Thanks to the IUDX we have a new data model to describe the water distribution network of a locality.
Reach them at the new subject water distribution
- WaterDistributionNetwork. A Data Model for water supply network in a city.
Author: maestro
New subject Data Quality and new data model Data Quality assessment
Thanks to the University of Cantabria and the project Salted we have a new data model to assess data quality in a new subject Data quality
Reach them at the new subject Data quality
- DataQualityAssessment. This entity describes the data quality properties of a measurement, such as a temperature.
New service for customization of @context with official ontologies
Some of the data models available are generated according to some ontologies (like dataModels.OSLO). The @context provided for the subject includes IRIs with the smartdatamodels by default, however, the use of official ontologies can be required.
In order to allow this the file notes_context.jsonld was created and also included in the contribution manual (seection 1.5 slide 23).
Now the service for mapping the external ontologies (Home -> tools -> Mapper @context with external ontologies) can detect that instead of a regular configuration file a notes_context.jsonld is provided and applies the replacement of terms defined there.
It can be also used as an API call, in this link you have an example https://smartdatamodels.org/extra/create_external_referenced_context.php?localContext=https://raw.githubusercontent.com/smart-data-models/dataModel.OSLO/master/context.jsonld&configOntologies=https://raw.githubusercontent.com/smart-data-models/dataModel.OSLO/master/notes_context.jsonld
The structure of the notes_context.jsonld has to follow the template
- {
“@context”: {
“Term1”: “uri_term_1”,
“Term2”: “uri_term_2”,
}
}
New version of pysmartdatamodels 0.5.41
There is a new version of the python package for smart data models pysmartdatamodels 0.5.41
Changelog:
– The README include now the basic documentation of each function
- New function to load in a dictionary all subjects and their data models, with their repository link, and related domains
- New function to load in a dictionary all the attributes in every data model including name of the property, data type, NGSI type, description, units, et
The data models available for python developers. pysmartdatamodels 0.5.40 published. Beta version.
Now you can find in pypi.org the python package pysmartdatamodels with 13 functions for the integrators of the data models (more than 800) in external systems and applications. It is a beta version. There is a function, update_data() that whenever is run, it updates the data models to the last version (including adding the new data models). The code is available at the utils directory.
This python package includes all the data models and several functions (listed below) to use in your developments.
If you want to be updated on this package you can join this mailing list (Announcements are sent only when something relevant happens). We love to get your feedback at info@smartdatamodels.org
There are several online tools to manage and to create the data models, generate examples or to adapt to existing ontologies. See the tools menu option at the home site.
Functions available include:
1- List all data models. Function list_all_datamodels()
2- List all subjects. Function list_all_subjects()
3- List the data models of a subject. Function datamodels_subject(subject)
4- List description of an attribute. Function description_attribute(subject, datamodel, attribute)
5- List data-type of an attribute. Function datatype_attribute(subject, datamodel, attribute)
6- Give reference model for an attribute. Function model_attribute(subject, datamodel, attribute)
7- Give reference units for an attribute. Function attributes_datamodel(subject, datamodel)
8- List the attributes of a data model. Function attributes_datamodel(subject, datamodel)
9- List the NGSI type (Property, Relationship or Geoproperty) of the attribute. Function ngsi_datatype_attribute(subject, datamodel, attribute)
10- Print a list of data models attributes separated by a separator. Function print_datamodel(subject, datamodel, separator, meta_attributes)
11- Returns the link to the repository of a subject. Function subject_repolink(subject)
12- Returns the links to the repositories of a data model name. Function datamodel_repolink(datamodel)
13- Update the official data model list or the database of attributes from the source. Function update_data()
Roadmap
1.- Create a proper documentation
2.- Function to allow submission of improvements (i.e. missing recommended units or model) and comments to the different data models. Currently, you can do it by searching for your data model here
https://smartdatamodels.org/index.php/list-of-data-models-3/ visiting the github repo and making your PR or raising your issues there.
3.- Function to submit a new data model to an incubation repository. Currently, this is done manually incubated repository. By filling this form you are granted to contribute with new data models.
4.- Include new functions like search for the subject of a data model or other that you can suggest to us at info@smartdatamodels.org
### some example code
from pysmartdatamodels import pysmartdatamodels as sdm
subject = "dataModel.Weather"
dataModel = "WeatherForecast"
attribute = "precipitation"
print(sdm.list_all_datamodels())
print(sdm.list_all_subjects())
print(sdm.datamodels_subject("dataModel.Weather"))
print(sdm.description_attribute(subject, dataModel, attribute))
print(sdm.datatype_attribute(subject, dataModel, attribute))
print(sdm.model_attribute(subject, dataModel, attribute))
print(sdm.units_attribute(subject, dataModel, attribute))
print(sdm.attributes_datamodel(subject, dataModel))
print(sdm.subject_repolink(subject))
print(sdm.datamodel_repolink(dataModel))
print(sdm.print_datamodel(subject, dataModel, ",", ["property", "type", "dataModel", "repoName", "description", "typeNGSI", "modelTags", "format", "units", "model"]))
sdm.update_data()
New data models MedicationAdministration and Claim
Happy new year the last two data models of 2022
See it in subject Hl7 in the Smart Health domain.
- Claim. A provider issued list of professional services and products which have been provided, or are to be provided, to a patient which is sent to an insurer for reimbursement.
- MedicationAdministration. Describes the event of a patient consuming or otherwise being administered a medication. This may be as simple as swallowing a tablet or it may be a long running infusion. Related resources tie this event to the authorizing prescription, and the specific encounter between patient and health care practitioner.
New data model Organization at Hl7 subject (Health)
There is a new data model for the subject Hl7, Organization for this health sector.
See it in subject Hl7 in the Smart Health domain.
- Organization: A formally or informally recognized grouping of people or organizations formed for the purpose of achieving some form of collective action. Includes companies, institutions, corporations, departments, community groups, healthcare practice groups, payer/insurer, etc.
SQL export available for Postgresql
There is a new file ‘schema.sql‘ in all the directories of the data models. It is a SQL script for PostgreSQL.
The script creates the structure of a relational table containing the attributes defined in the data model. It also creates the data types for those attributes with an enumeration of values.
For those attributes being arrays or objects, it creates a JSON attribute (allowed in PostgreSQL).
If you need additional features in this export please report them to info@smartdatamodels.org.
See an example.
Sargon ontology available for mapping with Smart Data Models
There is a service for mapping any smart data models with one (or several) external ontologies. Now the SARGON ontology 1.0 for energy is available for this mapping.
The Sargon mapping file is located in the ontologies_files folder ad the umbrella repository data-models.
The description of SARGON is below.
SARGON ( SmArt eneRGy dOmain oNtology ) is an open-source effort to define semantic descriptions of the smart assets in building automation and smart grid and the relationships between them. SARGON consists of an extensible dictionary of terms and concepts in and around buildings and smart grids, a set of relationships for linking and composing concepts together, and a flexible data model permitting seamless integration of SARGON with existing tools and databases. Through the use of powerful Semantic Web technology, SARGON can describe the broad set of Devices and custom features, assets and subsystems found across the building stock in a consistent matter.
Draft of a python package available
Now we have a draft version of a python package to integrate the smart data models with your developments. It is a beta version so you can expect some issues when using it. We will be glad if you report it at info@smartdatamodels.org or suggest new features. Thanks to Anthony Uphof for his contributions (only a few of them are in this draft, next version will include them)
To install
pip install -i test.pypi.org/simple/ pysmartdatamodels
The functions included are:
1- List all data models. Function list_all_datamodels()
2- List all subjects. Function list_all_subjects()
3- List the data models of a subject. Function datamodels_subject(subject)
4- List description of an attribute. Function description_attribute(subject, datamodel, attribute)
5- List data-type of an attribute. Function datatype_attribute(subject, datamodel, attribute)
6- Give reference model for an attribute. Function model_attribute(subject, datamodel, attribute)
7- Give reference units for an attribute. Function attributes_datamodel(subject, datamodel)
8- List the attributes of a data model. Function attributes_datamodel(subject, datamodel)
9- List the NGSI type (Property, Relationship or Geoproperty) of the attribute. Function ngsi_datatype_attribute(subject, datamodel, attribute)
11- Print a list of data models attributes separated by a separator. Function print_datamodel(subject, datamodel, separator, meta_attributes)
12- Update the official data model list or the database of attributes from the source. Function update_data()
