EIF Perspective attributes of Big Data Test Infrastructure (BDTI)

General information

Name of the solution: Big Data Test Infrastructure (BDTI)

Solution's owner: European Commission - DIGIT

Description:

The BDTI is a ready-to-use, free of charge, analytics cloud stack for the public sector offered to all European public administrations to experiment with open-source tools and foster the re-use of public sector data for a data-informed public sector.

Type of solution: Common services

Go to Solution

The Big Data Test Infrastructure (BDTI) implements the following:

Principles

Interoperability layers

Conceptual model

Model

Big Data Test Infrastructure (BDTI) implements the following EIF recommendations as explained below:

Recommendation 6 | Reusability

The Big Data Test Infrastructure offers support and guidance on how Member States can use their big data to deliver better public services. Hence, by re-using this building block and running pilots and proofs of concept, Member States cooperate in development of new solutions.
Recommendation 7 | Reusability

The Big Data Test Infrastructure enables the sharing and reuse of public administration data by allowing them to harness it for new big data driven solutions.
Recommendation 21 | Interoperability governance

Thanks to the experimentation platform and a repository of tools supporting Big Data pilots, BDTI helps big data pilot implementers to verify the interoperability readiness of their solutions by performing tests.
Recommendation 22 | Interoperability governance

Thanks to repository of tools available on the BDTI, project owners are encouraged to select and implement solutions that are interoperable and in line with European standards.
Recommendation 28 | Organisational interoperability

One of the key steps of setting up the Big Data Test Infrastructure is the documentation of core business processes associated with the data and the purpose for which it will be used.
Recommendation 30 | Semantic interoperability

The Big Data Test infrastructure departs from the assumption that public data is an open data and identifies ways in which public administrations can reuse this data to deliver better public services.