Data model

MIRACLE’s data model

The most important objective of the MIRACLE project is to provide a common data model for electronic content labels that includes all necessary categories and fields for content-related classification information. The MIRACLE updated Version 2.0 specification is accompanied by a thorough documentation, code snippet examples and potential forms of implementation. Currently the data model is serving as a framework for all project partners, external players planning to implement the data model, too, and for new players aiming at reducing the risks for sunk costs due to proprietary, less interoperable approaches.

Basic principles of the specification

The MIRACLE data model builds on existing age labeling practices, as it otherwise would undermine the efforts already taken by both companies and rating bodies, including the classification knowledge that goes with these schemes. Hence, for companies and bodies that already provide classification data or label online content electronically, no disadvantages will  result from the proposals made. The three basic requirements the data model therefore takes into account are:

  1. The data model is platform-neutral to reach maximum openness and compatibility between different systems and languages. It does not dictate labeling languages that have to be used, but rather the data structure, its categories, their fields and the possible values of single fields.
  2. It considers existing electronic labeling systems to ensure that these are not undermined by the interoperable data model but can easily be mapped onto it.
  3. It takes into account existing national and supranational classification schemes. By doing so, existing visual labels can easily be extended by respective electronic labels, ensuring backwards-compatibility with both the data model and the underlying traditional scheme.

Based on these principles, the data model aims at fostering a technically interoperable data structure among different rating schemes, technical implementations and distribution contexts of rated content.

Information following this specification is machine-readable and can be processed in different software, apps and electronic appliances.

One fundamental principle of the proposed data model is that no scheme has to provide information in all categories! As long as the data bits that are provided by a label do fit into any of the proposed categories the system is technically interoperable.

However, the more information a system or label provides, the better other IT systems will be able to use and process the data.

Blocks (categories) and fields of the data model

The structure of MIRACLE labels

Main blocks of data within each <age-declaration> dataset under  the overarching <label> root element are:

  • The body issuing the classification (<issuer>),
  • the scope of the dataset (<scope>),
  • age labels (<rating>),
  • content descriptors (<content-descriptors>),
  • feature descriptors (<feature-descriptors>), and
  • an enveloped XML signature.

MIRACLE specification - Documents

MIRACLE specification (v2.0) NEW

Date: 24 September 2015
Status: Version 2.0

The MIRACLE specification has been developed to fulfill needs of companies, intermediate services and end users. In case you feel something’s missing or want to comment on the current version, please don’t hesitate to mail us:

MIRACLE specification (v1.0)

Date: 20 October 2014
Status: Version 1.0


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