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.

The data sharing strategy involves understanding the challenges and problems that can be solved through the collaboration of different entities sharing their data. The implementation of a data space in Mallorca is based on understanding the available data and identifying the problems that can be solved using them. The use of data through data spaces will contribute to the transformation of destinations into smart tourism destinations. Smart tourism destinations are considered as smart cities in which the tourism industry offers a new layer of complexity in which technologies, digitalization, and intelligence are powered by data. This study analyzes four scenarios in which geo-dashboards are developed: flood exposure of tourist accommodation, land-cover changes, human pressure, and tourist uses in urban areas. The results of applying the geo-dashboards to these different scenarios provide tourists and destination managers with valuable information for decision-making, highlighting the utility of this type of tool, and laying the foundations for a future tourism data space in Mallorca.

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.

Artificial intelligence (AI) and data-driven applications are transforming industry and research across domains. Despite research advances, the management of the AI and data life cycle in organizations remains largely manual and ad hoc. At the same time, data spaces initiatives are emerging, providing new data-sharing opportunities but posing new challenges for organizations seeking to leverage all their potential. Tackling these challenges, this chapter describes the new framework proposed by the CyclOps project, which aims to enable interoperable and trustworthy automatic management, governance, and maintenance of the entire data life cycle for large-scale volumes of data generated in heterogeneous distributed sources. This supports the development and deployment of AI-based applications across both business and research contexts. CyclOps operationalizes the end-to-end data life cycle, placing at its core knowledge graphs, an established semantic formalism to represent data and metadata adhering to the FAIR Principles, while capturing relevant information to improve reproducibility, traceability, and explainability of the AI results. This core layer is complemented with tools for the automation of data management tasks; distributed data processing; AI tools, algorithms, and models; data space interoperability; and a human-centric interface. The chapter presents the key innovative propositions of CyclOps and its underlying technologies and illustrates them through selected use cases that highlight the general applicability of the approach.

This chapter examines the role of tourism data spaces as a transformative tool for enhancing tourists’ experiences in the present digital era. These spaces are presented as federated, secure and interoperable environments that enable ethical data-sharing among tourism stakeholders, such as public institutions, private companies and local communities. The chapter provides a conceptual foundation for understanding how tourism data spaces contribute to enhancing tourists’ experiences while ensuring smart, inclusive and sustainable tourism. The main contribution of the chapter lies in demonstrating how tourism data spaces enhance tourists’ experiences through the integration of heterogeneous data sources as well as real-time data, artificial intelligence solutions, the Internet of Things and collaborative governance. The chapter identifies key domains in which tourism data spaces add value: hyper-personalisation, visitor flow management, unbalanced tourism, crisis prevention and anticipation, inclusive service design and environmental sustainability.