Why do we need a MIRACLE?
MIRACLE's background and starting point
Providers of online content and services face highly fragmented systems of age classification, depending on country, region and type of medium.
Media content is being distributed more and more via electronic networks, and parents as well as their kids receive and access this content with electronic end devices. Where retail boxes traditionally came with visual age labels, the digitalisation of age labels is stuck in a very early stage of development. There is no extensive use of digital age labels yet, especially on the open internet. One of the main reasons for this is the high fragmentation of classification systems and labelling approaches among European Member States.
A solution that fosters an extended use of machine-readable classification data and age labels by content providers, filter software solution providers and users is a common information exchange reference model that enables cross-border machine-readable electronic labels, thus making existing label approaches and classification schemes technically interoperable. This results in an optimized usage of current classification knowledge and existing classification data, brings cost synergies for content providers and filter software solution providers. It also enables new innovative services in providing classification data.
MIRACLE’s project consortium spreads across five different member states and systems and includes classification bodies, safer internet nodes, self-regulatory bodies and filter software providers.
One language for all classification schemes
MIRACLE's approach and objectives
MIRACLE is here to provide a common technical specification for the machine-based exchange of existing and future classification data.
MIRACLE’s data model
Developing a common data scheme that can be used by all classification schemes and electronically labels is the first step of the project. Here, we build on the outcome of the CEO Coalition’s Task Force on Interoperability and Machine-Readability, so we are not starting from scratch. By publicly documenting the revisions and conducting consultations with experts and interested stakeholders, we integrate both practical experiences and technological advise.
A common data scheme alone will not suffice to let different classification schemes talk to each other. By implementing the data model in five different age rating contexts, we will show the feasibility of MIRACLE’s approach and provide a critical mass of interoperable classification data to fiddle around with. The implementing partners will publicly document their implementation strategies and provide best-practice approaches for all other interested partners planning to map their own scheme to the data model. By the way: We offer active support for stakeholders that consider providing/using MIRACLE data!