{"id":12963,"date":"2025-02-19T08:30:25","date_gmt":"2025-02-19T07:30:25","guid":{"rendered":"https:\/\/smartdatamodels.org\/?p=12963"},"modified":"2025-02-19T00:18:46","modified_gmt":"2025-02-18T23:18:46","slug":"two-new-data-models-timeseries-and-machinetool","status":"publish","type":"post","link":"https:\/\/smartdatamodels.org\/index.php\/two-new-data-models-timeseries-and-machinetool\/","title":{"rendered":"Two new data models TimeSeries and MachineTool"},"content":{"rendered":"<p>There are two new data models <a href=\"https:\/\/github.com\/smart-data-models\/dataModel.OPCUA\/tree\/master\/MachineTool\">MachineTool<\/a> at <a href=\"https:\/\/github.com\/smart-data-models\/dataModel.OPCUA\/tree\/master\">OPCUA<\/a> subject and <a href=\"https:\/\/github.com\/smart-data-models\/dataModel.AAS\/tree\/master\/TimeSeries\">TimeSeries<\/a> in <a href=\"https:\/\/github.com\/smart-data-models\/dataModel.AAS\">AAS<\/a> subject<\/p>\n<p>Thanks to Manfredi Pistone from <a href=\"https:\/\/www.eng.it\">Engineering<\/a> for the contributions<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-10318 size-medium\" src=\"https:\/\/smartdatamodels.org\/wp-content\/uploads\/2024\/04\/AAS_image-300x169.jpg\" alt=\"\" width=\"300\" height=\"169\" srcset=\"https:\/\/smartdatamodels.org\/wp-content\/uploads\/2024\/04\/AAS_image-300x169.jpg 300w, https:\/\/smartdatamodels.org\/wp-content\/uploads\/2024\/04\/AAS_image-1024x576.jpg 1024w, https:\/\/smartdatamodels.org\/wp-content\/uploads\/2024\/04\/AAS_image-768x432.jpg 768w, https:\/\/smartdatamodels.org\/wp-content\/uploads\/2024\/04\/AAS_image-622x350.jpg 622w, https:\/\/smartdatamodels.org\/wp-content\/uploads\/2024\/04\/AAS_image-150x84.jpg 150w, https:\/\/smartdatamodels.org\/wp-content\/uploads\/2024\/04\/AAS_image.jpg 1280w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><img decoding=\"async\" src=\"https:\/\/opcfoundation.org\/wp-content\/themes\/opc\/images\/logo.jpg\" alt=\"logo\" \/><\/p>\n<p>&nbsp;<\/p>\n<ul>\n<li><a href=\"https:\/\/github.com\/smart-data-models\/dataModel.OPCUA\/blob\/master\/MachineTool\/README.md\">MachineTool<\/a>. MachineTool is a mechanical device which is fixed (i.e. not mobile) and powered (typically by electricity and compressed air), typically used to process workpieces by selective removal\/addition of material or mechanical deformation<\/li>\n<li><a href=\"https:\/\/github.com\/smart-data-models\/dataModel.AAS\/blob\/master\/TimeSeries\/README.md\">TimeSeries<\/a>. Time Series can represent raw data, but can also represent main characteristics, textual descriptions or events in a concise way.<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>There are two new data models MachineTool at OPCUA subject and TimeSeries in AAS subject Thanks to Manfredi Pistone from Engineering for the contributions &nbsp; MachineTool. MachineTool is a mechanical device which is fixed (i.e. not mobile) and powered (typically by electricity and compressed air), typically used to process workpieces&#8230; <a class=\"continue-reading-link\" href=\"https:\/\/smartdatamodels.org\/index.php\/two-new-data-models-timeseries-and-machinetool\/\">More&#8230;<\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"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":[119,88],"tags":[],"class_list":["post-12963","post","type-post","status-publish","format-standard","hentry","category-smart-robotics","category-smart-sensoring"],"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"jetpack-related-posts":[{"id":2989,"url":"https:\/\/smartdatamodels.org\/index.php\/3-new-data-models-in-frictionlessdata-subject-csvdialectfrictionlessdata-dataresourcefrictionlessdata-and-tableschemafrictionlessdata\/","url_meta":{"origin":12963,"position":0},"title":"3 new data models in FrictionlessData subject CSVDialectFrictionlessData, DataResourceFrictionlessData and TableSchemaFrictionlessData","author":"maestro","date":"24\/08\/2021","format":false,"excerpt":"The adaptation of the frictionless data standard is completed with these three new data models in the datamodel.FrictionlessData subject CSVDialectFrictionlessData. The CSV dialect descriptor. Converted for Smart Data Models initiative from original frictionless data DataResourceFrictionlessData. Data Resource. Converted for Smart Data Models initiative from original frictionless data TableSchemaFrictionlessData. A Table\u2026","rel":"","context":"In &quot;Cross Sector&quot;","block_context":{"text":"Cross Sector","link":"https:\/\/smartdatamodels.org\/index.php\/category\/cross-sector\/"},"img":{"alt_text":"","src":"https:\/\/frictionlessdata.io\/img\/frictionless-color-full-logo.svg","width":350,"height":200,"srcset":"https:\/\/frictionlessdata.io\/img\/frictionless-color-full-logo.svg 1x, https:\/\/frictionlessdata.io\/img\/frictionless-color-full-logo.svg 1.5x, https:\/\/frictionlessdata.io\/img\/frictionless-color-full-logo.svg 2x"},"classes":[]},{"id":618,"url":"https:\/\/smartdatamodels.org\/index.php\/automated-readme-md-for-data-models\/","url_meta":{"origin":12963,"position":1},"title":"Automated README.md for data models","author":"maestro","date":"07\/09\/2020","format":false,"excerpt":"Currently, the README.md at data models level (inside every directory in a Subject) explaining the contents of the data models is automated, and therefore there is no need to be contributed by the contributors. See an example here for the weather forecast. Thus, the README.md is based on the examples\u2026","rel":"","context":"In &quot;Smart Cities domain&quot;","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":7722,"url":"https:\/\/smartdatamodels.org\/index.php\/new-database-of-data-models-versions\/","url_meta":{"origin":12963,"position":2},"title":"New database of data models&#8217; versions","author":"maestro","date":"28\/11\/2022","format":false,"excerpt":"In the main menu, it has been extended the submenu of list data models with a complete database of all versions of the data models. It includes not only the data model, subject, and version but also the data directly linked to the raw version of the data model. You\u2026","rel":"","context":"In &quot;Cross Sector&quot;","block_context":{"text":"Cross Sector","link":"https:\/\/smartdatamodels.org\/index.php\/category\/cross-sector\/"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":13212,"url":"https:\/\/smartdatamodels.org\/index.php\/new-script-for-testing-several-data-models-at-the-same-time\/","url_meta":{"origin":12963,"position":3},"title":"New script for testing several data models at the same time.","author":"maestro","date":"27\/02\/2025","format":false,"excerpt":"Most of the files of the testing process have been updated and make it available the source code: https:\/\/github.com\/smart-data-models\/data-models\/tree\/master\/test_data_model But also there is a new file multiple_tests.py This file enables you to test all the data models located in a internal subject (subdirectories of the root one). Currently this option\u2026","rel":"","context":"In &quot;Cross Sector&quot;","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\/2022\/01\/favicon-300x300.png?resize=350%2C200&ssl=1","width":350,"height":200},"classes":[]},{"id":582,"url":"https:\/\/smartdatamodels.org\/index.php\/new-harmonization-repository\/","url_meta":{"origin":12963,"position":4},"title":"New harmonization repository","author":"maestro","date":"02\/09\/2020","format":false,"excerpt":"In order to provide a more transparent and participative approach to the creation and maintenance of data models, here you can see the three stages for a usual data model to be part of the official list of data models. 1.- Pending is the 'wild' zone where developers share their\u2026","rel":"","context":"In &quot;Cross Sector&quot;","block_context":{"text":"Cross Sector","link":"https:\/\/smartdatamodels.org\/index.php\/category\/cross-sector\/"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":1472,"url":"https:\/\/smartdatamodels.org\/index.php\/new-subject-touristdestination-at-smart-destinations-domain-and-data-models-event-and-tourist-destination\/","url_meta":{"origin":12963,"position":5},"title":"New Subject TouristDestination at Smart Destinations domain and data models Event and Tourist Destination","author":"maestro","date":"29\/01\/2021","format":false,"excerpt":"New Subject, dataModel.TourismDestinations for allocating data models related to touristic destinations. It is located in the Smart Destinations domain repository. Event is based on the examples provided for the semantic standard UNE 178503 and schema.org. TouristDestination is also based on this standard and UNE178503. Schema and examples already available, specification\u2026","rel":"","context":"In &quot;SmartDestinations&quot;","block_context":{"text":"SmartDestinations","link":"https:\/\/smartdatamodels.org\/index.php\/category\/smartdestinations\/"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]}],"_links":{"self":[{"href":"https:\/\/smartdatamodels.org\/index.php\/wp-json\/wp\/v2\/posts\/12963","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=12963"}],"version-history":[{"count":2,"href":"https:\/\/smartdatamodels.org\/index.php\/wp-json\/wp\/v2\/posts\/12963\/revisions"}],"predecessor-version":[{"id":12966,"href":"https:\/\/smartdatamodels.org\/index.php\/wp-json\/wp\/v2\/posts\/12963\/revisions\/12966"}],"wp:attachment":[{"href":"https:\/\/smartdatamodels.org\/index.php\/wp-json\/wp\/v2\/media?parent=12963"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/smartdatamodels.org\/index.php\/wp-json\/wp\/v2\/categories?post=12963"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/smartdatamodels.org\/index.php\/wp-json\/wp\/v2\/tags?post=12963"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}