=Paper=
{{Paper
|id=Vol-3306/keynote
|storemode=property
|title=Data spaces for data ecosystems (invited paper)
|pdfUrl=https://ceur-ws.org/Vol-3306/keynote.pdf
|volume=Vol-3306
|authors=Boris Otto
|dblpUrl=https://dblp.org/rec/conf/vldb/Otto22
}}
==Data spaces for data ecosystems (invited paper)==
https://ceur-ws.org/Vol-3306/keynote.pdf
Data spaces for data ecosystems
Boris Otto1,2
1
TU Dortmund University, Joseph-von-Fraunhofer-Str. 2-4, 44227 Dortmund, Germany
2
Fraunhofer ISST, Emil-Figge-Str. 91, 44227 Dortmund, Germany
Abstract
The keynote talk motivates the sharing of data within ecosystems as a prerequisite for data-driven
innovation and proposes data spaces as an appropriate data infrastructure pattern in this regard. It puts
the current activities concerned with building and scaling data spaces in the context of the European
strategy for data which calls for the establishment of common European data spaces. Furthermore, the
talk introduces conceptual and technical foundations of data spaces and points to recent developments
in practice, such as Gaia-X and the IDS Association.
Keywords
Data space, data ecosystem, data sharing
1. The Role of Data Spaces in the European Data Economy
Many data-driven innovation scenarios require exchange and sharing of data among many
different partners within an ecosystem. Catena-X is an example from the automotive industry
which is characterized by distributed value creation across the entire production and supply
network, demands for supply chain transparency from the original equipment manufacturer
(OEM) over tier 1 and tier 2 suppliers to the raw material suppliers and shortage situations of
components and parts (e.g. semiconductor components). Catena-X aims at end-to-end data
value chains to allow for every ecosystem member to cope with current challenges such as
carbon footprint transparency and supply chain act compliance.
A second example can be found in the mobility domain. End-to-end inter-modal mobility
services can be only achieved if the different service providers in this case share information
about the mobile traveller, their preferences, payment information, about time-tables and context
information such as weather and traffic.
In fact, ecosystems emerge in situations where innovation cannot be achieved by one company
alone, but where different data need to be used and re-used collaboratively. Thus, ecosystems
can be understood as a multilateral form of organizing for joint customer innovation. They
balance the viability of the ecosystem at large and of its individual members. At present, data
ecosystems emerge in different domains such as healthcare, mobility, and manufacturing.
Data spaces provide data infrastructures for data ecosystems and play an important role for
the implementation of the European data strategy which calls for the establishment of common
DEco - First International Workshop on Data Ecosystems, 5 September 2022, Sydney
$ boris.otto@tu-dortmund.de (B. Otto)
https://iim.mb.tu-dortmund.de/ (B. Otto)
0000-0003-3189-9461 (B. Otto)
© 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
CEUR
Workshop
Proceedings
http://ceur-ws.org
ISSN 1613-0073
CEUR Workshop Proceedings (CEUR-WS.org)
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European data spaces. Apart from that, data spaces form a layer in an overall architecture stack
digital architecture stack and, thus, are important in the ongoing debate regarding technology
sovereignty in Europe.
To differentiate data spaces from data ecosystems on a conceptual level, applying an archi-
tecture approach is useful. Typically, private data from different data providers need to be
combined with context (often open) data. Examples can be found in healthcare (personalized
medicine), smart cities (traffic management, multi-modal mobility services), and manufacturing
(collaborative supply chain management, end-to-end supply chain transparency). Thus, data
sharing enables co-opetition in ecosystems when every individual member gives something to
gain something. With regard to data sharing in ecosystem, it is clear that a balance is required
between using the data and protecting the data. In this context, data spaces represent a promis-
ing data integration approach as they embrace a federated data architecture and typically come
with measures which foster data sharing while ensuring trust and data sovereignty among
participants.
2. Data Spaces Foundation
Research on data spaces has its roots in semantic web and Linked Data research. In general, a
data space is a distributed integration concept which does not require physical data integration
or a common schema. As mentioned above, data spaces are seen as a promising approach
to support data ecosystems which results in a set of business requirements. Among these
are, for example, support of different data ecosystem roles (such as data provider, data user,
and data sharing service intermediary), traceability of data in the ecosystem as well as policy
management, and trust among participants.
Gaia-X and the International Data Spaces (IDS) are initiatives kick-started in Europe, which
aim a setting de-facto standards for data spaces and, hence, supporting European regulation (e.g.
Data Governance Act and Data Act). The IDS Reference Architecture Model (RAM) envisages a
set of essential services to support data spaces. Among these are a broker service, a clearing
house and an app store service. Apart from that, the IDS RAM identifies the so-called IDS
connector as a key component. It provides access to data sources, manages policies which
constrain the use of the data and support the exchange of the data between data provider and
data user as well as to the various essential services. Policies are articulated as rules in the IDS
RAM. Typical data policies constrain the use of data for a certain period of time, allow/prohibit
forwarding of data and determine the number of read accesses to the data by a data user.
In this context, data sovereignty can be understood as the capability of a legal entity or
natural person to be self-determined regarding their shared data. Interoperability, traceability,
and enforcement of usage policies allow for executing data sovereignty in data ecosystems.
Gaia-X is a non-for-profit initiative aiming at setting de-facto standards for data sovereignty in
the cloud. It envisages four so-called federation services, namely "identity and trust", "sovereign
data exchange", "federated catalogue", and "compliance". Gaia-X and the IDS Association
work together in the Data Spaces Business Alliance (DSBA) on conceptual consistency and
architectural convergence.
Both initiatives aim at three deliverables, namely specifications, open-source software, and
2
compliance/certification tools.
3. Outlook
Today, the European data economy is characterized by the genesis and emergence of individual,
open data ecosystems. To achieve the vision of common European data spaces, however,
interoperability and sharing of data not only within individual data spaces but between them is
required.
Apart from that, critical mass must be achieved when it comes to adoption of the fundamental
architecture building blocks and software components. The EDC project is an open-source
project hosted by the Eclipse Foundation aiming an providing open-source implementations of
the most important data spaces components. It is coordinated by Fraunhofer and supported by
a number of large industrial partners.
Finally, the EU Data Spaces Support Centre will define common building blocks for data
spaces as a recommendation for the various data ecosystems which have already been started
or will be started soon.
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