Data models guidelines

This is a set of guidelines for defining new data models. Further information and a guideline update can be found at D2.2 Synhronicity IoT LSP

Before creating a new data model, explore the existing ones to be sure there is already a data model that covers your use case. The search box in the ReadTheDocs page can help you to search for specification connected to your needs. Recall to use synonyms in your search. E.g. what you might call Public Transport already exists under UrbanMobility.

If you are looking for guidelines on adoption of existing data models, please refer to How to use FIWARE Harmonised Data Models in your projects section.


  • Use English terms, preferably American English.
  • Use camel case syntax for attribute names (camelCase).
  • Entity type names must start with a Capital letter, for instance, WasteContainer.
  • Use names and not verbs for attribute names, ex. name, qualifying it when necessary, ex. totalSpotNumber or dateCreated.
  • Avoid plurals in attribute names, but state clearly when a list of items fits. Ex. category.


  • Check for the existence of the same attribute on any of the other models and reuse it, if pertinent.
  • Have a look at trying to find a similar term with the same semantics.
  • Try to find common used ontologies or existing standards well accepted by the Community, or by goverments, agencies, etc. For instance, Open311 for civic issue tracking or Datex II for transport systems.

Data types

  • When possible reuse data types (Text, Number, DateTime, StructuredValue, etc.).

Attribute definition

  • Enumerate the allowed values for each attribute. Generally speaking it is a good idea to leave it open for applications to extend the list, provided the new value is not semantically covered by any of the existing ones.

  • State clearly what attributes are mandatory and what are optional. If needed state clearly what is the meaning of a null value.


  • Define a default unit for magnitudes. Normally it will be the unit as stated by the international system of units.

  • If a quantity is expressed in a different unit than the default one, use the unitCode metadata attribute.

Relative values

  • Use values between 0 and 1 for relative quantities, which represent attribute values such as relativeHumidity, precipitationProbability, etc.

Modelling location

  • Use address attribute for civic locations as per

  • Use location attribute for geographical coordinates. Ideally use GeoJSON for codifying geospatial properties. That works from Orion 1.2 on. If not use, old NGSI version 1 type coords.

Modelling linked data

  • When an entity attribute is used as a link (relationship) to other entities two modelling options are possible:

    + A/ Name the attribute with the prefix `ref` plus the name of the target (linked) entity type. For instance `refStreetlightModel`, represents an attribute

    which contains a reference to an entity of type StreetlightModel. This option has been extensively used by data models initially intended to be used with NGSIv2 . + B/ Name the attribute using a verb (plus optionally an object) such as hasStop, operatedBy, hasTrip, etc. This option is the one advocated by NGSI-LD, as in NGSI-LD URNs are used to identify entities, and NGSI-LD URNs already convey the type of the target entity, for instance urn:ngsi-ld:gtfs:Stop:S123.

As the current trend is to align with NGSI-LD as much as possible, B option can be considered as the recommended one and A option is to some extent "deprecated".

Date Attributes

  • Attribute type must be DateTime.

  • Use the date prefix for naming entity attributes representing dates (or complete timestamps). Ex. dateLastEmptying.

  • dateCreated must be used to denote the (digital) entity's creation date.

  • dateModified must be used to denote the (digital) entity's last update date.

  • dateCreated and dateModified are special entity attributes provided off-the-shelf by NGSIv2 implementations. Be careful because they can be different than the actual creation or update date of the real world entity represented by its corresponding digital entity.

  • When necessary define additional attributes to capture precisely all the details about dates. For instance, to denote the date at which a weather forecast was delivered an attribute named dateIssued can be used. In that particular case just reusing dateCreated would be incorrect because the latter would be the creation date of the (digital) entity representing the weather forecast which typically might have a delay.

Dynamic attributes

  • Use a metadata attribute named timestamp for capturing the last update timestamp of a dynamic attribute. Please note that this is the actual date at which the measured value was obtained (from a sensor, by visual observation, etc.), and that date might be different than the date (metadata attribute named dateModified as per NGSIv2) at which the attribute of the digital entity was updated, as typically there might be delay, specially on IoT networks which deliver data only at specific timeslots.

Internationalization (i18N)

There can be certain entity attributes which content is subject to be internationalized. For instance, the description of a Point of Interest. The internationalization (i18N) guidelines for the FIWARE Data Models are defined as follows:

  • By default, the value of an attribute subject to be internationalized should be expressed in American English (en-US). However there can be situations where an English term is not the most common one, for instance, the English exonym for the city of Livorno (Italy) is a very obscure term, Leghorn. In such situations, the common international name (Livorno in our example) in latin script should be used.

  • There shall always be a term for the original attribute, i.e. it is not allowed to have entity representations which only contain terms associated to language variants.

  • For each language variant of an internationalized attribute, there shall be an additional entity attribute which name shall be in the form:

<AttributeName>_<LanguageTag> where AttributeName is the original attribute name and LanguageTag shall be a language tag as mandated by RFC 5646. W3C provides guidelines on how to use language tags.

JSON-LD can facilitate developers to parse internationalized entity representations, thus Context Producers are encouraged to use JSON-LD (provided that the backing implementations support it).

When parsing plain JSON content, developers should validate that the corresponding JSON terms are actually conveying a language variant of an attribute. For instance, by validating that the term's suffix actually corresponds to a valid language tag and by checking that the corresponding original attribute is contained in the entity.


An entity may contain an attribute named description. The value of such attribute shall be expressed in American English. Additionally it might exist an attribute named description_es used to convey the value of such a description attribute in Spanish.

Some of the most used attributes

In case of doubt check other existing models!

  • name
  • alternateName
  • description
  • serialNumber
  • category
  • features
  • source
  • relativeHumidity
  • temperature

How to contribute

Contributions should come in the form of pull requests. Fork the repository, Create a branch containing your changes, and proceed with a Pull Request.

Pull Request should be easy to review, so if the model, or the changes you are proposing are wide, please create different pull requests.

New data models should be added under a folder structured as follows:

The name of the folder should match the entity type used in the JSON Schema (e.g. NewModel). For data models including more entities, a hierarchical folder should be used. The father folder can include common JSON schemas shared among the entities. e.g.:

  • specs/
    • NewModel/
      • doc/
      • newmodel-schema.json: the common schema for the different entities.
      • NewModelEntityOne/
        • doc/
        • schema.json
        • example.json
      • NewModelEntityTwo/
        • doc/
        • schema.json
        • example.json