the data model for WeatherForecast of the datamodel.Weather is being extended with the property:
- precipitation: Amount of water rain expected.
the data model for WeatherForecast of the datamodel.Weather is being extended with the property:
The context.jsonld for smart data models has been updated to meet json ld requirements. Now they are implementing geojson requirements.
It affects the terms of bbox and coordinates. It could impact those elements having a geoproperty (most of the data models).
NEW VERSION!!
This post became obsolete, go for the new master sheet
This is a resource, especially for those who have limited knowledge of JSON schema.
If you want to create a basic version of a data model (not all JSON schema is implemented), you can use a copy of this spreadsheet as template. This spreadsheet is always available at https://bit.ly/schema_sheet short name.
You need to fill the blue cells for these parameters:
Once you’ve got the schema, grab some examples (It is always good to review the contribution manual) and you can make a Pull Request on any of the subjects of any domain in Github. Or just use this form.
NOTE 1: The first option will be attended quicker than the second.
NOTE 2: Do not write out of the blue cells (it will be ignored). And do not add or remove cells. The converter script looks for these precise locations in blue.
NOTE 3: Your spreadsheet has to be made public. (anyone with the link), otherwise, the script will not be able to retrieve your data.
Call:
Parameters: (Mandatories)
Output: A json schema based on the properties defined in the database. This is an alpha version so errors are not managed.
In case you are not an expert for creating a JSON schema (one of the elements of a data model)
On this page, you have a spreadsheet for helping with the first steps.
1.- Fill the spreadsheet with the names of the properties for your model
2.- fill the NGSI type (Property, Relationship or Geoproperty)
3.- In case of property, fill the data type (array and object types are currently not completely supported)
4.- Fill in the description
5.- Click the button, the page will reload
6.- voila! you have your json schema below the spreadsheet, just copy and paste into your favourite editor.
The python code for it is also made public in the utils directory in the data models repo.
It has been updated the format of the list of adopters of the data models (formerly were CURRENT-ADOPTERS.md markdown files), now in it is rename into ADOPTERS.yaml based on this yaml template which allows an automatic processing. (Further announcements could be included in a future).
Further instructions in the page Data Models Adopters how to located in the menu option Data models -> Data Models Adopters How to
New Subject, dataModel.Multimedia for allocating these data models related to multimedia management.
It is located in the Cross sector domain repository.
MediaEvent, to be contributed, will be dedicated to the events captured in a multimedia stream like face/plate recognition, etc.
The database for the searching on data models, properties and their descriptions has been expanded to allow filtering also by :
Additionally, it has been updated containing more than 11.000 items
Accessible from the front page in this widget (Structured check)
You can export the results
The new Subject of Satellite Imagery, inside the CrossSector domain, has released 6 new data models for Earth Observation:
– EOAnalysis
– EODataHub
– EOGeoDataLayer
– EOInstrument
– EOProduct
– EOSatellitePlatform
All the specifications (the text descriptions of the data model located in the /doc directory of each daat model) for the different domains and languages (currently French and Spanish besides English) have been updated to the new format. See an example in Spanish and French.
All of them are generated automatically from the json schema (which is the unique source of truth for the data model)
The contribution manual explains further details.
Raise an issue for any point you find in the new format.