Category: Smart Manufacturing domain

New data models I4submodelElement operation and I4SubmodelElementProperty In AAS subject

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Two new data models have been published in the subject dataModel.AAS (Asset administration shell) in the Smart manufacturing domain.

The data model was created thanks to the project Corosect.

  • I4SubmodelElementOperation. Based on IDTA-01001-3-0, describes a generic RAMI4.0 SubmodelElement representing an OPERATION (Command) of a referenced Asset Administration Shell

  • I4SubmodelElementProperty. Based on IDTA-01001-3-0, maps a generic RAMI4.0 SubmodelElement representing a PROPERTY or attribute of a referenced AAS. RAMI4.0 Standard

New data models I4AAS and I4Asset

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Two new data models has been published in the subject dataModel.AAS (Asset administration shell) in the Smart Manufacturing domain.

The data models were created thanks to the project Corosect.

  • I4AAS. Based on IDTA-01001-3-0, describes a generic Asset Administration Shell – AAS – tree, component of the RAMI4.0

  • I4Asset. Based on IDTA-01001-3-0, defines the Asset -instance- linked to a given AAS a generic Asset Administration Shell – AAS – component of the RAMI4.0

 

New subject Asset Administration Shell

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We have created a new subject, aligned with Asset Administration Shell, dataModel.AAS in the Smart Manufacturing domain.

The Corosect project is using NGSI-LD for using AAS assets coming from the document Specification of the Asset Administration Shell. Part 1: Metamodel.

Data models will be soon added.

Thanks to the contributors coming from these organizations

 

pysmartdatamodels updated to 0.7

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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 0.6.4.1

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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))
print(metadata["spec_ES"]

You can install the update

pip install –upgrade pysmartdatamodels

New version of pysmartdatamodels package 0.6.4 with adaptations to Data Spaces

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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

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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:

Enjoy!

New scripts released

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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

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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.