Towards Legal Interoperability in International Data Spaces

Victor Benoiston Jales de Oliveira

1 a

, Patr

ıcio de Alencar Silva

1 b

and Jo

ao Luiz Rabelo Moreira

2 c

Federal Rural University of the Semiarid, Av. Francisco Mota, 572, Costa e Silva, Mossor

o, 59625-900,

Rio Grande do Norte, Brazil

University of Twente, Enschede 7522, Netherlands

Keywords:

Legal Interoperability, International Data Spaces, Ontology, Design Science Research.

Abstract:

The value of data exchange is indubitably a thriving approach, however, it must be conducted in a safe and

sovereign space, avoiding the loss of control, and data misusage. The International Data Spaces (IDS) is sup-

posed to be a trusted environment, in which companies could share sensitive data upholding data sovereignty.

Thus, mitigating the risk of losing industrial secrets and further threats to competition. Along with the men-

tioned two foundations of IDS, its architecture allows a free contract endorsement, on which, companies may

negotiate their policies and governing laws. A service contract should be able to unambiguously represent

all involved policies, leaving no breach for subjectivity. Another important aspect of IDS is to follow the

Findable, Accessible, Interoperable, and Reusable (FAIR) principles. In particular, we focus on the Legal

Interoperability. As one of the proposed interoperability layers (intended by the European Interoperability

Framework), Legal Interoperability is proposed as the capability of companies from different countries (un-

der different governing laws) to cooperate. This paper provides a research agenda and presents prior results

of the proposed methodologies, addressing how to resolve legal interoperability issues before establishing

IDS legal agreements. It takes a Design Science perspective for problem decomposition into speciﬁc issues,

triangulation of research methods, and projection of a solution space.

1 INTRODUCTION

Companies nowadays try to keep the balance between

sharing data among business partners to optimize op-

erations and controlling it for competitiveness and in-

tegrity. This reality leads to a discussion about data

sovereignty - individuals’ and companies’ ability or

power to control who and how one could use their pri-

vate data (Otto, 2019). There have been initiatives to

enforce data sovereignty in the corporate domain. For

instance, an Industrial Data Space has been proposed

as an environment where companies could share sen-

sitive data based on mutual trust assumptions (Otto

et al., 2019). As business ecosystems evolve, shar-

ing corporate data may cross international boundaries,

which motivated the proposition of International Data

Spaces (IDS) – an environment where companies

could share data based on competence legitimized

by certiﬁcations and explicit data usage policies –

as deﬁned by the International Data Spaces Associa-

https://orcid.org/0009-0000-7026-6929

https://orcid.org/0000-0001-6827-1024

https://orcid.org/0000-0002-4547-7000

tion (IDSA)

. The IDS Reference Architecture Model

(RAM) and implementation guidelines proposed by

IDSA are aligned with the European Interoperability

Framework (EIF)

. The EIF proposes the division of

interoperability into six operational layers, the foun-

dational ones (GANCK, 2017), i.e., Legal, Organiza-

tional, Semantical, and Technical interoperability, and

the recently added, i.e., Interoperability Governance

and Integrated public service governance.

As for the scope of our research, we are com-

plying with the foundational layers, responsible for

grounding the IDS RAM

. For instance, in an IDS-

based business ecosystem, a data usage policy formal-

izes technical aspects of data exchange (e.g., data for-

mats, standards, and transformations) (Ganzha et al.,

2017); data brokers may rely on ontologies to de-

scribe, discover, and select data connectors suitable

to the needs of data owners or data users (Firdausy

et al., 2022a), or enterprise architectures may guide

https://internationaldataspaces.org/

https://ec.europa.eu/isa2/eif en/

https://internationaldataspaces.org/offers/

reference-architecture/

232

Jales de Oliveira, V., Silva, P. and Moreira, J.

Towards Legal Interoperability in International Data Spaces.

DOI: 10.5220/0012699600003690

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 26th International Conference on Enterprise Information Systems (ICEIS 2024) - Volume 2, pages 232-239

ISBN: 978-989-758-692-7; ISSN: 2184-4992

the development of processes and services to leverage

Enterprise Interoperability (Firdausy et al., 2022b).

However, little attention has been paid to enforcing or

promoting legal interoperability in IDS. For instance,

the IDSA Dataspace Protocol

speciﬁes schemas and

protocols required from entities to publish data and

negotiate data usage policy agreements. However, it

lacks explicit guidance on enforcing legal restrictions

and compliance in an IDS-based business ecosystem.

Moreover, in a multi-organizational scenario different

legal norms may impact how actors exchange data in

the IDS-based business ecosystem, and data may face

interoperability barriers, such as different schemas,

different protocols, different descriptions, and subjec-

tive representations (Chituc et al., 2009).

This paper provides a research agenda to address

how to promote the legal interoperability necessary

to unambiguously represent contract policies in a

machine-readable way, fostering its automatization.

We adopt Design Science (Wieringa, 2009) as a guid-

ing research methodology to decompose this problem

into minor ones, identify research methods (Sandberg

and Alvesson, 2010) necessary to treat it, and project

a solution space of design artifacts. To accomplish the

Design Science problem investigation phase, we pro-

pose the General Research Question ‘How to achieve

legal interoperability in IDS?’, which is further de-

composed into conceptual, technical, and practical is-

sues. The treatment design phase of the methodol-

ogy shall comprehend the development of a System-

atic Literature Review (SLR), focusing on knowledge

questions, and the development of software artifacts,

among which, is an ontology for legal interoperability

in IDS, and further machine learning model develop-

ment for automatic instantiation and classiﬁcation of

proposed legal aspects. The validation phase of the

design cycle will demand a combination of methods,

including, a case study evaluation, and a focus discus-

sion group.

The rest of the paper is organized according to the

following: Section 2 presents a set of supporting ar-

guments, leading to the motivation of this research.

Section 3 applies the ﬁrst step of Design Science Re-

search, deﬁning the problem, with further decomposi-

tion into minor issues. Furthermore, Section 4 deﬁnes

the study goals and summarizes the chosen method-

ologies to tackle the problems. Section 5 presents

the prior results of the presented methodologies, with

an explanatory approach for each technique, ﬁnally,

a discussion is presented. Lastly, Section 6 encom-

passes the conclusion, analyzing the mentioned re-

sults, and expressing the current status of develop-

https://docs.internationaldataspaces.org/

dataspace-protocol/

ment and integration, with a ﬁnal disclosure point-

ing towards future works and the next steps of the

research agenda.

2 RESEARCH MOTIVATION

Not only responsible for managing, maintaining,

and certifying the IDS initiative, IDSA is also in-

volved in several types of research, as seen in (Otto

et al., 2019)(Otto et al., 2022), and the main ar-

chitecture such as the Reference Architecture Model

(RAM), and Information Model (IM). International

Data Spaces are designed to facilitate data exchange

and data linkage in a trusted, protected, reliable, and

standardized business ecosystem. The two main as-

pects of an IDS are data sovereignty and trust. The

IDS initiative proposes a reference architecture model

for data sovereignty and related aspects, including se-

cure and trusted data exchange in business ecosys-

tems. With numerous data spaces in Europe as well

as in China, the Americas, and beyond, an authentic

international phenomenon, and these spaces must be

trusted to create value from data. Hence, there is a re-

current urge to develop a protocol with international

validity.

Although Catena-X

and European Health Data

Space (Stellmach et al., 2022) are good examples of

large data spaces, there are smaller data spaces that

only exist for fewer days, and with a smaller number

of actors. Similarly, data spaces may be centralized,

based on an organization or government body, or de-

centralized, adhering to a common rulebook but not

bound by a central association. The proposed proto-

col should encompass a minimal viable interoperabil-

ity approach for all the different frameworks, prod-

ucts, or services. Even though IDSA is currently de-

veloping the Dataspace Protocol, the legal aspects is-

sues are addressed by a so-called Task Force Legal

(Gras, 2023). Despite the legal approach being devel-

oped, there is still a lack of protocols and frameworks

to work as a foundation, leading to repetitive and

resource-intensive processes for each data exchange

agreement.

Projects such as the Eclipse Dataspace Compo-

nents

aim at providing frameworks that could act

as a valid reference for third parties, enabling prod-

ucts and services built on top of the framework auto-

matically to implement the Dataspace correctly, thus,

being compatible with others using the same proto-

col. The IDS itself holds two contract samples, which

https://catena-x.net/en/

https://projects.eclipse.org/projects/technology.edc

Towards Legal Interoperability in International Data Spaces

233

represent (based on German law), a data purchase

contract, and a data rent contract. Those contracts

work as an example for companies to provide their

own contracts, referred to as ‘contract freedom’, by

(Duisberg, 2022). However, this lack of standards

leads to time and resource-intensive negotiations, due

to contract subjectiveness and ambiguous interpreta-

tions. Further, (Duisberg, 2022) also states the devel-

opment of the so-called legal test bed

, which would

be able to perform contract negotiation automation.

However, it is still a future work. Finally, (Munoz-

Arcentales et al., 2019) and (Weichhart et al., 2016)

propose as future work the speciﬁcation of a pol-

icy speciﬁcation language, which is theoretically ad-

dressed by IDSA in the Usage Policy Speciﬁcation

but not implemented in the Information Model.

Still, there is no current real application and

validation regarding the legal interoperability layer.

Through this work, we start a road map towards the

development of semi-automated strategies to enhance

the data exchange negotiation among countries.

3 PROBLEM DEFINITION

Design Science is a methodology to treat problems

of practical relevance, which are normally com-

plex (Wieringa, 2014), (vom Brocke et al., 2020).

(Wieringa, 2009) proposes decomposing a main re-

search question into conceptual, technical, and practi-

cal questions for traceability and assessment. Con-

ceptual questions seek knowledge about real-world

phenomena without interfering with or changing their

internal state, whereas technical questions concern

state-of-the-art technology to solve a problem. Fi-

nally, practical questions relate to how a software ar-

tifact could impact stakeholders’ needs. This research

agenda aims to treat the following general question:

General Research Question (GRQ): How to

Achieve Legal Interoperability in IDS?

Assumptions: We follow the guidelines of the

European Interoperability Framework, which sets le-

gal interoperability as a top-level layer of Enterprise

Interoperability, i.e., above the organizational, seman-

tical, and technical layers. Treating Enterprise Inter-

operability issues with a bottom-up approach is possi-

ble in this context (and mostly preferred by current re-

search). Still, we plan to follow a top-down approach,

starting with the legal interoperability layer. Further,

for the scope of this paper, we are addressing the four

fundamental legal layers, once the recently added two

https://legaltestbed.org/en/start/

https://docs.internationaldataspaces.org/

ids-knowledgebase/v/ids-g/UsageControl/Contract

address public integration, which is not supported by

the Reference Architecture Model for now.

Problem Decomposition: The main research

question is divided into three other major questions,

which are explained as follows.

General Conceptual Question (GCQ): What is

legal interoperability in Dataspaces?

Assumptions: Data owners and users in an IDS-

based ecosystem may operate under distinct govern-

ing laws for data sharing in different countries. Al-

though the main goal of the proposed research regards

Legal Interoperability speciﬁcally for IDS, we might

as well examine the current literature in related datas-

paces (once IDS technology is the foundation for dif-

ferent types of dataspaces).

Problem Decomposition: (1) What is the current

representation of service contracts in IDS? (2) How

do legal aspects interfere with Data Sovereignty? (3)

How are the legal norms and usage policies cur-

rently represented in IDS? (4) What are the legal mo-

ments/positions of IDS participants? Is personal-data

management approached in IDS architecture?

General Technical Question(GTQ): How to ef-

fectively enforce Legal Interoperability in IDS?

Assumptions: Resolving legal interoperability is-

sues in an environment such as an IDS-based business

ecosystem will ultimately involve human negotiation,

especially with legal aspects, due to its subjectivity.

By semi-automatic enforcement, we mean to promote

legal interoperability in design time (interoperable by

design).

Problem Decomposition: (1) Which machine-

readable speciﬁcation language could address policy

representation? (2) How to enforce a common under-

standing of contractual bindings (policies)? (3) What

constitutes the workﬂow of data exchange within IDS?

(4) What is the current state-of-the-art regarding con-

tract automation? (5) how could an application help

resolve legal interoperability issues as a prelude to a

contractual agreement?

General Practical Question(GPQ): How does

Proper Legal Interoperability affect IDS-based

ecosystems?

Assumptions: Achieving a contractual agreement

in IDS is a time-consuming and onerous process.

Companies should be able to fulﬁll a proper negotia-

tion and agreement, with a common understanding of

the parties while endorsing data sovereignty and trust.

The IDS architecture provides the possibility of dy-

namization in contract creation, the proposed datas-

pace may foster a mean understanding of the govern-

ing laws, or the instauration of a new one.

Problem Decomposition: (1) How could a semi-

automated approach facilitate the contract/policies

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234

negotiation? (2) What is the common understanding

potential of an ontology? (3) What implementations

could reduce costs and time towards contract nego-

tiation? (4) What is the impact of establishing the

legal availability of participants, to foster the choice

or creation of governing law?

4 STUDY GOALS AND

METHODOLOGY

In Design Science Research (DSR) methodology,

(Wieringa, 2009) deﬁnes the possible goals of re-

search as social context goals (External stakeholders’

goals and Context improvement goals) and the design

science research goals, divided into Artifact Design

Goal: to design or redesign an artifact, Instrument

Design Goal: to design or redesign a research instru-

ment, Knowledge Goal: to answer knowledge ques-

tions, and Prediction Goals: to predict future events.

The present paper encloses the following goals:

Prediction Goal: The prediction goal is not di-

rectly applicable to this research, however, the future

implementation of proposed machine learning models

may reach, at some level, the capability of inferring

predictions.

Knowledge Goal: Identify the ongoing gaps,

challenges, and opportunities in the literature regard-

ing the legal interoperability layer when applied to

IDS. The knowledge goal is directly aligned with the

SLR, answering knowledge (and conceptual) ques-

tions.

Artifact Design Goal: Develop an expandable

and acceptable legal interoperability protocol for data

exchange negotiation among countries grounded by

different data exchange policies, allowing the unam-

biguous representation of policies that compose a ser-

vice contract. As a work in progress, we might move

toward the implementation of the proposed ontology,

in a Retrieval Augmented Generation (RAG) model,

that encompasses the legal interoperability nuances

of IDS and leverages the automation of processes re-

garding contract automation.

Instrument Design Goal: Develop an ontology

following the FAIR data principles (Guizzardi, 2020),

which works as a legal base for further applica-

tion development (ontology-driven development (Pan

et al., 2012)). The ontology should leverage legal

interoperability, therefore unambiguously represent-

ing the legal aspects domain regarding contract for-

mulation, negotiation, and agreement. To do so, we

are grounded by the Systematic Approach to Build

Ontologies (SABiO) methodology, which deﬁnes a

ﬁve-step (i.e., purpose identiﬁcation and requirements

elicitation, ontology capture and formalization, de-

sign, implementation, and testing) iterative guide for

developing ontologies. The ﬁrst and second steps are

responsible for creating a so-called reference ontol-

ogy, which graphically represents the ontology, and

may be designed with languages such as OntoUML

. The design and implementation steps foster the

development of the operational ontology, which is

the most common approach in ontology engineering

(Keet, 2018), ending up with an OWL/RDF opera-

tional ontology. The last phase is summarized as test-

ing, but it also comprises its veriﬁcation, complete-

ness, and validation with stakeholders. Another Im-

portant approach of DSR is the clear eliciting of re-

quirements. Requirements may be addressed as func-

tional requirements and non-functional requirements.

(Su

arez-Figueroa et al., 2009) deﬁnes the Ontology

Requirements Speciﬁcation Document (ORSD), as a

clear statement of why the ontology is being built, for

whom, what the intended uses are, and especially, list-

ing the requirements. As an ongoing work, the latest

version of the proposed ORSD is available on an open

GitHub Repository

, along with the latest version of

the reference ontology. Furthermore, we propose as

future works the development of a machine learning

model that enables the automatic and continuous in-

stantiation of the ontology, and a Natural Language

Processing (NLP) engine able to classify text snippets

into the correct class, based on the ontology.

To answer the proposed RQs and foster the next

step of DSR, i.e., treatment design, which comprises

the speciﬁcation of requirements, possible contribu-

tions to goals, available treatments, and design of

new treatments, we focused on the following re-

search methodologies: Review of literature, which,

according to (Snyder, 2019), is the ability to rely

on existing valid work, being the foundation of all

academic research activity. For this particular re-

search methodology, we proposed a Systematic Lit-

erature Review, which is fairly described in Section

5; Ontology Engineering, in Agreement with (Keet,

2018), plays a critical role regarding the machine-

understandable web, and domain representation. Sev-

eral other methodologies are encompassed, such as

Formal Conceptual Analysis (Stumme, 2002), Pro-

totyping (Luqi and Steigerwald, 1992), Complete-

ness Test (Tambassi, 2021), and others. As for the

last step of DSR (i.e., treatment validation), we pro-

pose the following methodologies: Case Study, de-

ﬁned by (Feagin et al., 2016) as an in-depth, mul-

tifaceted investigation. It allows the resemblance of

https://ontouml.org/

https://github.com/VictorBenoiston/legal

interoperability IDS ontology

Towards Legal Interoperability in International Data Spaces

235

Figure 1: Problem-Solution set of the proposed work (Roadmap).

the theoretical models applied to real-world scenar-

ios; Finally, the Focus Discussion Group method, de-

scribed by (Sutton and Arnold, 2013), is a possible so-

lution for the limited theoretical understanding of pro-

posed technology-driven research. Addressing those

methodologies in the present work, it is possible to

summarize the following methodologies:

Literature Review: A systematic literature re-

view for comprehending the legal aspects, gaps, chal-

lenges, opportunities, and future works encompassed

in Legal Interoperability regarding IDS. The proposed

SLR is based on the (Kitchenham, 2004) guidelines

Furthermore, the retrieved aspects and papers may

be used as a database for future implementation of

machine learning models, and RAGs.

Ontology Engineering: As proposed by

(de Almeida Falbo, 2014), formulate a reference on-

tology, encompassing the domain of the legal aspects

regarding legal interoperability, relying on founda-

tional ontologies such as Uniﬁed Foundational On-

tology (UFO)(Guizzardi et al., 2022), Information

Model (IM) (Bader et al., 2020), and Service Con-

tract Ontology (SCO) (Griffo et al., 2021). The ontol-

ogy should answer open questions spotted on the SLR,

and fulﬁll the requirements established by the stake-

holders, and literature as well. Furthermore, the on-

tology should be enhanced to an operational version

in OWL/RDF, in order to allow further implementa-

tion in applications, and machine learning models.

Case Study: In-depth understanding of the re-

sults, challenges elicitation, and validation in a real-

life application scenario.

Focus Discussion Group: Validate the research

with specialists, point out strengths and weaknesses,

and present future works.

Therefore, we may encapsulate our research

goals, questions, and solutions road map as follows

in Figure 1. Please note that, although we establish

a possible prediction goal, it should be further ad-

dressed as the work proceeds, and it is not addressed

in our proposed road map.

5 PRIOR RESULTS AND

DISCUSSION

To better understand the current challenges, opportu-

nities, gaps, and proposed future work toward legal

interoperability within IDS, and grounded by the ﬁrst

ICEIS 2024 - 26th International Conference on Enterprise Information Systems

236

proposed methodology, we have performed a Sys-

tematic Literature Review, which is available in an

open-access GitHub Repository

. 40 papers have

been reviewed, from ACM Digital Library, EI Com-

pendex, IEEE, ScienceDirect, Scopus, and Springer-

Link databases. Figure 2. showcases the lifecycle

of the proposed SLR. Along with an in-depth dis-

cussion of the legal aspects of IDS, the SLR pre-

sented 10 retrieved legal aspects that foster legal in-

teroperability, i.e., domains of business, personal /

non-personal data, usage and data policies, interoper-

ability constraints, smart contracts/contract automa-

tion, semantic appeal, AI usage in IDS, cloud, IDS

usage in open spaces, and future works addressing

legal aspects. Along with the retrieved legal as-

pects, the literature reviewed acknowledges 12 dis-

tinct kinds of future works, i.e., cloud, governance,

AI, semantics implementation, technology integra-

tion, practical implementation, common understand-

ing, privacy/personal data, modular templates, policy

speciﬁcation language, and automated negotiation.

Figure 2: SLR Lifecycle.

Furthermore, to ground the development of the

proposed ontology, entitled Legal Interoperability

Ontology for International Data Spaces (LegIOn-

IDS), we employed the previously mentioned SABiO

methodology (de Almeida Falbo, 2014). Moreover,

part of the data retrieved by the SLR acted as a foun-

dation for ontology development, especially foster-

ing the ﬁrst and second steps of the SABiO guide-

https://github.com/VictorBenoiston/towards legal

interoperability IDS archive

line (purpose identiﬁcation and requirements elicita-

tion and ontology capture and formalization). The

SLR was able to ground the requirements for devel-

oping the reference ontology. The operational on-

tology was manually instantiated for testing, veriﬁca-

tion, and partial validation, also based on the retrieved

data from the SLR. The complete ontology engineer-

ing encompassing the reference ontology, operational

ontology, and SPARQL queries is available in the pre-

viously mentioned open-access GitHub repository.

For the operational ontology, we employed

the Design and Implementation steps, providing a

machine-readable ontology through the Web Ontol-

ogy Language (OWL). The operational ontology im-

plements concepts such as disjointness, and closing

axioms, and allows the inclusion of instances, foster-

ing the division of the Tbox, and Abox. The former,

provides the taxonomical box, providing the class hi-

erarchy structure, and the latter, provides the assertion

box, delivering the use of instances to provide reason-

ing. The complete documentation of LegIOn-IDS is

available on an open-access website

, with a unique

URL, following the FAIR principles (Wilkinson et al.,

2016), and enforcing the Reuse, we also provide a vo-

cabulary of terms reusing the ISO standards.

Thus far, based on the outcome of the proposed

SLR, we might connect the intended future works

with our road map of development. A few insights

and metrics about the SLR were condensed in this

GitHub Repository

, along with its data. The latest

version of the operational ontology is also available in

the GitHub repository, as mentioned above.

6 CLOSING THOUGHTS

For this paper, we propose a DSR project, relate on-

going work, and state the roadmap toward its con-

clusion. Table 1 summarizes the proposed treatments

(outcomes) of this DSR project, based on referring to

proposed work highlighted by the SLR, and points out

the current level of implementation, i.e., low means a

draft or a ﬁrst version, medium refers to an ongoing

work based either on stakeholders’ requirements or

open issues retrieved from SLR, and high, alludes the

ﬁnal version of the outcome.

Furthermore, as an ongoing work, we are cur-

rently implementing a machine-learning model ca-

pable of classifying text snippets retrieved from ser-

vice contracts. In order to train our model, we de-

veloped a database providing 505 comma-separated

https://legionids.netlify.app/

https://github.com/VictorBenoiston/towards legal

interoperability SLR

Towards Legal Interoperability in International Data Spaces

237

Table 1: Alignment with Recovered Future Works and Current Level of Implementation.

Outcome Proposed Future Works

Level of Im-

plementation

SLR

Semantics Implementation (Reference and Operational),

Common Understanding

High

Reference Ontology

Semantics Implementation (Reference), Common Under-

standing, Modular templates, Policy Speciﬁcation Lan-

guage

Medium

Operational Ontol-

ogy

Semantics Implementation (Operational), Technology

Integration, Common Understanding, Privacy/Personal

Data, Modular Templates, Policy Speciﬁcation Lan-

guage, Automated negotiation

Medium

ML Classiﬁcation

Model

AI, Technology Integration, Modular Templates, Auto-

mated Negotiation

Low

values, collected from the SLR, which implies some

examples of service contracts, and generic contrac-

tual clauses. As the ﬁrst step for providing the com-

plete lifecycle of our proposal to provide a legal in-

teroperability framework for IDS, we employed Nat-

ural Language Processing (NLP), and Object Charac-

ter Recognition (OCR), among other techniques. The

complete lifecycle may be presented twofold, such as

in a bottom-up approach, analyzing existent service

contracts, extracting the text snippets, and employing

the IDS architecture through the LegIOn-IDS taxon-

omy, or top-bottom, on which lawyers or companies’

representatives may manually provide the contractual

clauses, and through the NLP processing, we employ

the IDS architecture through LegIOn-IDS, terminat-

ing the process with a sample contract in natural lan-

guage, which already complies with the IDS archi-

tecture. Moreover, it is possible to predict challenges

and limitations such as using sensitive data to train our

models, along with the recurrent need to collaborate

with real case applications, conditionalizing the out-

come to the proper instantiation of the ontology and

models.

Finally, we establish as future steps, the complete

validation and evaluation of the proposed ontology,

along with the API. To properly address such steps,

we must employ use cases that rely on negotiating ser-

vice contracts between companies under different le-

gal frameworks (legislation). Furthermore, the usage

of AI technologies, such as training machine learn-

ing models to classify text snippets to automatically

instantiate the ontology, integrating with its API us-

ing the Python library OWLReady2

is currently un-

der development. Lastly, we are currently investigat-

ing the usage of the proposed ontology as the foun-

dation for a Retrieval Augmented Generation (RAG)

– which is a model capable of generating knowledge

https://pypi.org/project/owlready2/

based on a retrieve-generate architecture, based on a

knowledge source (Huang et al., 2023). In conclu-

sion, we are actively looking for additional applica-

tions of the proposed ontology, better addressing the

recovered gaps in the literature, and fostering the au-

tomation of processes regarding contractual issues in

IDS.

In conclusion, we are actively looking for addi-

tional applications of the proposed ontology, better

addressing the recovered gaps in the literature, and

fostering the automation of processes regarding con-

tractual issues in IDS.

ACKNOWLEDGEMENTS

The present work was endorsed by CNPq - National

Council for Scientiﬁc and Technological Develop-

ment - Brazil.

REFERENCES

Bader, S., Pullmann, J., Mader, C., Tramp, S., Quix, C.,

uller, A., Aky

urek, H., B

ockmann, M., Imbusch, B.,

Theissen-Lipp, J., Geisler, S., and Lange, C. (2020).

The International Data Spaces Information Model –

An Ontology for Sovereign Exchange of Digital Con-

tent, page 176–192.

Chituc, C.-M., Azevedo, A., and Toscano, C. (2009). A

framework proposal for seamless interoperability in a

collaborative networked environment. Computers in

Industry, 60(5):317–338.

de Almeida Falbo, R. (2014). Sabio: Systematic approach

for building ontologies. Onto. Com/odise@ Fois,

1301.

Duisberg, A. (2022). Legal Aspects of IDS: Data

Sovereignty—What Does It Imply?, page 61–90.

Springer International Publishing, Cham.

ICEIS 2024 - 26th International Conference on Enterprise Information Systems

238

Feagin, J. R., Orum, A. M., and Sjoberg, G. (2016). A case

for the case study. The University of North Carolina

Press.

Firdausy, D. R., de Alencar Silva, P., van Sinderen, M., and

Iacob, M.-E. (2022a). A data connector store for in-

ternational data spaces. Cooperative Information Sys-

tems, page 242–258.

Firdausy, D. R., De Alencar Silva, P., Van Sinderen, M., and

Iacob, M.-E. (2022b). Towards a reference enterprise

architecture to enforce digital sovereignty in interna-

tional data spaces. 2022 IEEE 24th Conference on

Business Informatics (CBI).

GANCK, A. D. (2017). The new european interoperability

framework.

Ganzha, M., Paprzycki, M., Pawłowski, W., Szmeja, P.,

Wasielewska, K., and Moreira, J. (2017). Towards

semantic interoperability between internet of things

platforms. Internet of Things, page 103–127.

Gras, N. (2023). Let’s talk about idsa’s task

force legal. https://internationaldataspaces.org/

lets-talk-about-idsas-task-force-legal.

Griffo, C., Almeida, J. P. A., Guizzardi, G., and Nardi, J. C.

(2021). Service contract modeling in enterprise ar-

chitecture: An ontology-based approach. Information

Systems, 101:101454.

Guizzardi, G. (2020). Ontology, ontologies and the “i” of

fair. Data Intelligence, 2(1-2):181–191.

Guizzardi, G., Botti Benevides, A., Fonseca, C. M., Porello,

D., Almeida, J. P. A., and Prince Sales, T. (2022).

Ufo: Uniﬁed foundational ontology. Applied ontol-

ogy, 17(1):167–210.

Huang, W., Lapata, M., Vougiouklis, P., Papasarantopoulos,

N., and Pan, J. Z. (2023). Retrieval augmented gen-

eration with rich answer encoding. Proc. of IJCNLP-

AACL, 2023.

Keet, C. M. (2018). An introduction to ontology engineer-

ing. University of Cape Town.

Kitchenham, B. (2004). Procedures for performing system-

atic reviews. Keele, UK, Keele Univ., 33.

Luqi, L. and Steigerwald, R. (1992). Rapid software proto-

typing. In Proceedings of the Twenty-Fifth Hawaii In-

ternational Conference on System Sciences, volume ii,

pages 470–479 vol.2.

Munoz-Arcentales, A., L

opez-Pernas, S., Pozo, A., Alonso,

l., Salvach

ua, J., and Huecas, G. (2019). An archi-

tecture for providing data usage and access control in

data sharing ecosystems. Procedia Computer Science,

160:590–597.

Otto, B. (2019). Interview with reinhold achatz on “data

sovereignty and data ecosystems”. Business & Infor-

mation Systems Engineering, 61(5):635–636.

Otto, B., Hompel, M. t., and Wrobel, S. (2019). Interna-

tional Data Spaces, pages 109–128. Springer Berlin

Heidelberg, Berlin, Heidelberg.

Otto, B., Wrobel, S., and Hompel, M. (2022). Designing

data spaces. Springer International Publishing.

Pan, J. Z., Staab, S., Aßmann, U., Ebert, J., and Zhao,

Y. (2012). Ontology-driven software development.

Springer Science & Business Media.

Sandberg, J. and Alvesson, M. (2010). Ways of construct-

ing research questions: Gap-spotting or problematiza-

tion? Organization, 18(1):23–44.

Snyder, H. (2019). Literature review as a research method-

ology: An overview and guidelines. Journal of Busi-

ness Research, 104:333–339.

Stellmach, C., Muzoora, M. R., and Thun, S. (2022). Dig-

italization of health data: Interoperability of the pro-

posed european health data space. Studies in Health

Technology and Informatics.

Stumme, G. (2002). Formal concept analysis on its way

from mathematics to computer science. Conceptual

Structures: Integration and Interfaces, page 2–19.

arez-Figueroa, M., Gomez-Perez, A., and Villazon Ter-

razas, B. (2009). How to Write and Use the Ontology

Requirements Speciﬁcation Document, volume 5871.

Sutton, S. G. and Arnold, V. (2013). Focus group meth-

ods: Using interactive and nominal groups to explore

emerging technology-driven phenomena in account-

ing and information systems. International Journal

of Accounting Information Systems, 14(2):81–88.

Tambassi, T. (2021). Completeness in information systems

ontologies. Axiomathes, 32(S2):215–224.

vom Brocke, J., Hevner, A., and Maedche, A. (2020). In-

troduction to design science research. Progress in IS,

page 1–13.

Weichhart, G., Gu

edria, W., and Naudet, Y. (2016). Sup-

porting interoperability in complex adaptive enter-

prise systems. Data & Knowledge Engineering,

105(C):90–106.

Wieringa, R. (2009). Design science as nested problem

solving. Proceedings of the 4th International Confer-

ence on Design Science Research in Information Sys-

tems and Technology - DESRIST ’09.

Wieringa, R. J. (2014). Design science methodology

for information systems and software engineering.

Springer.

Wilkinson, M. D., Dumontier, M., Aalbersberg, I. J., Apple-

ton, G., Axton, M., Baak, A., Blomberg, N., Boiten,

J.-W., da Silva Santos, L. B., Bourne, P. E., Bouw-

man, J., Brookes, A. J., Clark, T., Crosas, M., Dillo,

I., Dumon, O., Edmunds, S., Evelo, C. T., Finkers,

R., Gonzalez-Beltran, A., Gray, A. J. G., Groth, P.,

Goble, C., Grethe, J. S., Heringa, J., ’t Hoen, P. A. C.,

Hooft, R., Kuhn, T., Kok, R., Kok, J., Lusher, S. J.,

Martone, M. E., Mons, A., Packer, A. L., Persson, B.,

Rocca-Serra, P., Roos, M., van Schaik, R., Sansone,

S.-A., Schultes, E., Sengstag, T., Slater, T., Strawn,

G., Swertz, M. A., Thompson, M., van der Lei, J.,

van Mulligen, E., Velterop, J., Waagmeester, A., Wit-

tenburg, P., Wolstencroft, K., Zhao, J., and Mons,

B. (2016). The fair guiding principles for scientiﬁc

data management and stewardship. Scientiﬁc Data,

3(11):160018.

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