{"id":8443,"date":"2023-03-15T13:39:59","date_gmt":"2023-03-15T12:39:59","guid":{"rendered":"https:\/\/smartdatamodels.org\/?page_id=8443"},"modified":"2023-03-15T13:39:59","modified_gmt":"2023-03-15T12:39:59","slug":"generator-of-examples","status":"publish","type":"page","link":"https:\/\/smartdatamodels.org\/index.php\/generator-of-examples\/","title":{"rendered":"Generator of examples"},"content":{"rendered":"<p>There are 3 options for generating examples based on the schemas of SDM<\/p>\n<ul>\n<li><a href=\"https:\/\/smartdatamodels.org\/index.php\/generate-a-ngsi-ld-keyvalues-payload-compliant-with-a-data-model\/\">Keyvalues format<\/a><\/li>\n<li><a href=\"https:\/\/smartdatamodels.org\/index.php\/generate-a-ngsi-ld-payload-based-on-a-smart-data-model\/\">Normalized format<\/a><\/li>\n<li><a href=\"https:\/\/smartdatamodels.org\/index.php\/generate-a-geojson-feature-format-payload-based-on-a-smart-data-model\/\">Geojson features<\/a><\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>There are 3 options for generating examples based on the schemas of SDM Keyvalues format Normalized format Geojson features <a class=\"continue-reading-link\" href=\"https:\/\/smartdatamodels.org\/index.php\/generator-of-examples\/\">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-8443","page","type-page","status-publish","hentry"],"jetpack_sharing_enabled":true,"jetpack-related-posts":[{"id":2201,"url":"https:\/\/smartdatamodels.org\/index.php\/generate-examples-of-ngsi-payloads-compliant-with-a-data-model\/","url_meta":{"origin":8443,"position":0},"title":"Generate examples of NGSI payloads compliant with a data model","author":"maestro","date":"28\/04\/2021","format":false,"excerpt":"NGSI-LD normalized format NGSI-LD keyvalues format NGSIv2 normalized format (pending) NGSIv2 keyvalues format (pending)","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":8443,"position":1},"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":1329,"url":"https:\/\/smartdatamodels.org\/index.php\/draft-a-data-model\/","url_meta":{"origin":8443,"position":2},"title":"Draft a data model","author":"maestro","date":"24\/01\/2021","format":false,"excerpt":"Steps to create your new data model in json schema Supposedly you know how many fields you want your data model to have and what data types they would be. 1.- Copy this text 2.- Open in a new window this web. 3.- Paste the text in the left form\u2026","rel":"","context":"Similar post","block_context":{"text":"Similar post","link":""},"img":{"alt_text":"","src":"https:\/\/i0.wp.com\/smartdatamodels.org\/wp-content\/uploads\/2021\/06\/validation.png?resize=350%2C200&ssl=1","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/smartdatamodels.org\/wp-content\/uploads\/2021\/06\/validation.png?resize=350%2C200&ssl=1 1x, https:\/\/i0.wp.com\/smartdatamodels.org\/wp-content\/uploads\/2021\/06\/validation.png?resize=525%2C300&ssl=1 1.5x"},"classes":[]},{"id":255,"url":"https:\/\/smartdatamodels.org\/index.php\/how-to-use-data-models\/","url_meta":{"origin":8443,"position":3},"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":18619,"url":"https:\/\/smartdatamodels.org\/index.php\/validate-your-payloads-against-smart-data-models-powering-real-world-use-cases\/","url_meta":{"origin":8443,"position":4},"title":"Validate Your Payloads Against Smart Data Models \u2013 Powering Real-World Use Cases!","author":"maestro","date":"08\/06\/2025","format":false,"excerpt":"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're excited to announce a new tool that brings our\u2026","rel":"","context":"Similar post","block_context":{"text":"Similar post","link":""},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":126,"url":"https:\/\/smartdatamodels.org\/index.php\/coding-data-models\/","url_meta":{"origin":8443,"position":5},"title":"Check the whole data model repository","author":"maestro","date":"17\/03\/2020","format":false,"excerpt":"The data models are composed of: Manually contributed Json schema describing the technical properties of the model and their descriptions Some examples in JSON and JSON-LD (example.json, example.jsonld, example-normalized.json and example-normalized.json) Optional Manually contributed: The authors (CONTRIBUTORS.yaml) Manually contributed: Current adopters of the data model (ADOPTERS.yaml) Manually contributed: Customization of\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\/8443","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=8443"}],"version-history":[{"count":1,"href":"https:\/\/smartdatamodels.org\/index.php\/wp-json\/wp\/v2\/pages\/8443\/revisions"}],"predecessor-version":[{"id":8444,"href":"https:\/\/smartdatamodels.org\/index.php\/wp-json\/wp\/v2\/pages\/8443\/revisions\/8444"}],"wp:attachment":[{"href":"https:\/\/smartdatamodels.org\/index.php\/wp-json\/wp\/v2\/media?parent=8443"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}