FIWARE Foundation has joined the “Metaverse Standards Forum” The Metaverse Standards Forum is a non-profit, member-funded consortium of standards-related organizations, companies, and institutions that are cooperating to foster interoperability for an open and inclusive metaverse.
The Smart Data Models initiative is willing to contribute to those standards with all its data models to enable its use in the metaverse.
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 generate_sql_schemqa() Function:
With the new function, generate_sql_schemqa() pysmartdatamodels simplifies the process of creating SQL schemas for your data models by providing as input the model.yaml representation of a Smart Data Model.
The Korean translation of the specifications has been incorporated. Therefore every specification folder now it has a new file spec_KO.md with the Korean translation.
See an example:
Also the specification is linked from the README.md file at the front of every data model.
We provide a service to Generate a PostgreSQL schema SQL script from the model.yaml representation of a Smart Data Model.
You can access this service under this link following Tools > SQL service.
You need to provide as input the standard GitHub link to the model.yaml file or the raw version GitHub link.
We provide a service to generate JSON schemas from the example payloads you provide. This service is designed to assist contributors who may have limited experience with JSON schemas but with actual examples. You can access the service through this link.
We are pleased to announce that we have made some updates to this service::
Please feel free to try it out and leave your comments on info@smartdatamodels.org.
We have introduced several new sections in the README.md for all the smart data models that we’ve published
These are:
Such as in the data model WeatherForecast:
Hope you find it useful and feel free to make your comments on info@smartdatamodels.org.
DCAT-AP is, possibly, the most relevant standard of a catalogue of datasets (even resources as well). A data spaces’ data models’ building block needs a semantic catalogue of resources in DCAT-AP format.
Here you have the beta version of a service providing a DCAT-AP catalogue containing all semantic resources of Smart Data Models.
You just connect to this URL and you can get it. It will be updated once a day and whenever a data model is published.
You can also reach it at home -> tools -> DCAT-AP catalog (last option)
As long as the catalogue and its structure can be enriched I’d like to hear from you any comments / additions and critics you wish / need at info@smartdatamodels.org
So you can enrich it before the official release
There is a new version of the python package for pysmartdatamodels 0.6.1.
This python package includes all the data models and several functions to use them in your developments.
Changelog:
– Two updated functions
– Minor changes on providing links of repository, issues, updating on latest statistics, etc.
Get more details on the pypi page and feel free to try it out!
We are very close to launch a new service and we want to have your feedback on how to create this service.
So we made a Survey and you can help us by submitting your preference.
Thank you!
A new data model in the transportation subject, APDSObservation, it is the result of the ANPR camera (automatic number plate recognition). It is aligned with the alliance of parking standards.
APDSObservation. This entity models a particular observation of a set of ANPR camera. The Observation might be done with several ANPR cameras, but is limited to the observation of ONE vehicle. It implements the APDS data model https://www.allianceforparkingdatastandards.org/
List of attributes
-address
-addressCountry
-addressLocality
-addressRegion
-alternateName
-areaServed
-creator
-dataProvider
-dateCreated
-dateModified
-description
-district
-id
-images
-location
-name
-observationDateTime
-observationEndDateTime
-observationStartDateTime
-observedCredentialCharacterConfidence
-observedCredentialConfidence
-observedCredentialCountry
-observedCredentialId
-observedCredentialType
-observedHeading
-observedLocation
-observedLocationPDOP
-observedMethod
-observedSpeed
-observedVehicleColour
-observedVehicleMake
-observedVehicleType
-observer
-observerCameras
-observerDescription
-observerHeading
-observerLocation
-observerLocationPDOP
-observerSpeed
-owner
-postOfficeBoxNumber
-postalCode
-seeAlso
-source
-streetAddress
-streetNr
-towardsObserver
-type
Slack channel
Discord channel #smart-data-models
help on discord
Invitation to discord 
Validate a payload with a data model(external)
