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In the digital economy era, the efficient, secure, and compliant circulation of cross-border data flow has become a key issue for the coordination of global industrial chains and the deepening of regional cooperation. It is a driving force for the high-quality development of the global digital economy. Currently, cross-border data flow is confronted with multiple challenges, including the interweaving of driving forces and contradictions, inadequate adaptation between mechanisms and technologies, and poor connection between compliance requirements and practical implementation. There is an urgent need to formulate systematic solutions from both theoretical and practical perspectives. To this end, this journal has invited five experts from universities and enterprises to organize a roundtable discussion on the complete logical chain of \"the underlying logic, mechanism construction, trend prediction, compliance governance, and scenario-based implementation of cross-border data flow\". The key viewpoints are as follows: 1) Dynamic Mechanism and Governance Logic of Cross-border Data Flow: Cross-border data flow is jointly driven by three major forces: economic interests, technological innovation, and international cooperation. Meanwhile, it faces core contradictions including the trade-off between sovereign security and flow efficiency, fragmentation of rules and institutional coordination, and technological balance and the digital divide. It is necessary to establish a governance philosophy of \"dynamic balance\" and build a multilateral co-governance system through three types of tools-algorithm-based supervision, technology empowerment, and institutional experimentation-to promote the shift from \"fragmented rule-based games\" to \"systematic coordination\". 2) Construction of a Collaborative Mechanism for Cross-border Data Flow: The mechanism for cross-border data flow needs to break through the limitations of a single dimension and form a multi-dimensional collaborative system integrating \"policy, technology, and industry\". At the policy level, regulatory sandbox pilots, standard mutual recognition, and compliance infrastructure sharing are adopted to address regulatory barriers. At the technical level, scenario-specific needs are met based on a maturity gradient, and the integrated innovation of \"technology + management\" is promoted. At the industry level, the self-regulatory role of professional fields such as library and information science (LIS) is leveraged to compensate for the rigidity of policies and build a closed-loop governance structure. 3) Trend Evolution and Risk Resilience of Cross-border Data Flow: In the next 3 to 5 years, cross-border data flow will exhibit characteristics of structural growth and domain differentiation. Smart manufacturing and digital trade will drive growth on a large scale, while smart healthcare and modern agriculture will emerge as core sectors. It is imperative to address bottlenecks in infrastructure upgrading and the impact of \"black swan\" events, establish a risk resilience system from technical, governance and strategic dimensions, and promote service model innovation in LIS as well as advance layout in the agricultural sector. 4) Compliance Governance and China's Path for Cross-border Data Flow: China has established a hierarchical and classified governance framework centered on three fundamental laws, and explored practical paths through institutional innovations such as the negative list system in free trade pilot zones. To tackle challenges including discrepancies in legal compliance requirements, technical barriers, and the complexity of regulatory coordination, it is necessary to strengthen legal synergy and rule mutual recognition, advance infrastructure construction and technological innovation, and improve the compliance service support system, thereby forming a China-specific path that balances security and controllability with high efficiency and convenience. 5) Practice of Cross-border Data Circulation and Credit Product Mutual Recognition: Cross-border data circulation lays a core foundation for the cross-border mutual recognition of credit products, which holds significant strategic value for promoting the facilitation of international trade and supporting the international development of enterprises. Currently, it faces challenges such as data security compliance, standard discrepancies, and high technical costs. To advance the implementation of cross-border mutual recognition of credit products, efforts should be made to improve the legal and regulatory framework and standard system, strengthen the construction of technical infrastructure, deepen international cooperation and mutual recognition mechanisms, and cultivate international credit service institutions.

[Purpose/Significance] The digital characteristic collections of libraries are facing significant challenges in terms of data circulation and value, which greatly limits their potential utility. To address these issues, this study proposes to establish a trusted data space specifically designed for the digital special collections of libraries. The main objective is to reduce the costs related to trust and promote the full utilization of its multi-dimensional value in areas such as cultural heritage protection, academic research, industrial innovation, and social education. By creating a secure and interoperable environment for data sharing, the plan aims to transform the way digital special collections are managed, accessed and utilized, thereby enhancing their contribution to broader social goals. [Method/Process] This study centers on the trusted data space to explore the cross-domain circulation and value release mechanism of digital specials. It aims to build a dedicated and trusted data space for libraries, break down data barriers, and activate multi-dimensional value. The investigation follows a structured approach centered on requirements analysis, framework construction and strategy formulation. This research is based on the concept and technical foundation of the trusted data space, taking into account the unique attributes and sharing requirements of digital special collections. A comprehensive theoretical framework has been developed and centers around three core capability streams: resource interaction, trusted governance, and value co-creation. These flows are supported by a five-layer architecture model: infrastructure, data interaction, data elementization, intelligent services, and value realization. To illustrate the practical application of this framework, typical usage scenarios were analyzed to demonstrate how special collected data can be transformed from raw resources into valuable assets, and the characteristics and key tasks of specific stages were examined in detail. In addition, a multi-faceted implementation strategy has been proposed to address real-world challenges, including stakeholder reluctance, technological heterogeneity, and conflicts in rights management. These strategies emphasize the development of intelligent resources, the integration of multi-modal and heterogeneous technologies, policy incentive mechanisms, and the establishment of a sound data element market. [Results/Conclusions] The trusted data space proposed in this paper provides a systematic and effective solution for the trusted circulation and efficient utilization of cultural data. It transforms digital characteristic collections into open and reusable assets, thereby significantly enhancing the quality and scope of public cultural services. This development is in line with and supports the national strategic goals of building a \"cultural power\" and a \"Digital China\". Looking ahead, future research should prioritize the shift from theoretical conceptualization to practical implementation. This includes integrating technical solutions with actual service workflows and clarifying the unique role of libraries in the broader data ecosystem. To ensure long-term success and influence, key challenges such as sustainable business models and scientific and reasonable evaluation mechanisms must be addressed.

The EU’s Common European Data Space (CEDS) aims to create a single market for data-sharing in Europe, build trust among stakeholders, uphold European values, and benefit society. However, there is the possibility that the values of the EU and the benefits for the common good of European society may get overlooked for the economic benefits of organisations if norms and social values are not considered. We propose that the concept of “data commons” is relevant for defining openness versus enclosure of data in data spaces and is important when considering the balance and trade-off between individual (market) versus collective (societal) benefits from data-sharing within the CEDS. Commons are open-access resources governed by a group, either formally by regulation or informally by local customs. The application of the data commons to the CEDS would promote data-sharing for the “common good.” However, we propose that the data commons approach should be balanced with the market-based approach to CEDS in an inclusive hybrid data governance approach that meets material, price-driven interests, while stimulating collective learning in online networks to form social communities that offer participants a shared identity and social recognition.

Data Spaces appear to offer a solution to data sovereignty concerns in public cloud environments, which are managed by third parties and must therefore be considered potentially untrusted. The IDS Connector, a key component of Data Space architecture, acts as a secure gateway, enforcing data sovereignty by controlling data usage and ensuring that data processing occurs within a trusted and verifiable environment. This study compares the performance of cloud-native data sharing services offered by major cloud providers—Amazon, Microsoft, and Google—with Data Spaces services delivered via two connector implementations: the Dataspace Connector and the Prometheus-X Dataspace Connector. An extensive set of experiments reveals significant differences in the performance of cloud-native managed services, as well as between connector implementations and hosting methods. The results indicate that the differences in the performance of data sharing services are unexpectedly substantial between providers, reaching up to 187%, and that the performance of different connector implementations also varies considerably, with an average difference of 56%. This indicates that the choice of cloud provider and data space Connector implementation has a major impact on the performance of the designed solution.

Smart tourism destinations aim to manage data coming from deployment of ICT solutions for the sake of an actionable decision-making process. However, data management in the tourism domain have some challenges, such as (i) the need of tourism sector for including external, non-tourism data to make the data more meaningful; (ii) the very heterogeneous nature of tourism data by subject matter; as well as (iii) data coming from many levels of granularity (e.g., city, region, or nation). In order to propose how to properly address these challenges, contribution of this paper is twofold. First, opportunities and barriers that held data-driven smart tourism destinations are analyzed by considering the case study of Visit Benidorm, the Destination Management Organization (DMO) of Benidorm, which is the first city certified as smart tourism destination according to the Spanish standards. Secondly, insights are provided that allow to state that data spaces in the tourism sector are required for DMOs to unleashing the potential of data in a smart tourism destination. Los destinos turísticos inteligentes buscan gestionar los datos provenientes del despliegue de soluciones TIC con el fin de facilitar un proceso de toma de decisiones accionable. Sin embargo, la gestión de datos en el ámbito turístico presenta algunos desafíos, tales como: (i) la necesidad del sector turístico de incluir datos externos, no turísticos, para hacer que los datos sean más significativos; (ii) la naturaleza muy heterogénea de los datos turísticos por temática; así como (iii) datos que provienen de muchos niveles de granularidad (por ejemplo, ciudad, región o nación).Con el objetivo de proponer cómo abordar adecuadamente estos desafíos, la contribución de este artículo es doble. En primer lugar, se analizan las oportunidades y barreras que condicionan a los destinos turísticos inteligentes basados en datos, considerando el estudio de caso de Visit Benidorm, la Organización de Gestión del Destino (DMO) de Benidorm, que es la primera ciudad certificada como destino turístico inteligente según los estándares españoles. En segundo lugar, se ofrecen perspectivas que permiten afirmar que los espacios de datos en el sector turístico son necesarios para que las DMOs puedan liberar el potencial de los datos en un destino turístico inteligente.

The proliferation of Internet of Things (IoT) devices and big data has catalyzed the emergence of data markets. Regulatory and technological frameworks such as International Data Spaces (IDS) have been developed to facilitate secure data exchange while integrating security and data sovereignty aspects required by laws and regulations, such as the GDPR and NIS2. Recently, novel attack vectors have taken a toll on many enterprises, causing significant damage despite the deployed security mechanisms. Hence, it is reasonable to assume that the IDS may be just as susceptible. In this paper, we conduct a STRIDE threat analysis on IDS to assess its susceptibility to traditional and emerging cybersecurity threats. Specifically, we evaluate novel threats such as Man-in-the-Middle (MitM) attacks, compromised end-user devices, SIM swapping, and potential backdoors in commonly used open-source software. Our analysis identifies multiple vulnerabilities, particularly at the trust boundary (TB) between users and the IDS system. These include the traditionally troublesome Denial of Service (DoS) attacks, key management weaknesses, and the mentioned novel threats. We discuss the hacking techniques, tools, and associated risks to the IDS framework, followed by targeted mitigation strategies and recommendations. This paper provides a framework for performing a STRIDE-based threat analysis of the IDS. Using the proposed methodology, we identified the most potent threats and suggested solutions, thus contributing to the development of a safer and more resilient data space architecture.

This article delves deeply into the burgeoning field of Tourism Data Spaces (TDS) in Europe, focusing on how technologies like Big Data and IoT are redefining the tourism sector. This technological shift is steering traditional tourist destinations towards smarter, more sustainable models. The study utilizes a multifaceted approach, combining documentary and bibliographical analysis with empirical data from the EU’s DATES project. By employing the Drivers, Pressures, State, Impacts, Responses (DPSIR) model, it provides a nuanced understanding of the dynamics in TDS. The findings underscore TDS’s pivotal role in improving decision-making and personalizing tourism services. The study also acknowledges the growing need for detailed tourism information to enhance travel planning and experience personalization. Furthermore, it highlights the importance of efficient and secure data management in tourism. This comprehensive analysis points to a future where data-driven insights foster more sustainable, tailored travel experiences. Additionally, the research illuminates both the challenges and prospects inherent in implementing TDS, stressing the importance of clear governance, technical standards, and balancing diverse stakeholder interests in the tourism industry. By addressing these challenges, the article posits that TDS can make a significant contribution to the innovation and sustainability of the tourism sector.

This paper addresses the dilemmas of accessibility, comprehensiveness, and ownership related to health data. To resolve these dilemmas, we propose and justify a novel, globally scalable reference architecture for a Personal Health Data Space (PHDS). This architecture leverages decentralized content-addressable storage (DCAS) networks, ensuring that the data subject retains complete control and ownership of their personal health data. In today's globalized world, where people are increasingly mobile for work and leisure, healthcare is transitioning from episodic symptom-based treatment toward continuity of care. The main aims of this are patient engagement, illness prevention, and active and healthy longevity. This shift, along with the secondary use of health data for societal benefit, has intensified the challenges associated with health data accessibility, comprehensiveness, and ownership. The study is structured around four health data use case scenarios from the Estonian National Health Information System (EHIS): primary medical use, medical emergency use, secondary use, and personal use. We analyze these use cases from the perspectives of accessibility, comprehensiveness, and ownership. Additionally, we examine the security, privacy, and interoperability aspects of health data. The proposed architectural solution allows individuals to consolidate all their health data into a unified Personal Health Record (PHR). This data can come from various healthcare institutions, mobile applications, medical devices for home use, and personal health notes. The comprehensive PHR can then be shared with healthcare providers in a semantically interoperable manner, regardless of their location or the information systems they use. Furthermore, individuals maintain the autonomy to share, sell, or donate their anonymous or pseudonymous health data for secondary use with different systems worldwide. The proposed reference architecture aligns with the principles of the European Health Data Space (EHDS) initiative, enhancing health data management by providing a secure, cost-effective, and sustainable solution.

The Philippine Space Agency (PhilSA) implemented the PhilSA Integrated Network for Space Enabled Actions towards Sustainability (PINAS) to establish an active network of institutions and citizen scientists that will work together to utilize space data and information in support of the sustainable development agenda. The project was conceptualized to address the inherent challenge in gathering feedback, disseminating space data and information, and conducting capacity building initiatives in an archipelagic nation. The project will be conducted in three (3) phases, Phase 1: Network Building, Phase 2: Capacity Building, and Phase 3: Build Up and Expansion. This paper highlights the initial activities and preliminary assessment of the PINAS Project. The results of the initial activities illustrate the potential of the project in optimizing data products and its distribution processes, and in strengthening local capacity to use space data and information. This contributes to the development of effective capacity building initiatives and efficient space data optimization and data-sharing workflows in the country.

The definition of a tourism data space (TDS) in the Balearic Islands is a complex process that involves identifying the types of questions to be addressed, including analytical tools, and determining the type of information to be incorporated. This study delves into the functional requirements of a Balearic Islands’ TDS based on the study of scientific research carried out in the field of tourism in the Balearic Islands and drawing comparisons with international scientific research in the field of tourism information. Utilizing a bibliometric analysis of the scientific literature, this study identifies the scientific requirements that should be met for the development of a robust, rigorous, and efficient TDS. The goal is to support excellent scientific research in tourism and facilitate the transfer of research results to the productive sector to maintain and improve the competitiveness of the Balearic Islands as a tourist destination. The results of the analysis provide a structured framework for the construction of the Balearic Islands’ TDS, outlining objectives, methods to be implemented, and information to be considered.