{"id":18619,"date":"2025-06-08T02:58:51","date_gmt":"2025-06-08T00:58:51","guid":{"rendered":"https:\/\/smartdatamodels.org\/?page_id=18619"},"modified":"2025-06-08T03:15:32","modified_gmt":"2025-06-08T01:15:32","slug":"validate-your-payloads-against-smart-data-models-powering-real-world-use-cases","status":"publish","type":"page","link":"https:\/\/smartdatamodels.org\/index.php\/validate-your-payloads-against-smart-data-models-powering-real-world-use-cases\/","title":{"rendered":"Validate Your Payloads Against Smart Data Models \u2013 Powering Real-World Use Cases!"},"content":{"rendered":"<p data-sourcepos=\"51:1-51:383\">Are you working with data in the realm of IoT, Smart Cities, or other domain-specific applications, and often find yourself grappling with inconsistent data formats or complex ontologies? The <strong>Smart Data Models initiative<\/strong> is here to streamline your work, and we&#8217;re excited to announce a new tool that brings our models from theory to practical application: <strong>payload validation! Always\u00a0 available at the Main menu -&gt; Validate Payload Against SDM.<\/strong><\/p>\n<p data-sourcepos=\"53:1-53:34\"><strong>Why is this important for you?<\/strong><\/p>\n<p data-sourcepos=\"55:1-55:295\">In large-scale European research and development projects, within the FIWARE ecosystem, or when you&#8217;re simply seeking robust data models where standards are lacking or traditional ontologies fall short, ensuring data consistency is paramount. Our new validation tool helps you achieve just that.<\/p>\n<p data-sourcepos=\"57:1-57:54\"><strong>How it Works: Simple and Effective Data Validation<\/strong><\/p>\n<p data-sourcepos=\"59:1-59:244\">Our new service allows you to easily validate your data payloads against the comprehensive collection of Smart Data Models. The system intelligently identifies the appropriate data model(s) by examining the <code>type<\/code> attribute within your payload.<\/p>\n<p data-sourcepos=\"61:1-61:46\"><strong>Ready to try it out? Here&#8217;s how to use it:<\/strong><\/p>\n<p data-sourcepos=\"63:1-63:64\">You can access the validation service directly via a simple URL:<\/p>\n<p data-sourcepos=\"65:1-65:109\"><code>https:\/\/smartdatamodels.org\/extra\/SDM_validate.php?payload_url={url_to_your_payload}&amp;email={your_email}<\/code><\/p>\n<ul data-sourcepos=\"67:1-69:0\">\n<li data-sourcepos=\"67:1-67:90\"><strong>payload_url<\/strong>: Replace this with the URL pointing to your JSON or Key-Value payload.<\/li>\n<li data-sourcepos=\"68:1-69:0\"><strong>email<\/strong>: Provide your email address for validation feedback.<\/li>\n<\/ul>\n<p data-sourcepos=\"70:1-70:32\"><strong>See it in Action \u2013 Examples:<\/strong><\/p>\n<p data-sourcepos=\"72:1-72:66\">To give you a clearer picture, here are a couple of live examples:<\/p>\n<ul data-sourcepos=\"74:1-79:0\">\n<li data-sourcepos=\"74:1-76:0\">\n<p data-sourcepos=\"74:3-75:243\"><strong>Example 1 (JSON-LD key values):<\/strong> <code><a href=\"https:\/\/smartdatamodels.org\/extra\/SDM_validate.php?payload_url=https:\/\/raw.githubusercontent.com\/smart-data-models\/dataModel.Weather\/refs\/heads\/master\/WeatherObserved\/examples\/example.jsonld&amp;email=alberto.abella@fiware.org\">https:\/\/smartdatamodels.org\/extra\/SDM_validate.php?payload_url=https:\/\/raw.githubusercontent.com\/smart-data-models\/dataModel.Weather\/refs\/heads\/master\/WeatherObserved\/examples\/example.jsonld&amp;email=alberto.abella@fiware.org<\/a><\/code><\/p>\n<\/li>\n<li data-sourcepos=\"77:1-79:0\">\n<p data-sourcepos=\"77:3-78:209\"><strong>Example 2 (JSON-LD normalized payloads):<\/strong> <code><a href=\"https:\/\/smartdatamodels.org\/extra\/SDM_validate.php?payload_url=https:\/\/smart-data-models.github.io\/dataModel.Weather\/WeatherObserved\/examples\/example-normalized.jsonld&amp;email=alberto.abella@fiware.org\">https:\/\/smartdatamodels.org\/extra\/SDM_validate.php?payload_url=https:\/\/smart-data-models.github.io\/dataModel.Weather\/WeatherObserved\/examples\/example-normalized.jsonld&amp;email=alberto.abella@fiware.org<\/a><\/code><\/p>\n<\/li>\n<\/ul>\n<p data-sourcepos=\"80:1-80:30\"><strong>Looking for Local Control?<\/strong><\/p>\n<p data-sourcepos=\"82:1-82:401\">For those who prefer to integrate the validation process directly into their own infrastructure, the source code for this validation tool is openly available. You can find the repository here: <strong><code><a href=\"https:\/\/github.com\/smart-data-models\/data-models\/tree\/master\/sdm_as_a_service\">https:\/\/github.com\/smart-data-models\/data-models\/tree\/master\/sdm_as_a_service<\/a><\/code><\/strong>This allows you to deploy and use it locally, offering greater flexibility and control over your data validation workflows.<\/p>\n<p data-sourcepos=\"82:1-82:401\">Feel free to provide feedback in this new service in the usual mail info @ smartdatamodels.org<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Are you working with data in the realm of IoT, Smart Cities, or other domain-specific applications, and often find yourself grappling with inconsistent data formats or complex ontologies? The Smart Data Models initiative is here to streamline your work, and we&#8217;re excited to announce a new tool that brings our&#8230; <a class=\"continue-reading-link\" href=\"https:\/\/smartdatamodels.org\/index.php\/validate-your-payloads-against-smart-data-models-powering-real-world-use-cases\/\">More&#8230;<\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"class_list":["post-18619","page","type-page","status-publish","hentry"],"jetpack_sharing_enabled":true,"jetpack-related-posts":[{"id":3263,"url":"https:\/\/smartdatamodels.org\/index.php\/generate-acontext-based-on-external-ontologies-iris\/","url_meta":{"origin":18619,"position":0},"title":"Generate a@context based on external ontologies IRIs","author":"maestro","date":"20\/10\/2021","format":false,"excerpt":"Call: https:\/\/smartdatamodels.org\/extra\/create_external_referenced_context.php Parameters: (Mandatories) localContext: Link to the RAW version or the direct payload of the local context configOntologies: configuration file for merging the different ontologies (see example) mail: your email Example: https:\/\/smartdatamodels.org\/extra\/create_external_referenced_context.php?contextOntologies=https:\/\/raw.githubusercontent.com\/smart-data-models\/data-models\/master\/context\/config_ontologies.json&localContext=https:\/\/raw.githubusercontent.com\/smart-data-models\/data-models\/master\/context\/context2.0.jsonld&email=alberto.abella@fiware.org It returns a JSON file with a @context with all the attribute's names and their\u00a0 IRIs based\u2026","rel":"","context":"Similar post","block_context":{"text":"Similar post","link":""},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":948,"url":"https:\/\/smartdatamodels.org\/index.php\/check-a-schema-validates-a-payload\/","url_meta":{"origin":18619,"position":1},"title":"Check a schema validates a payload","author":"maestro","date":"09\/12\/2020","format":false,"excerpt":"Although the service keeps being operative we recommend using this https:\/\/www.jsonschemavalidator.net\/ because it provides more explanations about the errors. If you want to check if a schema validates a payload\u00a0 through this API call Call: https:\/\/smartdatamodels.org\/extra\/validate_payload.php Parameters: (Mandatories) payloadUrl: The url of the payload in RAW version schemaUrl: The link\u2026","rel":"","context":"Similar post","block_context":{"text":"Similar post","link":""},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":1829,"url":"https:\/\/smartdatamodels.org\/index.php\/generate-a-ngsi-ld-payload-based-on-a-smart-data-model\/","url_meta":{"origin":18619,"position":2},"title":"Generate a NGSI-LD normalized payload based on a Smart Data Model","author":"maestro","date":"02\/03\/2021","format":false,"excerpt":"This is an alpha version (so you can expect errors and not being complete). Use it at your own risk. Please report them at info@smartdatamodels.org Call: https:\/\/smartdatamodels.org\/extra\/ngsi-ld_generator.php Parameters: (Mandatories) schemaUrl: The link to the RAW version of the json schema (see example) email: your email Example: https:\/\/smartdatamodels.org\/extra\/ngsi-ld_generator.php?schemaUrl=https:\/\/raw.githubusercontent.com\/smart-data-models\/dataModel.Streetlighting\/f56f5a7933ab05d7fce1d5adc0847f25a099cdb4\/StreetlightModel\/schema.json&email=alberto.abella@fiware.org Use any data\u2026","rel":"","context":"Similar post","block_context":{"text":"Similar post","link":""},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":2549,"url":"https:\/\/smartdatamodels.org\/index.php\/generate-a-geojson-feature-format-payload-based-on-a-smart-data-model\/","url_meta":{"origin":18619,"position":3},"title":"Generate a Geojson feature format payload based on a Smart Data Model","author":"maestro","date":"31\/05\/2021","format":false,"excerpt":"This is a beta version (so you can expect errors and not being complete). Use it at your own risk. Please report them at info@smartdatamodels.org Call: https:\/\/smartdatamodels.org\/extra\/geojson_features_generator_v1.0.php Parameters: (Mandatories) schemaUrl: The link to the RAW version of the json schema (see example) email: your email Example: https:\/\/smartdatamodels.org\/extra\/geojson_features_generator_v1.0.php?schemaUrl=https:\/\/raw.githubusercontent.com\/smart-data-models\/dataModel.Streetlighting\/f56f5a7933ab05d7fce1d5adc0847f25a099cdb4\/StreetlightModel\/schema.json&email=alberto.abella@fiware.org Use any data\u2026","rel":"","context":"Similar post","block_context":{"text":"Similar post","link":""},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":255,"url":"https:\/\/smartdatamodels.org\/index.php\/how-to-use-data-models\/","url_meta":{"origin":18619,"position":4},"title":"How to use data models","author":"maestro","date":"03\/04\/2020","format":false,"excerpt":"Simple user: Use the csv (comma separated values) like this table, a csv is available in every data model and its specification and explanation in the \/doc\/spec.md that explains the meaning of the fields id type address__addressLocality address__addressCountry atmosphericPressure dataProvider dateObserved location__coordinates precipitation pressureTendency relativeHumidity source stationCode stationName temperature windDirection\u2026","rel":"","context":"Similar post","block_context":{"text":"Similar post","link":""},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":2199,"url":"https:\/\/smartdatamodels.org\/index.php\/generate-a-ngsi-ld-keyvalues-payload-compliant-with-a-data-model\/","url_meta":{"origin":18619,"position":5},"title":"Generate a NGSI-LD keyvalues payload compliant with a data model","author":"maestro","date":"28\/04\/2021","format":false,"excerpt":"This is an alpha version (so you can expect errors and not being complete). Use it at your own risk. Please report them at info@smartdatamodels.org Call: https:\/\/smartdatamodels.org\/extra\/ngsi-ld_generator_keyvalues_v0.95.php Parameters: (Mandatories) schemaUrl: The link to the RAW version of the json schema (see example) email: your email Example: https:\/\/smartdatamodels.org\/extra\/ngsi-ld_generator_keyvalues_v0.95.php?schemaUrl=https:\/\/raw.githubusercontent.com\/smart-data-models\/dataModel.Streetlighting\/f56f5a7933ab05d7fce1d5adc0847f25a099cdb4\/StreetlightModel\/schema.json&email=alberto.abella@fiware.org Use any data\u2026","rel":"","context":"Similar post","block_context":{"text":"Similar post","link":""},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]}],"_links":{"self":[{"href":"https:\/\/smartdatamodels.org\/index.php\/wp-json\/wp\/v2\/pages\/18619","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/smartdatamodels.org\/index.php\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/smartdatamodels.org\/index.php\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/smartdatamodels.org\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/smartdatamodels.org\/index.php\/wp-json\/wp\/v2\/comments?post=18619"}],"version-history":[{"count":8,"href":"https:\/\/smartdatamodels.org\/index.php\/wp-json\/wp\/v2\/pages\/18619\/revisions"}],"predecessor-version":[{"id":18643,"href":"https:\/\/smartdatamodels.org\/index.php\/wp-json\/wp\/v2\/pages\/18619\/revisions\/18643"}],"wp:attachment":[{"href":"https:\/\/smartdatamodels.org\/index.php\/wp-json\/wp\/v2\/media?parent=18619"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}