Towards Interoperable Data Spaces: Comparative Analysis of Data

Space Implementations Between Japan and Europe

Shun Ishihara

and Taka Matsutsuka

Fujitsu Limited, Kawasaki, Kanagawa 211-8588, Japan

Keywords:

Trust, Analysis, Data Space, Interoperability, DATA-EX, Catena-X.

Abstract:

Data spaces are evolving rapidly. In Europe, the concept of data spaces, which emphasises the importance

of trust, sovereignty, and interoperability, is being implemented as a platform such as Catena-X. Meanwhile,

Japan has been developing its approach to data sharing, in line with global trends but also to address unique

domestic challenges, resulting a platform such as DATA-EX. Achieving interoperability between European

and Japanese data spaces remains a critical challenge due to the differences created by these parallel advances.

Although interoperability between data spaces has several aspects, compatibility of trust in the participating

entities and the data exchanged is a signiﬁcant aspect due to its inﬂuence on business. This paper undertakes a

comparative analysis of DATA-EX and Catena-X while focusing on aspect of trust, to explore the challenges

and opportunities for achieving interoperability between Japanese and European data spaces. By examining

common data exchange processes, key objects such as datasets, and speciﬁc evaluation criteria, the study

identiﬁes gaps, challenges, and proposes actionable solutions such as inter-exchangeable topology. Through

this analysis, the paper aims to contribute to the ongoing discourse on global data interoperability.

1 INTRODUCTION

The rapid evolution of data spaces is transforming

the landscape of secure and interoperable data sharing

across industries and regions. In Europe, the concept

of data spaces, supported by initiatives such as the

European Data Strategy, emphasises the importance

of trust, sovereignty, and interoperability. Mean-

while, Japan has been developing its approach to data

sharing, in line with global trends but also address-

ing unique domestic challenges. Despite these paral-

lel advancements, achieving interoperability between

European and Japanese data spaces remains a critical

challenge due to differences in governance, technol-

ogy standards, and authentication frameworks. Inter-

operability between data spaces has various aspects

such as compatibility of technologies like connectors,

compatibility of objects handled in data spaces, and

compatibility of trust on participating entities and the

data exchanged. Compatibility of trust is a signiﬁ-

cant issue among these aspects, because actual data

exchange is never established without trustworthiness

between participants.

https://orcid.org/0009-0005-4584-2695

https://orcid.org/0000-0002-2673-6708

This paper undertakes a comparative analysis of

DATA-EX and Catena-X to explore the challenges

and opportunities for achieving interoperability be-

tween Japanese and European data spaces. The anal-

ysis is focusing on trust. By examining common data

exchange processes, key objects such as participants,

datasets, and data catalogs, and speciﬁc criteria for

evaluation, the study identiﬁes gaps and proposes ac-

tionable solutions. The ﬁndings are based on a thor-

ough analysis of relevant documentation, highlighting

areas for alignment and improvement.

Through this analysis, the paper aims to contribute

to the ongoing discourse on global data interoperabil-

ity. It proposes an inter-exchangeable topology that

bridges regional differences while addressing com-

mon challenges.

The rest of the paper is structured as follows. Sec-

tion 2 reviews the development of data spaces in Eu-

rope and Japan, and examines the role of trust anchors

and interoperability challenges. Section 3 describes

the analysis method, including key evaluation crite-

ria and data sources. Section 4 presents the analy-

sis results, comparing participants, devices, datasets,

and other key elements of the two platforms. Sec-

tion 5 discusses identiﬁed gaps, proposes an inter-

exchangeable topology, and addresses speciﬁc chal-

318

Ishihara, S., Matsutsuka and T.

Towards Interoperable Data Spaces: Comparative Analysis of Data Space Implementations Between Japan and Europe.

DOI: 10.5220/0013460600003967

In Proceedings of the 14th International Conference on Data Science, Technology and Applications (DATA 2025), pages 318-328

ISBN: 978-989-758-758-0; ISSN: 2184-285X

lenges. Section 6 reviews related works, and Section

7 concludes with ﬁndings and future directions.

2 BACKGROUND

In recent years, the importance of the data economy

has been steadily increasing, with data spaces evolv-

ing through unique approaches in different regions

and countries. Data spaces refer to infrastructures or

frameworks that enable the sharing and integration of

data, allowing participating organisations and individ-

uals to maintain data sovereignty while securely shar-

ing information. This section provides an overview of

the development of data spaces in Europe and Japan,

highlights their characteristics, and identiﬁes chal-

lenges for the future.

2.1 Development of Data Spaces in

Europe

Europe has been accelerating its efforts to maximise

the potential of the data economy. Central to these

efforts are the European Data Strategy

and the con-

cept of data sovereignty. The European Data Strat-

egy aims to foster data sharing within and beyond

the region, positioning Europe as a global leader in

the data economy. This strategy is rooted in the be-

lief that data should be managed and utilised fairly,

without being disproportionately controlled by a few

companies or nations. Data sovereignty refers to the

principle that entities owning and managing data have

the exclusive right to determine its usage. For ex-

ample, this includes the control over the data, even

if the data is shared with other parties. Europe has

reinforced this principle through stringent data pro-

tection regulations such as General Data Protection

Regulation (GDPR), ensuring that individuals and or-

ganisations can safeguard their rights while contribut-

ing to the data economy. Initiatives like Interna-

tional Data Spaces Association (IDSA) and Gaia-X

exemplify Europe’s approach to data spaces. IDSA

focuses on creating secure and standardised frame-

works for data sharing across various industries, en-

suring that data sovereignty is maintained. Mean-

while, Gaia-X, a European initiative for cloud infras-

tructure and data sharing, aims to establish an interop-

erable ecosystem where data and services can be se-

curely exchanged while adhering to European values

such as transparency and privacy. Together, these ini-

https://commission.europa.eu/strategy-and-policy/

priorities-2019-2024/europe-ﬁt-digital-age/

european-data-strategy en

tiatives highlight Europe’s commitment to fostering a

trusted data economy by addressing technical, legal,

and ethical challenges inherent in cross-border data

exchanges. With this multipronged strategy, Europe

seeks to establish itself as a leader in the development

of a robust, scalable, and ethical data ecosystem.

2.2 Development of Data Spaces in

Japan

Similarly, Japan has pursued its own approach to de-

veloping data spaces, centerd on the concepts of So-

ciety 5.0

and Data Free Flow with Trust (DFFT)

Society 5.0 is a national strategy that envisions a

super-smart society where cyberspace and physical

space are seamlessly integrated to address societal

challenges through data utilisation. Within this con-

cept, DFFT emphasises the importance of trust in data

ﬂow, enabling secure data sharing across national and

organisational boundaries. The second phase of the

Strategic Innovation Promotion Program (SIP) and its

subsequent evolution into DATA-EX (Koshizuka and

Mano, 2022) have constituted signiﬁcant advances in

Japan’s data space endeavours, spearheaded by gov-

ernmental initiatives. In the context of SIP, a con-

nector called Connector Architecture for Decentral-

ized Data Exchange (CADDE)

has been developed

with the objective of enabling secure and efﬁcient

data sharing between organisations. This founda-

tional technology constituted the basis for the subse-

quent establishment of the DATA-EX initiative, which

was launched within Data Society Alliance (DSA).

The objective of this initiative is to expand the ca-

pabilities of CADDE into a broader data exchange

infrastructure, thereby promoting interoperability and

trust in data sharing across sectors. Another notable

effort is the Ouranos Ecosystem (Ministry of Econ-

omy, Trade and Industry, 2023) project, which began

in 2022 under the leadership of Information Process-

ing Agency’s Digital Architecture Design Center (IPA

DADC). The project’s objective is to enhance battery

traceability within the automotive manufacturing sup-

ply chain as well as ensure compliance with Euro-

pean battery regulations. This addresses the critical

need for transparency and accountability in tracking

battery production and usage. In 2023, the imple-

mentation phase was completed, establishing a tech-

nical foundation for real-world application. By 2024,

the operational body, Automotive and Battery Trace-

ability Center Association (ABtC), was established,

https://www8.cao.go.jp/cstp/english/society5 0/

https://www.digital.go.jp/en/policies/dfft

https://sip-cyber-x.jp/en/

Towards Interoperable Data Spaces: Comparative Analysis of Data Space Implementations Between Japan and Europe

319

marking the transition to full-scale operation and con-

tributing to the advancement of sustainable supply

chain management.

2.3 The Importance of Trust Anchors in

Data Spaces

Trust anchors are critical for ensuring the security, au-

thenticity, and reliability of data spaces, enabling par-

ticipants to conﬁdently share data while maintaining

sovereignty. Key technologies include digital identity

systems like decentralised identiﬁers (DIDs), which

allow entities to manage their own digital identities

securely, and veriﬁable credentials (VCs), which pro-

vide proof of attributes or certiﬁcations without ex-

posing unnecessary information. Governance frame-

works, like those from IDSA, establish common rules

for interoperability and trust. Together, these tech-

nologies and standards build a secure and reliable

foundation, fostering participation and unlocking the

full potential of global data spaces.

2.4 Challenges of Interoperability

Between Japan and Europe

Currently, data spaces in Japan and Europe are built

on different technological bases, making interoper-

ability challenging. In Europe, standardisation of data

space and trust is being pursued in IDSA and Gaia-X

respectively. In Japan, meanwhile, the DATA-EX and

Ouranos Ecosystem are pursuing their own individ-

ual standardisation agendas. However, the need for

interoperability between these data spaces is becom-

ing increasingly critical, particularly for addressing

global issues such as carbon footprint transparency

and international supply chain management. Inter-

operability between data spaces has various aspects

such as compatibility of technologies which means

connectors or related components can connect each

other seamlessly beyond a data space, compatibility

of objects which means expression of objects han-

dled in data spaces can be interpreted uniquely, and

compatibility of trust which means trustworthiness of

participating entities and the data exchanged is simi-

lar among data spaces. A signiﬁcant challenge lies in

the compatibility of trust. Without robust mechanisms

to guarantee trust, resistance to data sharing may in-

crease, stalling the ﬂow of data and hindering the data

economy. Therefore, creating systems that integrate

or harmonise the technological foundations of Japan

and Europe is essential. Addressing this challenge

will pave the way for a sustainable and interconnected

data economy in the future.

3 ANALYSIS METHOD

As a ﬁrst step towards solving the challenge men-

tioned above, we undertake a comparative analysis of

two prominent data space platforms in Japan and Eu-

rope from a trust perspective. We selected DATA-EX

in Japan and Catena-X in Europe as the representa-

tive data space platforms due to substantial number

of analysable documents and the past maturity evalu-

ation (Dam et al., 2023) (Bacco et al., 2024).

In this section, we examine a common data ex-

change process, key objects such as participants,

datasets, and data catalogs, and speciﬁc criteria for

evaluation, and available documents used for analy-

sis.

3.1 Common Data Exchange Process

First, we decided on a common data exchange process

to make a fair comparison between the two platforms.

We researched principal whitepapers written in Japan

and Europe to compare regional differences.

A whitepaper from Data Society Alliance (DSA,

2022) described processes, functions and elements

when data providers and data consumers who were

in different organisations or departments plan to han-

dle data across existing systems or applications. The

paper attempted to deﬁne the data exchange process.

Six phases below were extracted as the data exchange

process in the paper.

• Planning: A data provider prepares the data to be

transferred. A data consumer designs a new ser-

vice or application to use the data and deﬁnes data

requirements.

• Discovery: The data provider describes and pub-

lishes the catalog of the data. The data consumer

searches for the data to meet requirements through

a catalog search service.

• Contract: The data provider and the data con-

sumer negotiate terms and conditions of the data

exchange and conclude a contract.

• Transfer: The data provider makes the data avail-

able in an accessible location. The data consumer

obtains the data from the provider and uses it

within scope of the contract.

• Payment: The data consumer pays for the data

based on the contract.

• Veriﬁcation: The data provider and the data con-

sumer verify the status of the contract fulﬁlment

(e.g., progress of data delivery or payment).

A whitepaper from International Data Spaces As-

sociation (IDSA, 2023) deﬁned a reference architec-

ture model to generalise concepts, functionality, and

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320

overall processes for creating a secure network of

trusted data. Their reference architecture model de-

ﬁned ﬁve layers: business layer, functional layer, in-

formation layer, process layer, and system layer. The

process layer deﬁned ﬁve phases below as the inter-

actions that take place between the different com-

ponents (e.g., connectors) of the international data

spaces.

1. Onboarding, i.e. what to do to

be granted access to the International Data

Spaces as a Data Provider or Data Consumer.

2. Data Offering, i.e. offering data or

searching for a suitable data.

3. Contract Negotiation, i.e. accept data

offers by negotiating the usage policies.

4. Exchanging Data, i.e. transfer data be-

tween IDS Participants.

5. Publishing and using Data Apps, i.e. in-

teracting with an IDS App Store or using IDS

Data Apps.

There are some overlaps between the phases of

DSA and IDSA. Table 1 shows the correspondence

between DSA and IDSA phases.

Table 1: Correspondence between DSA and IDSA phases.

DSA IDSA

- Onboarding

Planning -

Discovery Data Offering

Contract Contract Negotiation

Transfer Exchanging Data

Publishing and using Data Apps

Payment -

Veriﬁcation -

Considering this correspondence, we extract the

onboarding phase from IDSA’s process and all six

phases from the DSA’s process as a common data ex-

change process.

3.2 Target Objects

Based on the common data exchange process, we

identiﬁed objects which are generated in a data ex-

change as a target for our analysis. (The term “object”

here means a digital entity that requires some kind of

trust.) As a result, six objects shown in Table 2 were

identiﬁed.

In the onboarding phase, a data space operating

company validates an applicant organisation and then

creates a user account. We deﬁned this account as

a “Participant” object. Following the acquisition of

the user account, the applicant organisation prepares

Table 2: Generated objects in the common data exchange

process.

Phase Generated object

Onboarding Participant (data consumer or

provider account)

Device (server and endpoint on

which connector works)

Planning Dataset

Data catalog

Discovery - (only refer data catalogs)

Contract Contract

Transfer Sending & Receiving Log

Payment

Veriﬁcation - (only refer previously generated

log)

servers and endpoints on which the connectors op-

erate. We deﬁned these servers and endpoints as

“Device” objects. During the planning phase, a data

provider prepares datasets to provide and data cata-

logs to advertise their datasets. We deﬁned these two

as “Dataset” and “Data catalog” objects. In the con-

tract phase, the data provider and consumer conclude

a contract about a data exchange. A record of the con-

tract is stored as a paper or a digital data. We deﬁned

these records as “Contract” objects. In the transfer

and payment phases, actual data and money are trans-

ferred in accordance with the contract. The records of

these transactions are stored as a digital log to prove

fulﬁlment of the contract. We deﬁned these logs as

“Sending & Receiving Log” objects.

3.3 Analysis Criteria

We have developed an analysis criteria on trust based

on six analysis target objects.

In order for an object to be considered trustworthy,

trust needs to be satisﬁed at two steps: when gener-

ated and when veriﬁed. The ﬁrst step is to ensure trust

of the object when it is generated. In the case of the

participant object, an applicant is validated by a sys-

tem administrator in a certain aspect (e.g., existence,

eligibility, agreement to rules). The second step is to

verify whether trust is ensured during the operation

of the data space. In the case of the participant object,

after the validation, the system administrator issues a

credential (e.g., user id and password), and the system

veriﬁes the credential on login. Considering these two

steps, we created two analysis perspectives.

• p1) How to ensure trust in the object generation

• p2) How to verify trust in operation

The ﬁnal analysis criteria using identiﬁed objects

and analysis perspectives is shown in Table 3.

Towards Interoperable Data Spaces: Comparative Analysis of Data Space Implementations Between Japan and Europe

321

Table 3: Analysis criteria.

p1 p2

Participant

Device

. . .

The horizontal axis represents analysis perspec-

tives, while the vertical axis represents identiﬁed ob-

jects. Employing these criteria facilitates comprehen-

sive analysis.

3.4 Documents Used for Analysis

Finally, we selected the technical documents to be

used in the analysis.

With regard to DATA-EX, we selected technical

documents in both the industrial data linkage infras-

tructure

and CADDE documents

. Digital Agency is

facilitating its implementation as industrial data link-

age infrastructure and publishing its basic design doc-

uments. Note that some documents are not included

in the industrial data linkage infrastructure’s publica-

tion but in the CADDE publication because indus-

trial data linkage infrastructure is an enhancement of

CADDE.

With regard to Catena-X, we selected technical

documents in both the technical standards (Catena-

X, 2024) and deliverables of the Eclipse Tractus-X

project

. Catena-X Automotive Network e.V. is pub-

lishing technical standards, but it doesn’t cover all

speciﬁcations of Catena-X. Eclipse Tractus-X is an

open-source project to develop reference implementa-

tions of Catena-X and providing some technical docu-

ments (not comprehensive) and source code. The ver-

sion of the selected documents was adhered to CX-

Jupiter release as Catena-X is under continuous de-

velopment.

4 ANALYSIS RESULT

Summary of the analysis result is shown in Table 4.

In this summary, function or method of each data

space is described. N/A means that there is no func-

tion or method. There is N/A in the dataset, data

catalog, and contract, because the trust of these ob-

jects should be ensured by the participant in princi-

ple. Therefore, described function or method of these

objects is not comprehensive solution but solution to

https://www.digital.go.jp/en/policies/

industrial-data-integration

https://github.com/CADDE-sip

https://github.com/eclipse-tractusx

complement the trust ensured by the participant. De-

tails of the analysis results for each object are shown

below.

4.1 Participant

About p1, both platforms validate the applicant or-

ganisation through an onboarding portal. A validation

process of each platform is shown in Figure 1.

Figure 1: Validation process of the participant.

In both platforms, the applicant organisation sub-

mits organization information to the operating com-

pany through onboarding portal, but there are two dif-

ferences.

The ﬁrst difference is the validation method and

standard (illustrated in Figure 1 as 3d,3c1,3c2,3c3).

The operating company in both platforms validates

similarly submitted information, but the validation

standards are not the same. In addition, partici-

pant authentication is performed by an authentica-

tion framework in Catena-X. This framework is called

as Gaia-X Digital Clearing House (Sprenger, 2024),

which automatically validates an organisation from

different perspectives (e.g., notarisation check with

LEI code). This framework can be used commonly

by multiple data spaces. By using this framework,

one data space can obtain compatibility about trust of

the participant with another data space.

The second difference is a credential which the ap-

plicant organisation receives (illustrated in Figure 1

as 5d,5c). In DATA-EX, a participant registry is an

identity provider, or IdP, so the applicant organisation

is registered in form of an account and receives the

id and password of the account as a credential. In

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322

Table 4: Summary of the analysis result.

p1) How to ensure trust in the object generation p2) How to verify trust in operation

DATA-EX Catena-X DATA-EX Catena-X

Participant

Onboarding Portal JWT (issued via

OIDC protocol &

presented via

original protocol)

VC (issued &

presented via

original protocol)

Validation with

DATA-EX speciﬁc

standards

Validation with

Catena-X speciﬁc

standards

Device

Validation with

DATA-EX speciﬁc

standards

Validation with

Catena-X speciﬁc

standards

Connector endpoint resolver and

general HTTPS veriﬁcation based on

X.509 certiﬁcate

Validation with CA’s common standards

(e.g., Extended Validation)

Dataset Data model & vocabulary repository Signable data pack-

age

N/A

Data cata-

log

Modiﬁed DCAT v2 format catalog cre-

ation function

N/A

Contract N/A Connector’s con-

tract negotiation

API

N/A (External contract brokering ser-

vice is recommended, and connector

can work with it)

Sending &

Receiving

Log

Centralized log

management ser-

vice

N/A (local log) Centralized log

management ser-

vice

N/A (local log)

Catena-X, on the other hand, the participant registry

is a veriﬁable data registry (VDR), so the applicant

organisation is registered in form of a DID document

which holds a public key and receives a veriﬁable cre-

dential signed by a private key of the operating com-

pany.

The difference in the credential affects function or

method on p2. In DATA-EX, the credential is handled

via the OpenID Connect (OIDC) protocol shown in

Figure 2.

Figure 2: Veriﬁcation process of the participant in DATA-

EX.

On OIDC protocol, the veriﬁcation is performed

by the authorisation server managed by the operating

company. In Catena-X, on the other hand, the creden-

tial is handled via the Decentralized Claims Protocol

(DCP) (Andrea et al., 2024), shown in Figure 3.

Figure 3: Veriﬁcation process of the participant in Catena-

On DCP, the veriﬁcation is performed by the data

provider, who is a veriﬁer. The operating company

only provides an issuer’s public key through the VDR.

The role of the operating company in the veriﬁcation

is a major difference.

4.2 Device

As a ﬁrst step on p1, both platforms validate the de-

vice against platform speciﬁc standards and register

device’s endpoint into a connector endpoint resolver.

The connector endpoint resolver provides the con-

Towards Interoperable Data Spaces: Comparative Analysis of Data Space Implementations Between Japan and Europe

323

nector endpoint to the data consumer according to

given search keys (e.g. identiﬁers representing the

data provider or its connector). The available search

keys are different on each platform, but the endpoint

provided by the resolver has assurance that has been

validated by the operating company.

As a second step on p1, external Certiﬁcation Au-

thority (CA) validates the device against common

standards (e.g., Extended Validation) and issues a

SSL certiﬁcate. This SSL certiﬁcate includes domain

information used by the endpoint, so it can prove

ownership of the endpoint.

In terms of p2, consistency between the endpoint

and the device showed by the endpoint can be veriﬁed

by an SSL certiﬁcate.

4.3 Dataset

The trust of the dataset depends on the data provider

in principle because the dataset is generated by the

data provider. Thus, in terms of p1, both platforms do

not have any validation function or method but sup-

porting function to improve portability of the dataset

across participants. Portability of the dataset here

means that one participant can use the dataset from

another participant without any conversion. For en-

suring portability of the dataset, all participants must

adopt same semantics on their dataset. In order to

standardise semantics of the dataset in a data space,

both platforms have a repository (called as vocabu-

lary repository in DATA-EX, semantic hub in Catena-

X) of data models and vocabularies. This reposi-

tory manages the vocabularies and models expressing

datasets in the data space. The data provider organiza-

tion can use this repository as a reference or propose

new vocabularies and models if existing data models

do not ﬁt the purpose. On Catena-X also has over

100 pre-deﬁned models and vocabularies with exter-

nal reference to ECLASS

In terms of p2, only DATA-EX supports a signable

format of datasets, called as Data Distribution Pack-

age (DDP). DDP allows the data consumer to verify

the creator’s authenticity of the dataset.

4.4 Data Catalog

In terms of p1, for the same reason as the dataset, the

trust of the data catalog depends on the data provider

and both platforms have a function to keep the data

catalogs interoperable in a data space. Both plat-

forms basically restrict the catalog to the DCAT Ver-

sion 2 (W3C, 2024) format by this function (data cat-

https://eclass.eu/en/

alog creation tool do in DATA-EX, connector do in

Catena-X).

In terms of p2, both platforms have no functions

to support.

4.5 Contract

The trust in the contract should be ensured by both

data consumers and providers, as the contract is an

object created by both participants. In terms of p1,

Catena-X supports the communication between both

participants through the connector’s contract negotia-

tion API, which is deﬁned in the dataspace protocol

(IDSA, 2024). Using this API, the data provider can

propose a contract candidate and the data consumer

can send the conﬁrmation result (agree or disagree).

DATA-EX doesn’t have this functionality.

In terms of p2, however, the contract should be

concluded in a commonly used manner because the

contract has legal requirements. For this reason, both

platforms recommend concluding the contract outside

of the platform (e.g., via an external contract broker-

ing service such as DocuSign). The connectors on

both platforms can work with the external contract

brokering service.

4.6 Sending & Receiving Log

On both platforms, the sending and receiving log is

basically generated by the connector and managed in

the participant’s device. Only DATA-EX has an op-

tional centralised management service (Provenance

Management Service). This service stores the send-

ing and receiving logs to construct the proof of origin,

which has the structures shown in Figure 4.

Type: Sent

URL: https://aa.com/bb.zip

Date: 2024/03/12T02:34:21

Provider: 302bd3

Consumer: dji30x

Signature: (by Provider)

Type: Received

URL: https://aa.com/bb.zip

Date: 2024/03/12T02:34:53

Provider: 302bd3

Consumer: dji30x

Signature: (by Consumer)

Type: Sent

URL: https://aa.com/bb.zip

Date: 2024/04/02T14:21:02

Provider: dji30x

Consumer: nc923o

Signature: (by Provider)

...

Figure 4: An example of provenance.

The provenance consists of a repetition of a sent

and received log. In terms of p1, by holding digital

signatures by both the data provider and consumer in

logs, the consistency of the sent and received logs can

ensure the occurrence of the data transfer. In terms of

p2, the provenance is veriﬁable as each log is signed

by the creator of the log.

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324

5 DISCUSSION

Based on the analysis results above, we discuss the

challenges of the international connectivity of data

spaces. First, we review the gaps identiﬁed as shown

in Table 4. Second, we discuss an inter-exchangeable

topology based on the review. Third, we discuss two

challenges based on the topology. Finally, we discuss

possible policy alignment for addressing two chal-

lenges.

5.1 Review of Gaps

5.1.1 Participant

It is difﬁcult to close the gap because of the differ-

ent ways in which trust is ensured and veriﬁed. The

trust of participants on each platform is not the same,

because participants are validated with platform spe-

ciﬁc standards at generation time. In addition, the

difference of veriﬁcation method makes it difﬁcult to

standardise data exchange protocols. Catena-X can-

not adopt DATA-EX’s OIDC protocol as veriﬁcation

method because Self Sovereign Identity (SSI) is an

essential requirement in Europe. Similarly, adopting

Catena-X’s DCP as a veriﬁcation method on DATA-

EX could take a long time because there are no laws

or government guidelines such as eIDAS2.0 on digital

identity wallet in Japan.

5.1.2 Device

In both platforms, the device is validated in two steps.

The ﬁrst step is the validation at the time of registra-

tion with the endpoint resolver. The second step is the

validation performed by CA at the time of getting de-

vice’s SSL certiﬁcate. In the second step, the device

is validated with common standards (e.g., Extended

Validation) by CA, so certain compatibility will be

ensured in trust of the device.

5.1.3 Dataset

Semantics of the dataset are different on each plat-

form, so it may spoil portability of the dataset across

multiple data spaces. Except for this portability issue,

however, exchange of the dataset itself is possible be-

cause each platform does not limit semantics of an

acceptable dataset to certain one.

5.1.4 Data Catalog

Both platforms adopt the same format as a basis and

restrict an acceptable catalog format. Principal prop-

erties of the catalog are common in both platforms, so

it is interoperable to a certain extent.

5.1.5 Contract

Both platforms recommend concluding the contract

outside of the platform, so trust of the contract is not

scope of assurance by platforms.

5.1.6 Sending & Receiving Log

Only DATA-EX assures trust of the sending and re-

ceiving log by enabling these logs veriﬁable in cen-

tralised management service. Veriﬁable sending and

receiving logs can be also used to proof transferred

path of the dataset across three or more participants

and this may contribute to ensure trust of the dataset.

However, this gap does not disturb data exchange be-

cause use of centralised management service is not

mandatory.

5.2 Inter-Exchangeable Topology

Figure 5 shows the possible inter-exchangeable topol-

ogy between DATA-EX and Catena-X based on our

gap analysis.

Participant’s Entity

Dataset

DATA-EX Connector

Catena-X Connector

Data catalog

Device certificate

Exchange Data with

Participant in JP

Exchange Data with

Participant in EU

Account as DATA-EX Participant

Account as Catena-X Participant

Figure 5: Inter-exchangeable topology between DATA-EX

and Catena-X.

To discuss inter-exchangeable topology, we

judged each gap whether it interferes interoperability

or not. For an object which has the former gap, we

thought that we should use the function or method on

each platform as they are. In our judgement, only the

participant has the former gap, so a connector, which

is a component to verify the participant, and an ac-

count, which acts as a participant’s credential, should

be prepared for both platforms like a dual-stack inter-

face. Fast and economic way to prepare the connector

and account will be desired because there is large bur-

den in preparation against two platforms.

For the rest objects, we thought that we may make

it to be common or omit it. In our judgement, the

dataset, data catalog, and the device certiﬁcate can

be used commonly in both connectors with tiny con-

version. The contract and logs can be omitted be-

cause these are managed outside of data spaces or not

mandatory.

Towards Interoperable Data Spaces: Comparative Analysis of Data Space Implementations Between Japan and Europe

325

5.3 A Challenge on the Participant

Enabling interoperability of the participant trust be-

tween data spaces is a high priority challenge, as the

trust of other objects depends on the participant trust.

Figure 6 shows the current state (left), the ideal state

(center), and a realistic solution (right) in terms of the

participant trust.

On the current state, laws or government guide-

lines about digital trust are different in Japan and Eu-

rope. Especially, there is no comprehensive one like

eIDAS2.0 in Japan. This difference is reﬂected in the

difference of the authentication framework. The au-

thentication framework is used by the operating func-

tions of the data space, so the trust of the registered

participants will be different as a result.

In the ideal state, laws and government policies

are mutually recognised. Mutual recognition of pub-

lic (i.e., governmental) leads to compatibility of the

authentication framework. As a result, the trust of

registered participants will be compatible in some ex-

tent. However, this model is difﬁcult to implement at

an early stage, as it could take a long time establish

mutual recognition. In fact, even electronic authen-

tication and electronic signature, which has been al-

ready used in various systems, is not mutually recog-

nised completely among each country (Tezuka et al.,

2024).

Figure 6 (right) shows our proposal as a realis-

tic solution. We recommend that the mutual recog-

nition of private authentication frameworks should

precede the mutual recognition of public to achieve

early adoption. While this approach needs to contin-

uously adapt to the latest developments in legislation

or government policy, it is advantageous for partici-

pants who wish to communicate to other participants

beyond a country or region.

5.4 A Challenge on the Dataset

Another challenge is the semantics of the dataset be-

yond the single data space. Although the trust of the

dataset depends on largely the participant, as men-

tioned in a previous section, the data space applies

governance to the data models and vocabularies by

providing the repository and pre-deﬁned models. The

repository does not cover a data space in other coun-

tries, and the pre-deﬁned models are not mutually

recognised between countries. This situation makes

it difﬁcult for the participant to trust the dataset in an-

other data space.

To address this problem, we consider two solu-

tions. The ﬁrst solution is to create an international

repository. Although it is an ideal solution, it takes

a long time to proceed mutual recognition between

countries or regions. The second solution is to cre-

ate an index repository to show correspondence of se-

mantics among existing repository in each data space.

It is more realistic than the ﬁrst solution because reg-

istration and maintenance of the index can be led

by the participant. To implement index repository,

some existing semantic technologies such as knowl-

edge graphs (Theissen-Lipp et al., 2023) may be use-

ful. Automation of registration or maintenance using

technologies such as a name identiﬁcation method is

also suitable for this solution. Thus, we believe the

second solution should be proceeded ahead of the ﬁrst

one.

5.5 Possible Policy Alignment

For address two challenges above in an ideal way, pol-

icy alignment and mutual recognition between coun-

tries or regions is essential. There are two approaches

to achieving it. The ﬁrst is standardization. While

the IDSA standardise the data space itself and related

technologies in the data space protocol, Gaia-X stan-

dardise trust required to join the data space ecosystem

in the Gaia-X compliance document (Gaia-X, 2024).

The Gaia-X compliance document deﬁnes trust stan-

dards to be satisﬁed as some levels and laws or reg-

ulations to be followed to be certiﬁed at each level.

Gaia-X itself is a European organization, so approach

to develop trust standards applicable internationally

through international and neutral standardization or-

ganizations is necessary.

The second approach is discussion in the interna-

tional committee. At G7 Hiroshima 2023, the estab-

lishment of the Institutional Arrangement for Partner-

ship (IAP)

was endorsed by G7 leaders to opera-

tionalise DFFT. The IAP can provide opportunities

for discussion utsing existing committees or organs of

international organisations, so discussing challenges

here can be another approach.

6 RELATED WORKS

A basic survey against data space connectors was

carried out (Dam et al., 2023) (Bacco et al., 2024).

A total of eight connectors including EDC used in

Catena-X were surveyed and evaluated, but Japanese

connectors are not included in the surveyed connec-

tors. Moreover, it didn’t discuss the interoperability

issues between connectors, while they explains IDS

RAM (IDSA, 2023) as a common speciﬁcation for

https://www.digital.go.jp/en/policies/dfft/dfft-iap

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326

Current State

Data Space in Japan Data Space in Europe

Ideal State

Data Space in Japan Data Space in Europe

Realistic Solution

Data Space in Japan Data Space in Europe

Participants Participants

cannot trust

Data Space

affect

Data Space

affect

Authentication Framework

used

Authentication Framework

different

used

Laws, Goverment Guidelines

affect

Laws, Goverment Guidelines

different

affect

Participants Participants

can trust

Data Space

affect

Data Space

affect

Authentication Framework

used

Authentication Framework

compatible

used

Laws, Goverment Guidelines

affect

Laws, Goverment Guidelines

mutual

recognition

affect

Participants Participants

can trust

Data Space

affect

Data Space

affect

Authentication Framework

used

Authentication Framework

mutual

recognition

used

Laws, Goverment Guidelines

affect

Laws, Goverment Guidelines

different

affect

Figure 6: States of a challenge on the participant.

data spaces. Our work is to compare European con-

nectors in accordance with IDS RAM and Japanese

connectors not in accordance with IDS RAM and to

consider interoperability among them.

Attempts to create design options for data spaces

by analysis of published papers or interview were

conducted (Gieß et al., 2023) (Gieß et al., 2025). This

paper also conducted a frequency analysis of design

options against existing data spaces. Their design op-

tions include a perspective of trust. They emphasise

the dataset and log as objects to consider trust, how-

ever, many other objects, such as contracts, are gen-

erated in an actual data exchange process. Our work

is to conduct an analysis with comprehensive criteria

covering a whole data exchange process.

Consideration of interoperability between data

spaces was carried out (Schinke and Roßmann, 2024).

They investigated and analysed various technologies

(including the data space) that can be used to increase

data sharing. They proposed six ways to enable trust-

worthy data sharing using the technologies they re-

searched. One of six ways included an architecture

that combines multiple data spaces. They stated that

handling of a dataset for multiple data spaces is a chal-

lenge in this architecture and this challenge should be

solved by data trustee (Schinke et al., 2023) (Steinert

et al., 2024). The data trustee can hide a layer of con-

nectors from the participants by creating intermediary

layer, so the participant does not have to consider in-

teroperability issues. While our work is to discuss

an inter-exchangeable topology without any trust in-

termediary like the data trustee, the data trustee can

be another solution towards achievement of interop-

erability.

Another consideration of interoperability between

data spaces was carried out (Hutterer and Krumay,

2024). They surveyed and analysed the scopes of gov-

ernance in data spaces from published papers. As

a result of the analysis, three types of governance

were identiﬁed: ecosystem governance, technologi-

cal governance, and operational governance. In the

technological governance, the authors argues that the

federated data space architecture (Schleimer et al.,

2023) can achieve interoperability across different

data spaces. The federated data space architecture ex-

presses the architecture to realise global data avail-

ability across multiple data spaces as three logical

layers, local foundation layer, federation layer, and

global presentation layer. This architecture was eval-

uated with a circular economy example, but designs

for each layer were abstract because no actual con-

nectors were described. Our work is to discuss an

inter-exchangeable topology at a more concreate level

by comparing and analysing actual connectors.

An experimental environment (called as Interna-

tional Testbed for Dataspace Technology, or ITDT)

to try interoperability measures was proposed (Mat-

sunaga et al., 2023). The ITDT aims to enable re-

searchers or developers to test connectivity or inter-

operability among connectors which built on different

technological bases. The ITDT can be an adequate

environment for us to implement and test our propos-

als in future, although a DATA-EX connector has not

provided yet in the ITDT.

7 CONCLUSION

In this paper, we analysed DATA-EX and Catena-X as

a representative data space platform in Japan and Eu-

rope from the perspective of trust. In order to make a

fair comparison between two platforms, we decided a

common data exchange process and identiﬁed six ob-

jects that are generated in the decided process and cre-

ated analysis criteria over the identiﬁed objects. Us-

ing the analysis criteria, we analysed two platforms

and identiﬁed gaps on all objects.

Then, we reviewed the identiﬁed gaps and con-

cluded that the trust of participant to be the most

signiﬁcant challenge. Based on the review, we dis-

cussed inter-exchangeable topology between two data

spaces and two challenges. As the ﬁrst challenge, we

Towards Interoperable Data Spaces: Comparative Analysis of Data Space Implementations Between Japan and Europe

327

identiﬁed compatibility of participant trust across data

spaces and a realistic solution to it. As a second chal-

lenge, we stated the semantics of the dataset beyond

single data space and a brief solution of it.

Our study is, naturally, subject to several limita-

tions that must be considered. Because of the anal-

ysis method focusing on trust, our solutions do not

cover all aspect of interoperability but focus on com-

patibility of trust on participating entities and the data

exchanged. Especially, issues like how to assure

compatibility between different connectors is not dis-

cussed. Continuous discussion is needed for it consid-

ering each standardization activities, although multi-

stack topology we proposed can be one solution for a

while.

Ideally, both two challenges we stated should be

addressed by each other’s government and interna-

tional standardisation organisation, but a work of

them takes time to reach consensus. Therefore, in the

perspective of immediacy, we believe that private trust

initiatives are just as important as public initiatives.

We hope this paper contributes to further efforts to-

wards a sustainable and interconnected data economy

in the future.

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