Page 17 - Redefining smart city platforms: Setting the stage for Minimal Interoperability Mechanisms - A U4SSC deliverable on city platforms

use. One way of doing this is to develop a data lake, which can be held either “on premises” (within
an organization's own data centres) or “in the cloud”.

A data lake is a centralized repository that allows an organization to store all its data, structured as
well as unstructured, at any scale. It can store relational data from line-of- business applications, and
non-relational data from mobile apps, IoT devices and social media. The key is that the structure
of the data or schema does not need to be defined when the data are captured. This means that
all a city’s data can be stored without needing to know what questions it might need answers for
in the future. Only when specific data sets need to be analysed are analytics like SQL queries, Big
Data analytics, full text search, real-time analytics and machine learning brought in to provide the
insights required.

For a data lake to make data usable, it needs to have defined mechanisms to catalogue and secure
data to ensure semantic consistency, and to provide controls to manage access. Without these
elements, data cannot be found, trusted or used resulting in a “data swamp.”

A data space is very similar to a data lake, except that it is more focused on the need to share these
data and to integrate different sets of data to provide new insights. Data spaces provide federated
data ecosystems in which the participants can exchange data easily based on shared policies,
standards, rules and economic models that protect their rights and guarantee transparency and
fairness.

Data spaces can deal with all types of data, be it from smart objects, data marketplaces, cloud
platforms, individuals or organizations, openly available or confidential. They enable interoperability
among data sources, data intermediaries and services that consume data, and thereby open up
novel uses.

Data spaces are still in their early days and a great deal of work is needed to develop consistent
standards and architectures, and thus drive adoption. However, to take one example, the European
Union considers data spaces as a key part of its ambition for the free flow of data in a Digital Single
Market. Because of this, the Digital Europe Programme will support the development of an open-
source, cloud-to-edge middleware infrastructure that can be used in the different data spaces to
develop data interoperability within and across sectors.

Among the key data spaces being proposed by the European Commission is one that is focused
on smart communities. This will bring together existing local data ecosystems, and relevant
stakeholders, to join efforts and identify common principles for sharing large pools of data at the
EU level. The action will contribute to the definition of the technical infrastructure for data sharing
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across relevant sectors (e.g., mobility, energy, pollution, extreme weather events, waste) in a local
context. The aim will be to develop a consortium of relevant supply and demand-side stakeholders
to establish a cluster of data spaces between a large number of EU cities. The data spaces will
consist of the same kind of datasets (including real time), from the local platforms of each city,
making them accessible, re-usable and interoperable across borders and cities.

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