Funded under the Horizon Europe programme (topic HORIZON-CL4-2023-DATA-01-02), this cluster brings together five distinct projects (DS2, CYCLOPS, CEDAR, PLIADES, NOUS). By sharing knowledge, research outcomes, and best practices, these projects are exploring powerful synergies to revolutionize how data is managed, shared, and utilized across Europe.

The Core Mission: Common Areas of Interest

While each project has its own unique focus, the cluster is united by a shared vision. Together, they are tackling the most pressing challenges in the data ecosystem, focusing on:

• Seamless Integration: End-to-end data lifecycle integration and interoperable, secure data sharing
• Standards & Architecture: Developing interoperable architectures
• Human-Centric Tech: Capturing human context and language, and ensuring there is a “human in the loop”
• Trust & Governance: Defining and enforcing data rights and obligations
• Real-World Application: Validating these concepts through cross-sector pilots

Meet the Five Projects Shaping the Cluster

The Data Lifecycle Cluster is driven by five differen initiatives, each bringing a vital piece to the puzzle:

1. CyclOps: Automation for Trustworthy Data Lifecycles CyclOps focuses on accelerating the adoption and production of data, models, and services within data spaces. It achieves this by introducing interoperable and trustworthy automation for lifecycle management, governance, and maintenance across distributed and heterogeneous data sources.

2. DS2: Intersector Dataspace Toolkit (IDT) Taking a simple, modular, and practical approach, DS2 drives data spaces forward with a unique “pick-and-mix” toolkit. This toolkit enables secure, cross-sector data sharing across vital industries like agriculture, energy, transport, and air quality. DS2’s solutions are actively being validated in Romania, Slovenia, and Greece.

3. CEDAR: Data Spaces + Robust AI for Public Governance CEDAR is building solutions that combine Common European Data Spaces with robust AI to foster more transparent public governance. Their work is especially critical in crisis contexts, ensuring transparency and accountability when traditional spending controls might be relaxed.

4. NOUS: Decentralised Cloud-to-Edge Infrastructure Focused on the physical and digital backbone of data sharing, NOUS is a Horizon Europe initiative creating a decentralized, secure cloud-to-edge infrastructure. By connecting IoT, edge devices, supercomputing, and quantum computing, NOUS aims to aggressively strengthen European data sovereignty and global competitiveness.

5. PLIADES: Reference Architectures for Next-Gen Data Spaces PLIADES is advancing the reference architectures and AI-enabled tools required to integrate the data lifecycle seamlessly within and between data spaces. Their work spans a wide array of high-impact use cases, including mobility, health, industry, energy, and the Green Deal.

By breaking down data silos and building interoperable, secure infrastructures, the Data Lifecycle Cluster, is laying the groundwork for a more competitive and technologically sovereign Europe.

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The PLIADES project was recently presented by Atlantis Engineering at two important events in Greece, further strengthening its outreach to industry, research and innovation communities.

On 25 April 2026, PLIADES was showcased at the Automation & Robotics Expo in Athens, a major exhibition bringing together stakeholders from automation, robotics, AI, manufacturing, public infrastructure and the digital economy. The event offered an excellent opportunity to present the project’s vision and connect with professionals and innovators shaping the future of intelligent, data-driven industrial solutions.

PLIADES was also represented at the 13th Technology Forum, held on 20 May 2026 in Thessaloniki. The forum once again brought research and innovation closer to industry, creating a dynamic environment for networking, knowledge exchange and discussions around robotics, AI and data spaces.

Through its participation in these events, PLIADES continued to raise awareness of its objectives and results, engaging with relevant audiences and promoting its contribution to sustainable, intelligent and collaborative maintenance.

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To support this objective, White Research (WR), within the framework of the PLIADES project, organized two interactive reflection workshops focused on the ethical, societal, and human dimensions of AI systems and data spaces that took place online the 22nd and 23^rd April. The sessions brought together project partners  with the aim to explore how emerging AI technologies may affect fundamental rights, human oversight, inclusion, and societal resilience. These sessions are part of the training programme that started with the introductory training “Ethics and Gender Biases in AI”, organized in the project meeting in Prague, May 2025.

From regulation to real-world reflection

The first workshop, “AI and Fundamental Rights”, introduced participants to the logic and structure of the EU AI Act and explored how AI systems can impact rights such as privacy, transparency, non-discrimination, and fair working conditions. Participants were also introduced to the concept of the Fundamental Rights Impact Assessment (FRIA) and its role in identifying and mitigating risks in high-risk AI systems.

Building on this foundation, the second workshop, “Human Oversight, Societal Impact, and Inclusion in AI”, shifted the discussion toward the practical implementation of trustworthy AI. The session focused on meaningful human oversight, societal impacts, diversity and inclusion considerations, and the challenges of ensuring effective human control in increasingly automated environments.

Together, the two workshops formed a complementary training programme designed to help participants move beyond theoretical compliance and engage critically with the real-world implications of AI deployment in data spaces.

A practical and interactive training approach

Both workshops combined short theoretical presentations with collaborative breakout exercises inspired by the PLIADES use cases. Participants worked in groups to identify ethical risks, discuss vulnerable groups affected, assess societal impacts, and propose mitigation measures for AI systems in healthcare, manufacturing, mobility, and robotics contexts.

This interactive format encouraged participants to reflect not only on technical risks, but also on organizational, behavioural, and societal dimensions that are often overlooked in AI development (Miro boards presented below).

Key insights from the discussions

Several common themes emerged across both workshops:

• Privacy remains a central concern: Across all breakout groups and sectors, participants consistently identified privacy and data protection as among the most impacted rights in AI-enabled environments. Concerns included sensitive patient data in healthcare, monitoring and surveillance in workplace settings, and data security within mobility systems.
• Human oversight must be meaningful: It was emphasized that human oversight cannot be reduced to a superficial “human-in-the-loop” checkbox. Effective oversight requires users to understand AI outputs, retain the ability to intervene, and avoid over-reliance on automated recommendations, especially in high-pressure environments.
• Inclusion and diversity are essential: The discussions highlighted the risks of designing AI systems around “average” users while overlooking minority populations or people in vulnerable situations. Participants stressed the importance of diverse datasets, inclusive testing practices, and accessibility considerations, particularly for older adults, people with disabilities, and other underrepresented groups.
• AI Impacts extend beyond technical Systems: Another important insight was that AI systems reshape organizational processes, working conditions, and societal dynamics. In manufacturing contexts, for example, participants discussed concerns related to worker displacement, over-reliance on automation, and the need to foster an “AI safety culture” where employees feel empowered to report malfunctions or concerns.

Towards Human-centric and Trustworthy Data Spaces

The workshops demonstrated the importance of embedding ethical reflection directly into the design, deployment, and governance of AI-enabled data spaces. Rather than treating ethics and fundamental rights as purely compliance-driven exercises, participants were encouraged to approach them as practical tools for building trustworthy, inclusive, and resilient systems.

By facilitating these discussions, PLIADES contributes to strengthening awareness and ethical readiness across sectors that increasingly rely on secure and interoperable data-sharing ecosystems.

Stay tuned for more updates and dissemination activities from the PLIADES project as it continues advancing human-centric and trustworthy European data spaces.

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The analysis explored how users, stakeholders, and organizational processes can unintentionally create vulnerabilities that adversaries exploit.  The objective was to identify human-centric vulnerabilities and define security requirements capable of supporting trustworthy and resilient AI-enabled data space environments.

Research Methodology

The analysis behind T2.6 rests on three complementary research pillars:

1. A comprehensive desk research and framework analysis covering human factors, ergonomics, and security models (including the Swiss-cheese model) across safety-critical sectors;
2. A multi-sector stakeholder mapping of 38 key actors across the healthcare, energy , and mobility sectors to better understand roles, responsibilities, and influence within emerging data spaces.; and
3. A targeted professional survey involving 58 professionals working with data-sharing ecosystems, assessing real-world awareness, preparedness, behaviours, and experiences with data incidents and security risks.

Key Findings: A Readiness Gap

The results reveal a significant readiness gap in today’s data space landscape.

74% Are Data Space Newcomers

Nearly three out of four survey participants reported having little or no previous experience participating in data spaces. This finding highlights the early maturity stage of many data-sharing ecosystems and underscores the need for stronger onboarding and operational guidance.

82% Report a Training Deficit

An overwhelming majority of respondents stated they feel inadequately or only partially prepared to detect and respond to compromised data scenarios. This indicates that while data spaces are evolving rapidly, many professionals still lack the practical preparation required to identify threats, understand protocols, and react effectively to security incidents.

Human-Centric Threats Dominate

The survey identified phishing and social engineering as the most significant threats affecting data spaces. These attacks exploit human behaviour, trust, and decision-making rather than technical weaknesses alone.

The findings reinforce a critical message: cybersecurity in data spaces is not solely a technical challenge, but also a behavioural and organizational one.

Sensitive Data Raises the Stakes

The majority of data processed within these ecosystems was identified as highly sensitive:

• 52% business confidential data
• 43% consumer confidential data

This highlights the importance of strong confidentiality safeguards, transparent governance mechanisms, and trusted access management processes.

Common Incident Causes Across Sectors

Across all examined sectors, the most frequently reported causes of incidents were lack of training and awareness, misunderstanding of operational protocols, and system error or external attacks.

Why This Matters

As data spaces become increasingly interconnected and AI-enabled, security challenges extend beyond infrastructure and software vulnerabilities. Misunderstood procedures, insufficient training, unclear responsibilities, and poor usability can create risks even in technically advanced environments.

The PLIADES findings demonstrate that improving human readiness is essential for building secure, trustworthy, and resilient European data spaces.

Six Human-Factor-Sensitive Security Requirements

1. Based on this analysis, T2.6 defines six security requirements that designed to strengthen trust, accountability, and operational resilience in data spaces:Awareness & Training – Mandatory, role-specific onboarding and adaptive training, with refresher modules triggered by user behaviour, to prevent unintentional compromise.Role Clarity & Access Governance – Strict Role-Based Access Control (RBAC/RRAC) tied to lifecycle responsibilities, ensuring accountability and minimizing internal threats.
2. Protocol Usability & Decision Support – Human-centered interfaces with real-time AI guidance to reduce cognitive load and reliance on personal judgment under pressure.
3. Detection of Human-Centric Anomalies – AI behavioural models trained to identify atypical user interactions, unusual access patterns, and irregular data sharing behaviours.
4. Trust-by-Design – Transparency dashboards and traceable audit trails so stakeholders can track data lineage and access logs, fostering trust and alignment.
5. Incident Response & Resilience – User-specific escalation flows, regular simulation exercises, and audit trails to support effective recovery from human-driven breaches.

Building Resilient Data Spaces Requires a Human-Centric Approach

The PLIADES T2.6 findings underscore a fundamental truth: building resilient data spaces requires addressing not just technical vulnerabilities, but the human behaviours, attitudes, and organizational structures that surround them. By embedding human-centric security principles into AI-enabled ecosystems, PLIADES contributes to the development of more trustworthy, interoperable, and resilient European data spaces across critical sectors.

Stay tuned for more updates from PLIADES as the project continues advancing secure, interoperable and resilient European data spaces.

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Workshop presentations

The presentations from WS56 are available for download below:

• WS56 Data Spaces Beyond the Basics: Toward Operational AI and Robotics – Introduction presentation
  Franziska Kirstein, Blue Ocean Robotics
  [Download PDF]
• Framing Dataspaces beyond Robotics – Why Governed Data Collaboration Matters for Real-World AI and Robotics
  Till Christopher Lech, SINTEF Digital
  [Download PDF]
• PLIADES – AI-Enabled Data Lifecycle Optimisation & Data Spaces Integration
  Dr. Dimitrios Giakoumis, CERTH/ITI
  [Download PDF]
• AI-based Robotics in the RoX Ecosystem
  Dr. Michael Suppa, Roboception GmbH
  [Download PDF]

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Following our previous announcement of the PLIADES workshop at the European Robotics Forum (ERF) 2026, we are pleased to share the confirmed speakers and the detailed programme of the session. The workshop will bring together experts from research, industry and policy to explore the evolving role of Data Spaces in enabling advanced AI and robotics applications across key sectors.

The workshop, titled “Data Spaces Beyond the Basics: Toward Operational AI and Robotics”, will focus on how Data Spaces can support the development, deployment and scaling of AI-driven solutions in domains such as mobility, industry and healthcare.

Building on the discussions initiated during last year’s ERF workshop, this follow-up session will dive deeper into the practical integration of Data Spaces in real-world environments. Participants will gain insights into interoperability mechanisms, emerging standards and the role of trustworthy and resource-efficient AI within distributed data ecosystems. Particular attention will be given to lessons learned from pilot implementations and cross-domain demonstrators.

 

Workshop 56: “Data Spaces Beyond the Basics: Toward Operational AI and Robotics”

25 March 2026
16:00–17:20
Room: Synesvarden

Workshop programme

The session will be opened by Franziska Kirstein (Blue Ocean Robotics) with an introduction to the workshop objectives and the broader context of Data Spaces in robotics innovation.

The keynote presentations will include contributions from leading experts involved in European research and innovation initiatives:

Till Christopher Lech – Senior Research Scientist, SINTEF, Norway

Framing Data Spaces Beyond Robotics: The talk will provide an overarching perspective on data spaces, drawing on examples from sectors beyond robotics. It will highlight how successful data spaces operate in practice, while addressing key challenges and opportunities for their broader adoption.

 

Dr. Dimitrios Giakoumis – ITI, CERTH, Greece

AI-Enabled Data Spaces in PLIADES: The talk will introduce the PLIADES project, highlighting its approach to AI-driven data lifecycle management across federated data spaces. Key technologies and selected use cases will be presented in the context of interoperable, next-generation AI and robotics ecosystems.

Dr. Michael Suppa – CEO, Roboception GmbH, Germany 

AI-based Robotics in the RoX Ecosystem: The talk will introduce the RoX project. Technologies will be elaborated alongside the use cases and put in context of a federated data space ecosystem.

Cem Gülec, – Policy and Programme Officer, DG CONNECT European Commission.

The talk will outline the European Commission’s vision of common data spaces as secure, interoperable ecosystems for sharing and exploiting data across sectors. It will highlight how EU calls position data spaces as a key enabler for AI and robotics innovation.

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Security and interoperability of European data space architectures

The first article, “A Security Analysis of European Data Space Architectures”, published in Data Science and Engineering (Springer), delivers a comprehensive review and comparative analysis of major European data space frameworks, including IDS-RAM, Gaia-X, FIWARE, and IHAN.

The study examines how these architectures address security, privacy, and interoperability, highlighting their strengths, limitations, and common challenges. It provides structured insights into governance models, trust mechanisms, identity management, and usage control, while also proposing recommendations to enhance data sovereignty, cross-platform interoperability, and privacy protection.

This work directly supports PLIADES’ objective to enable trusted, compliant, and interoperable data spaces, contributing valuable scientific foundations for the next generation of European data ecosystems.

Access the paper here

Toward sustainable data collection processes for autonomous vehicles

The second article, “Toward Sustainable Data Collection Processes for Autonomous Vehicles”, published in IEEE Access, focuses on a critical emerging challenge: how to manage the exploding volumes of autonomous vehicle data in a sustainable, efficient, and privacy-compliant way.

The authors propose and validate a scalable, modular data post-processing pipeline that integrates techniques such as deduplication, anonymization, event-based filtering, and compression. The results demonstrate that the approach can reduce storage requirements by over 50%, lower computational overhead, and simplify downstream AI training workflows, without compromising data quality.

This research aligns closely with PLIADES’ vision of AI-enabled data lifecycle optimisation, showing in practice how sustainability principles can be embedded directly into data creation and management pipelines.

Access the paper here

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The publication brings together expert contributions from leading researchers and Horizon Europe initiatives examining how AI can help move food safety and food systems from reactive practices to proactive and predictive risk intelligence. It addresses how AI can strengthen early warning mechanisms, enhance traceability and transparency and support coordinated cross-border responses to emerging food system risks.

The Discussion Paper is structured around three core thematic areas:

• AI Methods and Autonomous Systems, focusing on predictive models and autonomous technologies for real-time risk detection
• Food Safety and Agriculture Applications, highlighting the use of AI in traceability, hazard forecasting and supply chain visibility
• Cross-Disciplinary Science and Technology, addressing interoperability, trustworthy AI and coordinated risk intelligence across sectors

Within this context, PLIADES contributed to the publication by presenting how AI-enabled interoperable data spaces and full data-lifecycle optimisation can support proactive and trustworthy risk intelligence.

Although PLIADES does not target the food sector directly, its architecture and methodologies provide a transferable framework for food system applications. In its contribution, PLIADES highlights how:

• AI-assisted data quality monitoring, semantic alignment and integrity validation can support early risk detection
• interoperable and federated data spaces enable trusted cross-border data sharing without compromising data sovereignty
• explainable and transparent AI mechanisms strengthen trust and accountability in high-stakes decision environments
• governance frameworks and metadata-driven traceability are essential enablers for resilient data ecosystems

The PLIADES vision aligns strongly with the Discussion Paper’s outlook towards 2035, where federated European data spaces supported by trustworthy AI could continuously monitor, analyse and anticipate risks across complex value chains. Applied to food systems, such an approach could enable real-time collaboration between farms, industry, logistics actors and regulators, making resilience an inherent property of future food ecosystems.

PLIADES’ participation in the EFRA Discussion Paper underlines the project’s broader mission to build interoperable, AI-enabled and trustworthy data infrastructures capable of supporting resilience across domains including mobility, healthcare, manufacturing, energy, robotics and Green Deal applications.

The EFRA Discussion Paper “AI for Resilient Food Systems and Risk Intelligence” is available online and includes the PLIADES contribution on pages 16-17:

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