pysmartdatamodels updated to 0.7

The new version does not provide new functionalities but an indication, including drafted code, about what is missing or in progress to the package can grow according to your needs.

The source code for the new version 0.7.0 is here at the data-models repository

There are 4 new functions drafted with the headings inputs and outputs and some recommendations for development.

1) validate_payload(datamodel, subject, payload)
2) create_QR_code(datamodel, subject)
3) include_local_datamodel(schema, subject, datamodel, contributors (optional), adopters (optional), notes(optional))
4) submit_datamodel(subject, datamodel, contributors (optional), adopters (optional), notes(optional), example_payload, notes_context, public_repository, credentials)

we will be glad to receive code or questions implementing this and we will include the authorship

Minor extension of pysmartdatamodels

There is a minor new version of the package pysmartdatamodels.

Now it allows to have in the metadata of a data model the direct links to the specification in the 8 languages.

you can access thanks to the function list_datamodel_metadata and accessing the objects with the keys, spec, spec_DE, spec_ES, spec_FR, spec_IT, spec_JA, spec_KO and spec_ZH

from pysmartdatamodels import pysmartdatamodels as sdm
subject = "dataModel.Weather"
dataModel ="WeatherForecast"
metadata = sdm.list_datamodel_metadata(dataModel, subject))

You can install the update

pip install –upgrade pysmartdatamodels

New version of pysmartdatamodels package 0.6.4 with adaptations to Data Spaces

There is a new version of the python package pysmartdatamodels

to use it you have just to type

pip install pysmartdatamodels

in your system

Besides the update in the list of data models it includes two new functions
look_for_data_model that allows approximate searches for a data model based on their name
list_datamodel_metadata that returns the metadata of a data model including context link, data model version, model tags, link to the schema and to the yaml version of the schema, title, description, $id, required, links to the examples, link to the adopters, link to the contributors of the subject and a link to the sql export of a data model

These new functions are the result of some requests of data spaces managers and several others will be included soon to help you out in the management of the semantic contents of a data space.

A code example of these two new functions

from pysmartdatamodels import pysmartdatamodels as sdm

subject = "dataModel.Weather"
dataModel = "WeatherForecast"
# Look for a data model name 
print("22 : ")
print(sdm.look_for_datamodel("WeatherFora", 84))
# retrieve the metadata, context, version, model tags, schema, yaml schema, title, description, $id, required, examples, adopters, contributors and sql export of a data model
print("23 : ")
print(sdm.list_datamodel_metadata(dataModel, subject))

Metadata of the catalogue available

Now in the tools menu (currently the last option) you have a complete list of the most relevant links to the assets of the data models compile in the Smart Data Models initiative.

You can check in the main menu -> Tools  -> Metadata of the data models

The information is coded in a json format and includes:


New scripts released

4 of the python scripts that are used to maintain the Smart Data models have been released.

Use them or study it at your own convenience. Glad to receive comments and improvements

Check them out here:

Joining the Metaverse Standards Forum

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.


New pysmartdatamodels package 0.6.3 Release

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.

Korean translation available for all data models

The Korean translation of the specifications has been incorporated. Therefore every specification folder now it has a new file with the Korean translation.

See an example:

Also the specification is linked from the file at the front of every data model.

New service: Export you data models to SQL schema

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.

Update: Generate the schema out of your payload

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::

  • Added support for generating sub-property descriptions
  • Fixed the bug of duplicated property generation

Please feel free to try it out and leave your comments on