FIWARE Data Models
This repository contains:
- JSON Schemas and documentation on harmonized datamodels for different Smart Domains, particularly Smart Cities and Smart Agrifood.
- code that allows to expose different harmonized datasets useful for different applications. Such datasets are currently exposed through the FIWARE NGSI version 2 and/or NGSI-LD APIs (query).
This work is aligned with the results of the GSMA IoT Big Data Project. Such project is working on the harmonization of APIs and data models for fueling IoT and Big Data Ecosystems. In fact the FIWARE data models are a superset of the GSMA Data Models.
Some of the Data Models in this Repository have been adopted by a joint initiative between TM Forum and FIWARE Foundation. For more info please check https://github.com/smart-data-models/dataModels
Data Models adoption
A JSON Schema is provided for every harmonized data model. In the future all the documentation could be generated from a JSON Schema, as it is part of our roadmap. The different JSON Schemas usually depend on common JSON Schema definitions found at the root directory of this repository.
There are different online JSON Schema Validators, for instance: http://jsonschemalint.com/. For the development of these schemas the AJV JSON Schema Validator is being used. For using it just install it through npm:
npm install ajv npm install ajv-cli
validate.sh script is provided for convenience.
Note: JSON Schemas capture the name and data type of each Entity Attribute.
For instance, this means that to test JSON schema examples with a
FIWARE NGSI version 2 or
API implementation, you need to use the
keyValues mode (
How to contribute
Contributions should come in the form of pull requests.
Please note that some of the Data Models in this Repository have been adopted by a joint initiative between TM Forum and FIWARE Foundation. Pull Requests for those Data Models shall be done against the corresponding Repository at the https://github.com/smart-data-models/ Organization
New data models should be added under a folder structured as follows:
README.md: A summary file (as an extract from the spec file), e.g. README.md of WeatherObserved
schema.json: The JSON Schema definition, e.g. schema.json of WeatherObserved
example.json: One or more JSON example file, e.g. example.json of WeatherObserved
example-normalized.json: One or more JSON example file in NGSI v2 normalized format, e.g. example-normalized.json of WeatherObserved
example-normalized-ld.jsonld: One or more JSON example file in NGSI-LD normalized format, e.g. example-normalized-ld.jsonld of WeatherObserved
The name of the folder should match the Entity Type used in the JSON Schema
NewModel). For data models including more entities, a hierarchical
folder should be used. The parent folder can include common JSON schemas shared
among the entities. e.g.:
newmodel-schema.json: the common schema for the different entities.
To facilitate contributions and their validation, we developed a tool that is also used for the Continuous Integration of FIWARE Data Models. The FIWARE Data Model validator checks the adherence of each data model to the FIWARE Data Models guidelines.
For using it just install it through npm:
npm install -g fiware-model-validator
More details are available in the validator documentation.
Formatting and Text Correction
When creating a Pull Request, please ensure the files are properly formatted,
the Husky should do this automatically on
git commit, but the files can be manually formatted at any time using the
To check for spelling mistakes and dead links in the text within the Data Model, run the text linter as shown:
MIT © 2019 FIWARE Foundation e.V.
All the code in this repository is licensed under the MIT License. However each original data source may have a different license. So before using harmonized data please check carefully each data license.
All the data models documented here are offered under a Creative Commons by Attribution 4.0 License.