code>, <code>MonitoringInfrastructure<\/code>, <code>TreatmentPlant<\/code>, <code>HydroelectricPowerPlant<\/code>, <code>GaugingStation<\/code><\/td>\n<\/tr>\n<tr>\n<td>Assets \u2014 transport\/storage\/devices<\/td>\n<td><code>Channel<\/code>, <code>Intake<\/code>, <code>Main<\/code>, <code>Manhole<\/code>, <code>Pipe<\/code>, <code>Pit<\/code>, <code>Vent<\/code>, <code>Tank<\/code>, <code>Reservoir<\/code>, <code>FireHydrant<\/code>, <code>Pump<\/code>, <code>Valve<\/code>, <code>WaterMeter<\/code><\/td>\n<\/tr>\n<tr>\n<td>Meter\/tariff model<\/td>\n<td><code>Tariff<\/code>, <code>ConsumptionBasedTariff<\/code>, <code>ThresholdBasedTariff<\/code>, <code>TimeBasedTariff<\/code><\/td>\n<\/tr>\n<tr>\n<td>Property-grouping \/ controlled-vocabulary<\/td>\n<td><code>AcceptabilityProperty<\/code>, <code>BacterialProperty<\/code>, <code>ChemicalProperty<\/code>, <code>MicrobialProperty<\/code>, <code>WaterFlowProperty<\/code>, <code>WaterUse<\/code><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p><a href=\"https:\/\/github.com\/smart-data-models\/Candidates\/tree\/master\/standards\/saref4watr\">https:\/\/github.com\/smart-data-models\/Candidates\/tree\/master\/standards\/saref4watr<\/a><\/p>\n<h2 id=\"saref4grid-40-models\">SAREF4GRID \u2014 40 models<\/h2>\n<p><a href=\"https:\/\/saref.etsi.org\/saref4grid\/v2.1.1\/\">SAREF4GRID<\/a> (ETSI TS 103 410-12) is SAREF&#8217;s extension for <strong>smart electricity metering<\/strong>, explicitly designed to mirror <strong>DLMS\/COSEM (IEC 62056)<\/strong> so its classes map cleanly onto real meter data \u2014 every COSEM object carries an OBIS code (<code>hasObis<\/code>), the same identifier engineers use on the wire. It spans the physical meter and its components, tariff\/billing automation, generic COSEM data capture, and a full remote read\/write\/action service stack.<\/p>\n<table>\n<thead>\n<tr>\n<th>Category<\/th>\n<th>Models<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>Device &amp; device management<\/td>\n<td><code>GridMeter<\/code>, <code>Firmware<\/code>, <code>NetworkInterface<\/code>, <code>Clock<\/code>, <code>BreakerState<\/code><\/td>\n<\/tr>\n<tr>\n<td>Tariff\/billing automation<\/td>\n<td><code>ActivityCalendar<\/code>, <code>SeasonProfile<\/code>, <code>DayProfile<\/code>, <code>ScriptTable<\/code>, <code>Script<\/code><\/td>\n<\/tr>\n<tr>\n<td>Data capture<\/td>\n<td><code>ProfileGeneric<\/code><\/td>\n<\/tr>\n<tr>\n<td>Power-line \/ meter property kinds<\/td>\n<td><code>EnergyAndPowerProperty<\/code>, <code>QualityProperty<\/code>, <code>MeterProperty<\/code>, <code>PowerLine<\/code><\/td>\n<\/tr>\n<tr>\n<td>COSEM remote services &amp; operations<\/td>\n<td><code>GetService<\/code>, <code>SetService<\/code>, <code>ActionService<\/code>, plus 16 related operation\/input\/output models<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p><a href=\"https:\/\/github.com\/smart-data-models\/Candidates\/tree\/master\/standards\/saref4grid\">https:\/\/github.com\/smart-data-models\/Candidates\/tree\/master\/standards\/saref4grid<\/a><\/p>\n<h2 id=\"translation-notes\">Translation notes<\/h2>\n<ul>\n<li><strong>Measurable quantities kept as open vocabularies, not exploded into entities.<\/strong> Both standards express specific measurable properties (water quality parameters, <code>ActiveEnergy<\/code>, <code>Voltage<\/code>, <code>Current<\/code>,<code> ReactivePower<\/code>&#8230;) as named individuals of a handful of grouping classes rather than as classes in their own right. Each group class was<br \/>\nmodeled once, with an enum closed to its own named-individual set (plus a <code>broaderPropertyType<\/code>\/taxonomic field where the source ontology defines a broader\/narrower relationship) \u2014 giving full fidelity to every named individual without near-duplicate entity types.<\/li>\n<li><strong>DLMS\/COSEM alignment preserved.<\/strong> SAREF4GRID&#8217;s OBIS-coding convention is carried through to the candidate schemas via <code>hasObis<\/code>, keeping the translation directly usable against real meter data rather than an abstraction that loses the wire-level identifier.<\/li>\n<li><strong>Inheritance flattened, not duplicated<\/strong>, following this repo&#8217;s established Gaia-X precedent \u2014 SAREF4WATR&#8217;s deep taxonomy of water-body and asset &#8220;kinds&#8221; each still gets its own candidate model, documenting its taxonomic role rather than repeating inherited properties.<\/li>\n<li><strong>No naming collisions found<\/strong> against existing official Smart Data Models subjects for SAREF4GRID; SAREF4WATR&#8217;s <code>Water<\/code> entity does conceptually overlap with the already-published <code>WaterQualityObserved<\/code> model \u2014 flagged, not resolved, for reviewers to reconcile at promotion time.<\/li>\n<\/ul>\n<h2 id=\"try-it-and-tell-us-whats-missing\">Try it, and tell us what&#8217;s missing<\/h2>\n<p>These are <strong>Candidates<\/strong> \u2014 first, carefully-sourced translations, not yet promoted to official Smart Data Models subjects. The <code>Water<\/code> \/<code> WaterQualityObserved<\/code> overlap above is the main open item before promotion.<\/p>\n<p>Browse the models, open an issue, or send a PR:<\/p>\n<p><a href=\"https:\/\/github.com\/smart-data-models\/Candidates\/tree\/master\/standards\/saref4watr\">https:\/\/github.com\/smart-data-models\/Candidates\/tree\/master\/standards\/saref4watr<\/a><br \/>\n<a href=\"https:\/\/github.com\/smart-data-models\/Candidates\/tree\/master\/standards\/saref4grid\">https:\/\/github.com\/smart-data-models\/Candidates\/tree\/master\/standards\/saref4grid<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Smart Data Models&#8217; Candidates repository now includes two more ETSI SAREF extensions, both built around smart metering: saref4watr and saref4grid, together contributing 89 candidate models \u2014 the largest pair in this translation round. Both ship the full Candidates artifact set \u2014 a JSON Schema, an NGSI-LD @context, and all four&#8230; <a class=\"continue-reading-link\" href=\"https:\/\/smartdatamodels.org\/index.php\/saref4watr-saref4grid-join-smart-data-models-89-candidate-models-for-water-and-smart-grid-metering\/\">More&#8230;<\/a><\/p>\n","protected":false},"author":15,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_monsterinsights_skip_tracking":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2},"jetpack_post_was_ever_published":false},"categories":[103,30],"tags":[],"class_list":["post-43133","post","type-post","status-publish","format-standard","hentry","category-energy","category-water"],"jetpack_publicize_connections":[],"jetpack_sharing_enabled":true,"jetpack-related-posts":[{"id":43130,"url":"https:\/\/smartdatamodels.org\/index.php\/saref4city-saref4inma-join-smart-data-models-35-candidate-models-for-smart-cities-and-manufacturing\/","url_meta":{"origin":43133,"position":0},"title":"SAREF4CITY &#038; SAREF4INMA Join Smart Data Models: 35 Candidate Models for Smart Cities and Manufacturing","author":"Agent","date":"18\/10\/2026","format":false,"excerpt":"Smart Data Models' Candidates repository now includes two more ETSI SAREF extensions: saref4city and saref4inma, together contributing 35 candidate models. 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SAREF4CITY \u2014 14 models SAREF4CITY\u2026","rel":"","context":"In &quot;Manufacturing&quot;","block_context":{"text":"Manufacturing","link":"https:\/\/smartdatamodels.org\/index.php\/category\/manufacturing\/"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":43132,"url":"https:\/\/smartdatamodels.org\/index.php\/saref4ehaw-saref4wear-join-smart-data-models-41-candidate-models-for-ehealth-and-wearables\/","url_meta":{"origin":43133,"position":1},"title":"SAREF4EHAW &#038; SAREF4WEAR Join Smart Data Models: 41 Candidate Models for eHealth and Wearables","author":"Agent","date":"16\/10\/2026","format":false,"excerpt":"Smart Data Models' Candidates repository now includes two more ETSI SAREF extensions, both from the health and personal-devices space: saref4ehaw and saref4wear, together contributing 41 candidate models. 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Both are official ETSI Technical Specifications, each with a normative PDF and a published Turtle\/JSON-LD\/RDF-XML ontology, and both ship the full Candidates\u2026","rel":"","context":"In &quot;Energy&quot;","block_context":{"text":"Energy","link":"https:\/\/smartdatamodels.org\/index.php\/category\/energy\/"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":43131,"url":"https:\/\/smartdatamodels.org\/index.php\/saref4agri-saref4auto-join-smart-data-models-58-candidate-models-for-precision-agriculture-and-connected-vehicles\/","url_meta":{"origin":43133,"position":3},"title":"SAREF4AGRI &#038; SAREF4AUTO Join Smart Data Models: 58 Candidate Models for Precision Agriculture and Connected Vehicles","author":"Agent","date":"17\/10\/2026","format":false,"excerpt":"Smart Data Models' Candidates repository now includes two more ETSI SAREF extensions: saref4agri and saref4auto, together contributing 58 candidate models. Both ship the full Candidates artifact set \u2014 a JSON Schema, an NGSI-LD @context, and all four example serializations \u2014 validated against its own schema. SAREF4AGRI \u2014 21 models SAREF4AGRI\u2026","rel":"","context":"In &quot;Agrifood&quot;","block_context":{"text":"Agrifood","link":"https:\/\/smartdatamodels.org\/index.php\/category\/agrifood\/"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":32325,"url":"https:\/\/smartdatamodels.org\/index.php\/besser-smart-data-json-schema-generator\/","url_meta":{"origin":43133,"position":4},"title":"BESSER Smart Data JSON Schema Generator","author":"maestro","date":"27\/02\/2026","format":false,"excerpt":"Overview The tool automates the generation of Smart Data Models (SDM) from visual models, bridging the gap between high-level domain design and technical implementation for Digital Twins and IoT ecosystems. 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