The Manifesto for Agile Standardization (MAS) describes the 7 principles that we apply to the Smart Data Models program.
0. Don't just standardize, be agile and standardize 1. Do not reinvent the wheel 2. Normalize real cases 3. Be open 4. Don't be overly specific 5. Flat not Deep 6. Sustainability is key
If you want to read the agile standardization manifesto’s complete explanation a one-page document is located at the root of our data models repository.
Smart Data Models. Report and Open Session
06/01/2025 2:00 pm - 3:00 pm
Monthly meeting of Smart data models program to report and collect general feedback from users.
For specific questions use the booking service of support
https://calendly.com/smartdatamodels
** Update pysmartdatamodels.py
** Contributing vineyard to wine traceability data models for incubation
** added examples and needed files for all resource types of HL7/FHIR-R4
** Added schema and adopters for MachineTool OPCUA and TimeSeries AAS
** INCODE data models update - second round of validation
** Update Schema: Replace ResultDescription with Analytics
** Extend schemas for Dataset and DataService from 2.1.1 to 3.0.0
** Update pysmartdatamodels.py
** Contributing vineyard to wine traceability data models for incubation
** added examples and needed files for all resource types of HL7/FHIR-R4
** Added schema and adopters for MachineTool OPCUA and TimeSeries AAS
** INCODE data models update - second round of validation
** Update Schema: Replace ResultDescription with Analytics
** Extend schemas for Dataset and DataService from 2.1.1 to 3.0.0
