We are in the way of creating a service for testing purposes for getting payloads according to a data model.
The service is under debugging, so it cannot be trusted for production purposes. Let us know issues here
In order to access it has to access this URL (https://smartdatamodels.org/extra/payload_generator.php) with these two parameters token and dataModel
I.e. with a weather observation in the link below:
https://smartdatamodels.org/extra/payload_generator.php?token=sSdme8954c9&dataModel=%22WeatherObserved (reload page several times for generation)
In the production stage, there will be necessary a token in order to, if necessary, to limit the access for a single user. Additionally, it should be available the options of normalized and keyvalues and for the NGSI v2 and LD.
Comments are welcomed
Whenever there is measurement it could be necessary to use the unitCode for setting the units for the value.
Now the guidelines for the data model’s creation include the place to find out these unit codes. See section units.
The list of UN/CEFACT Common Code (3 characters) can be download from this page. Or the list directly from here.
It has been a minor fix in the water observed data model.
Included into the data model a first version for the placement of device. This feature allow a better use of the device data model in the smart sensoring domain .
See the Pull request.
In order to reduce the amount of work in the contribution of data models, we have a script that generates the key-values format of a normalized NGSI LD payload.
It has been operated on 46 data models currently in the repository.
In a close future instead of submitting 4 examples, it will be only necessary to include 2 examples, the normalized payloads for NGSI v2 and NGSI LD (the other two would be generated automatically).
All the repositories have been normalized in the naming of the core examples. So:
- Key values in NGSI v2 is named example.json
- Key values in NGSI LD is named example.jsonld
- Normalized (default) in NGSI v2 is named example-normalized.json
- Normalized (default) in NGSI LD is named example-normalized.jsonld
It is possible to have more examples in the directory. And in the same directory of every data model, there are other exports (csv) for the use of the data model users.
The goal is that this 4 examples were present in every data model
if you are browsing the repository you can realise that now there are several data models ended with the term ‘_incubated’.
This suffix denotes that there will be ‘soon’ a new data model.
The readme in the folder points to the repository where this data model is being created.
Once finished (all the docs, examples, etc) the _incubated suffix will be removed and the data model will be fully included into the data models.
PhreaticObserved_incubated (published 31-5-2021)
This is the first survey to the USERS of the Smart Data Models. We want to know what is more important to you and try to prioritize our efforts. This is an agile initiative, therefore we will take into very consideration your comments. Your survey is anonymous although if you wish you can include your email in comments and we will contact you regarding your comments.
You can answer it here.
Soon there will be another survey for the CONTRIBUTORS.
In order to provide a more transparent and participative approach to the creation and maintenance of data models, here you can see the three stages for a usual data model to be part of the official list of data models.
1.- Pending is the ‘wild’ zone where developers share their thoughts and create their data models. When finished (ready) they can create a PR on the right Subject repository.
2.- Harmonization is the repository for those new accepted models while they are fine-tuned or completed
3.- Subject means the repository in which the data model is officially published. Once there they are versioned when necessary.
|Control of contributions
|Scripts for checking
||Yes (only acceptance and on update)
|Code inside json schema
||Contributor + SDM control
||Yes but not managed
||Yes (Here the open ones)
- Anyone previous pending acceptance
- Members direct
SDM: Smart Data Models initiative