{"id":23510,"date":"2025-08-13T09:21:35","date_gmt":"2025-08-13T07:21:35","guid":{"rendered":"https:\/\/smartdatamodels.org\/?p=23510"},"modified":"2025-08-13T01:22:19","modified_gmt":"2025-08-12T23:22:19","slug":"new-pysmartdatamodels-version-0-8-0-2-enhanced-with-more-models-and-automated-contributor-tools","status":"publish","type":"post","link":"https:\/\/smartdatamodels.org\/index.php\/new-pysmartdatamodels-version-0-8-0-2-enhanced-with-more-models-and-automated-contributor-tools\/","title":{"rendered":"New pysmartdatamodels Version 0.8.0.2: Enhanced with More Models and Automated Contributor Tools"},"content":{"rendered":"

We are thrilled to announce a significant new release of our Python package, pysmartdatamodels<\/code>, designed to empower developers and streamline the contribution process for our community.<\/p>\n

This update is packed with new data models and, most notably, powerful new validation and testing services.<\/p>\n

What’s New in This Version?<\/h3>\n

An Expanded Library of Data Models<\/b><\/h4>\n

The heart of the Smart Data Models initiative is our comprehensive library of open-licensed data models. With this new release, we have expanded it further, adding new models across our thirteen domains, from Smart Cities to Smart Energy. This package continues to provide powerful functions to integrate more than 1,000 standardized data models into your projects, digital twins, and data spaces.<\/p>\n

New! Automated Testing for Contributors<\/b><\/h4>\n

To improve the quality and speed of contributions, we are excited to launch a brand new service for our contributors. You can now automatically test your data models<\/a><\/b> before submitting them. This automated validation ensures that new models comply with our standards, making the review and integration process smoother for everyone.<\/p>\n

For those who want to integrate this validation into their own workflows, the source code for the testing tool is also available<\/a><\/b>.<\/p>\n

Online Validation for Examples<\/b><\/h4>\n

In addition to the new contributor tool, you can also use the online service to validate payloads<\/a><\/b> against existing data model examples.<\/p>\n

Get the Latest Version<\/h3>\n

You can find all the details, explore the functions, and get the latest package from the Python Package Index (PyPI). The updated README file includes comprehensive documentation on all the new features.<\/p>\n

\u27a1\ufe0f Get the package on PyPI<\/a><\/b><\/p>\n

Our Commitment to Open and Interoperable Data<\/h3>\n

We are committed to making data interoperability easier for everyone. These updates are a direct result of community feedback and the hard work of our contributors. A huge thank you to everyone who has helped make this possible!<\/p>\n","protected":false},"excerpt":{"rendered":"

We are thrilled to announce a significant new release of our Python package, pysmartdatamodels, designed to empower developers and streamline the contribution process for our community. This update is packed with new data models and, most notably, powerful new validation and testing services. What’s New in This Version? An Expanded… More…<\/a><\/p>\n","protected":false},"author":1,"featured_media":3681,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"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}},"categories":[105,107,109,113,115,119,117,88,143,111,125,182,201],"tags":[],"class_list":["post-23510","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-cross-sector","category-smart-cities","category-smart-energy-domain","category-smart-environment","category-smart-manufacturing","category-smart-robotics","category-smart-water","category-smart-sensoring","category-smartaeronautics","category-smart-agrifood","category-smartdestinations","category-smarthealth","category-smartlogistics"],"jetpack_publicize_connections":[],"jetpack_featured_media_url":"https:\/\/smartdatamodels.org\/wp-content\/uploads\/2022\/01\/SmartDataModels_logo.png","jetpack_sharing_enabled":true,"jetpack-related-posts":[{"id":32544,"url":"https:\/\/smartdatamodels.org\/index.php\/new-pysmartdatamodels-version-0-8-0-9-updated-to-1066-data-models\/","url_meta":{"origin":23510,"position":0},"title":"New pysmartdatamodels Version 0.8.0.9. Updated to 1066 data models","author":"maestro","date":"09\/03\/2026","format":false,"excerpt":"We are thrilled to announce a significant new release of our Python package, pysmartdatamodels, designed to empower developers and streamline the contribution process for our community. This update is packed with new data models till 6-3-26. Yo do not need to update the package if you use the function it\u2026","rel":"","context":"In "Cross Sector"","block_context":{"text":"Cross Sector","link":"https:\/\/smartdatamodels.org\/index.php\/category\/cross-sector\/"},"img":{"alt_text":"","src":"https:\/\/i0.wp.com\/smartdatamodels.org\/wp-content\/uploads\/2026\/03\/Screenshot-from-2026-03-07-20-55-08.png?resize=350%2C200&ssl=1","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/smartdatamodels.org\/wp-content\/uploads\/2026\/03\/Screenshot-from-2026-03-07-20-55-08.png?resize=350%2C200&ssl=1 1x, https:\/\/i0.wp.com\/smartdatamodels.org\/wp-content\/uploads\/2026\/03\/Screenshot-from-2026-03-07-20-55-08.png?resize=525%2C300&ssl=1 1.5x"},"classes":[]},{"id":8176,"url":"https:\/\/smartdatamodels.org\/index.php\/new-version-of-pysmartdatamodels-0-5-41\/","url_meta":{"origin":23510,"position":1},"title":"New version of pysmartdatamodels 0.5.41","author":"maestro","date":"30\/01\/2023","format":false,"excerpt":"There is a new version of the python package for smart data models\u00a0 pysmartdatamodels 0.5.41 Changelog: - The README include now the basic documentation of each function New function to load in a dictionary all subjects and their data models, with their repository link, and related domains New function to\u2026","rel":"","context":"In "Cross Sector"","block_context":{"text":"Cross Sector","link":"https:\/\/smartdatamodels.org\/index.php\/category\/cross-sector\/"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":10356,"url":"https:\/\/smartdatamodels.org\/index.php\/new-version-of-pysmartdatamodels-python-package-0-7-1\/","url_meta":{"origin":23510,"position":2},"title":"New version of pysmartdatamodels python package 0.7.1","author":"maestro","date":"07\/05\/2024","format":false,"excerpt":"The changes in this new version are: - Including new function validate_dcat_ap_distribution_sdm - Updating the comments of most of the functions - Some code improvements by jilin.he@fiware.org - Included a new directory with templates for the creation of a data model. Not used yet but next version they will be\u2026","rel":"","context":"In "Cross Sector"","block_context":{"text":"Cross Sector","link":"https:\/\/smartdatamodels.org\/index.php\/category\/cross-sector\/"},"img":{"alt_text":"","src":"https:\/\/i0.wp.com\/smartdatamodels.org\/wp-content\/uploads\/2024\/05\/pysmartdatamodels_0.7.1.png?resize=350%2C200&ssl=1","width":350,"height":200},"classes":[]},{"id":10376,"url":"https:\/\/smartdatamodels.org\/index.php\/version-0-8-of-the-pysmartdatamodels-package\/","url_meta":{"origin":23510,"position":3},"title":"Version 0.8 of the pysmartdatamodels package","author":"maestro","date":"24\/05\/2024","format":false,"excerpt":"Due to the new configuration of files of the package pysmartdatamodels it will be no longer required to use the from clause (initially) Therefore now to import the package in python it will be simply import pysmartdatamodels as sdm Accordingly the examples of code in all data models are being\u2026","rel":"","context":"In "Cross Sector"","block_context":{"text":"Cross Sector","link":"https:\/\/smartdatamodels.org\/index.php\/category\/cross-sector\/"},"img":{"alt_text":"","src":"https:\/\/i0.wp.com\/smartdatamodels.org\/wp-content\/uploads\/2024\/05\/pysdm0.8.png?resize=350%2C200&ssl=1","width":350,"height":200},"classes":[]},{"id":10131,"url":"https:\/\/smartdatamodels.org\/index.php\/new-pysmartdatamodels-package-0-6-3-release\/","url_meta":{"origin":23510,"position":4},"title":"New pysmartdatamodels package 0.6.3 Release","author":"maestro","date":"02\/11\/2023","format":false,"excerpt":"We are thrilled to announce the latest update to pysmartdatamodels Python package, version 0.6.3, featuring a new function: generate_sql_schema()This addition enabling seamless generation of SQL schemas with just a few lines of code! Introducing\u00a0 generate_sql_schemqa() Function: With the new function, generate_sql_schemqa()\u00a0 pysmartdatamodels simplifies the process of creating SQL schemas for\u2026","rel":"","context":"In "Smart Cities domain"","block_context":{"text":"Smart Cities domain","link":"https:\/\/smartdatamodels.org\/index.php\/category\/smart-cities\/"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":9334,"url":"https:\/\/smartdatamodels.org\/index.php\/new-version-of-the-python-package-pysmartdatamodels-0-6-0\/","url_meta":{"origin":23510,"position":5},"title":"New Version of the Python Package pysmartdatamodels 0.6.0","author":"maestro","date":"01\/08\/2023","format":false,"excerpt":"There is a new version of the python package for pysmartdatamodels 0.6.0. This python package includes all the data models and several functions to use them in your developments. Changelog: - Four new functions New functions to generate fake example files given the schema payload of the data model in\u2026","rel":"","context":"In "Cross Sector"","block_context":{"text":"Cross Sector","link":"https:\/\/smartdatamodels.org\/index.php\/category\/cross-sector\/"},"img":{"alt_text":"pysmartdatamodels 0.6.0","src":"https:\/\/i0.wp.com\/smartdatamodels.org\/wp-content\/uploads\/2023\/08\/Screenshot-2023-08-01-at-09.34.53-300x162.png?resize=350%2C200&ssl=1","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/smartdatamodels.org\/wp-content\/uploads\/2023\/08\/Screenshot-2023-08-01-at-09.34.53-300x162.png?resize=350%2C200&ssl=1 1x, https:\/\/i0.wp.com\/smartdatamodels.org\/wp-content\/uploads\/2023\/08\/Screenshot-2023-08-01-at-09.34.53-300x162.png?resize=525%2C300&ssl=1 1.5x"},"classes":[]}],"_links":{"self":[{"href":"https:\/\/smartdatamodels.org\/index.php\/wp-json\/wp\/v2\/posts\/23510","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/smartdatamodels.org\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/smartdatamodels.org\/index.php\/wp-json\/wp\/v2\/types\/post"}],"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=23510"}],"version-history":[{"count":1,"href":"https:\/\/smartdatamodels.org\/index.php\/wp-json\/wp\/v2\/posts\/23510\/revisions"}],"predecessor-version":[{"id":23511,"href":"https:\/\/smartdatamodels.org\/index.php\/wp-json\/wp\/v2\/posts\/23510\/revisions\/23511"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/smartdatamodels.org\/index.php\/wp-json\/wp\/v2\/media\/3681"}],"wp:attachment":[{"href":"https:\/\/smartdatamodels.org\/index.php\/wp-json\/wp\/v2\/media?parent=23510"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/smartdatamodels.org\/index.php\/wp-json\/wp\/v2\/categories?post=23510"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/smartdatamodels.org\/index.php\/wp-json\/wp\/v2\/tags?post=23510"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}