Conceptual Framework and Prospective Analysis of EU Tourism Data Spaces

Abstract

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.

1. Introduction

In the contemporary economic context, the tourism sector emerges as one of the most dynamic and fast-growing areas at the global level [1]. This trend is evidenced by the quantitative increase in tourism flows and the qualitative diversification of the services and experiences offered [2]. Making a substantial contribution to Gross Domestic Product (GDP) and employment in many nations, tourism has solidified its position as a key driver of economic development and a strategic pillar for generating superior financial returns [3]. However, despite these economic advantages, tourism can also have negative effects, threatening the sustainability of tourist destinations by potentially overburdening local infrastructure, causing environmental degradation, and impacting local communities.

Having access to information on tourism is essential to help tourists plan their trips, know what to expect, how to get around, and how to make the most of their experience [4]. Information enables travellers to make informed decisions, resulting in more satisfying and safer travel experiences. Tour operators and related businesses also rely on information to design more attractive products, identify emerging trends, improve their services, and make strategic decisions that positively influence their companies. Tourism data is a single raw piece of tourism-related information. It can be qualitative, an individual’s review of a hotel for example, or quantitative, the number of people visiting an attraction on a specific day [5]. When collected and analysed as a whole, these data provide the basis of the tourism information presented to users. The distinction between information and data is fundamental [6]. While data are singular, unprocessed elements, information results from processing, organising and contextualising said data to give it meaning and utility.

In a digital era where the amount of data generated is massive, proper analysis and processing of tourism data is essential to maintain competitiveness in the sector, develop new business models, drive innovation, support decision-making, and ensure sustainability [7]. The correct interpretation of data holds the key to a deeper comprehension of tourists’ demands and behaviours, facilitating a swift adjustment to their needs and preferences.

Both private companies and public administration have recognised the importance of these data for various functions and purposes. From a private business perspective, tourism data is an invaluable resource providing essential insights to inform strategic decisions. Whether they are hotels, airlines, travel agencies or digital platforms, tourism companies derive immense benefits from understanding their customers’ preferences and behaviours. By leveraging data analytics, companies can identify emerging trends, customise their offerings, personalise services, and ultimately enhance the overall customer experience. In addition, data enables these companies to fine-tune prices and promotions, streamline resource management, and adopt a proactive stance, rather than a reactive one, in the fiercely competitive tourism market. For public administration, tourism data is fundamental to the planning and management of tourism within a region or country. Such data helps authorities monitor tourist inflows, understand their geographical distribution, and analyse tourism’s economic and environmental impact. This information is crucial for designing tourism policies and strategies that foster sustainable growth, ensuring destinations are not overwhelmed, and that the benefits of tourism are distributed equitably. Moreover, public administration can use this data to improve infrastructure, promote lesser-known destinations, and ensure the preservation of natural and cultural resources.

In the context of tourism data, two concepts that have gained prominence in recent years are Big Data and Open Data. Both represent revolutionary approaches and techniques that are transforming how businesses and governments understand and leverage information in the tourism sector. Big Data refers to data sets that are so large, fast, and complex that they require advanced tools and methods for storage, processing, and analysis [8]. Such data can come from various sources, like social networks [9], online bookings, web searches, and sensors, among others. In the realm of tourism, Big Data [10,11], among its various capabilities, enables tourism businesses and authorities to gain intricate insights into travellers’ preferences, behaviours, and trends. Big Data analysis can unveil patterns in emerging destinations, identify seasonal peaks in demand, and track evolving tourist expectations. By harnessing this information, organisations can quickly adapt to market needs and make more informed decisions.

Open Data refers to data that are openly accessible to the public, and can be used, redistributed, or shared by anyone. In the context of tourism, this can manifest as databases containing information on tourist attractions, visitor statistics, hotel ratings, or public transport routes [12,13]. When made available by government agencies or companies, these data foster transparency, innovation and collaboration. Startups, developers and other businesses can use Open Data to create innovative tourism applications, planning tools, or market research. At the same time, it empowers travellers to make more informed decisions and improve their travel experience [8].

In the last decade, with the evolution of the Smart Cities concept, we have witnessed the emergence of Smart Tourism [14]. These destinations, supported by the promise and delivery of rich data, not only make decisions based on greater insights, but also use data-driven indicators to validate their efforts to provide smarter and more sustainable tourism experiences.

In the ongoing evolution of the data-driven economy, the “Data Space” concept is gaining prominence, with the “Tourism Data Space” in particular standing out. The European Union, acknowledging the significance of this dynamism, ratified the European Data Strategy in February 2020 [15], establishing the Data Act as the cornerstone of this initiative. This strategy seeks to catapult Europe into the leadership of the data-driven economy, capitalizing on the immense potential of the growing accumulation of industrial data, all in the interest of strengthening Europe’s economy and social welfare.

A major challenge in the development of such data spaces lies in the sharing of information, highlighting the imperative need to establish clear governance rules, specify technical requirements and ensure a balance between the different actors involved in each data space. Following the definition proposed by the Data Space Support Centre (DSSC) [16], data spaces are presented as frameworks that facilitate the exchange of data within an ecosystem, guaranteeing a secure and reliable exchange, respecting current regulations and promoting equal treatment for all those involved.

Moving in this direction, in February 2022, the European Commission presented a working document on the Data Space, integrating it with the Digital Europe 2021–2027 programme. It is noteworthy to mention that, initially, the tourism sector was not included as one of the central pillars of this programme. However, recognising its importance, it was subsequently included, and is now a key component in the Data Space Work Programme. Following the launch of the European call, in which the DATES [17] and DSFT [18] projects were approved as Coordination and Support actions to lay out the foundations for what will be the Common European Data Space for tourism, in July 2023, the European Commission published a Communication [19]. This Communication was based on the work and activities carried out by both projects, and is titled “Towards a Common European Tourism Data Space: Driving data exchange and innovation across the tourism ecosystem”. It underscores the importance of the European Data Space as a key element to ensure the digitisation, innovation, sustainability and competitiveness of the European tourism industry through data sharing.

Within the rich and varied conceptual framework surrounding tourism data and information, a significant gap emerges in the management and understanding of data within the tourism industry, with a particular focus on the emerging trend of tourism data spaces. In this context, there is a pressing need to delve deeper into understanding how these data spaces will impact tourism and how this new dynamic of data sharing will strengthen the tourism sector’s competitiveness, while simultaneously improving residents’ quality of life in tourism destinations.

The scientific question of this study is how to build a tourism data space that effectively contributes to the sustainability of the smart tourism destinations. Sustainability is understood from its holistic point of view to generate balances between the economic development, the protection and restoration of the environment, and the improvement of the social development of destinations. To ensure the achievement of these balances, access to data coming from different sources becomes a requirement and data-sharing initiatives in the format of data spaces emerge as a potential solution to address the sustainability challenges of the tourism industry, as the overexploitation of the natural resources, the pressure on the territory and the local communities, the unbalances in the economic growth of people and companies, and increases in natural and human risks and hazards, among others.

To address these challenges, in this study, different aspects have been considered: data sharing and data integration from different sources; access to existing open data sources; and tourism impacts and how data can contribute to improve decision-making mechanisms for companies and destinations.

In this context, the central hypothesis of this paper postulates that the effective integration and management of data play a crucial role in the transformation of conventional tourist destinations into smart destinations, positively impacting their sustainability and competitiveness. In this sense, the establishment and consolidation of a Tourism Data Space is presented as a primary resource which, if properly implemented, has the potential to refine decision-making, drive the emergence of innovative business models, and strengthen both the competitiveness and sustainability of destinations and the sector as a whole.

To address this approach, this research focuses on identifying current trends and prevalent interests while discerning between the benefits and challenges of data sharing in the tourism context. A crucial task at hand is to examine and analyse the different initiatives undertaken in the European Union concerning the creation of a Tourism Data Space. This approach will not only provide an understanding of the current state of the art in this field, but also identify the gaps and loopholes that still exist. Based on this knowledge, the proposal is to deploy a diagnostic model based on the DPSIR methodology to assess the issues that need to be considered in deploying a Tourism Data Space.

The DPSIR framework is a tool that was developed by the Organization of Economic Cooperation and Development [20] and the European Environmental Agency [21]. The DPSIR framework usually starts with the driving forces, then passes through to the pressures on the state of the environment and the impacts on the ecosystem and human welfare, thereby leading to societal responses [22].

In the conceptualization of tourism data spaces, we focus on developing a holistic framework that recognizes the interdependence between sustainability, resilience, economic and social justice, and the evolution of economic thought in the context of tourism [23]. We understand that sustainability and resilience in tourism are intertwined and complementary concepts, coexisting and mutually reinforcing. Our analysis centres on the importance of socio-ecological systems and the adaptation of communities to the challenges of tourism. It is essential that the construction of data spaces promotes a transition towards sufficiency, challenging the growth paradigm and focusing on balanced practices mindful of ecological and social limits [24]. Moreover, it is important to incorporate aspects related to justice, ethics, and equity in tourism [25]. Tourism data spaces should encourage the maintenance of a triple balance—economic, social, and ecological [26]—and, in turn, foster the catalytic role of tourism in promoting territorial cohesion and competitiveness. This approach implies the capitalization of resources and the development of less developed or transitional areas [27]. By integrating these perspectives, we aim to establish a conceptual framework that not only addresses the current challenges of tourism, but also proposes innovative and sustainable solutions. Our approach will be interdisciplinary, combining theory and practice, to understand and guide the development of tourism data spaces in a way that is fair, resilient, and sustainable.

2. Literature Review

The acceleration in digitalisation driven by rapid technological developments in of recent years has had a direct impact on the importance of the use of data. The literature extensively analyses the impact of data and technologies on smart tourism destinations from different perspectives. For example, increasing the quality of life of residents and tourists [28], enhancing the tourism experience through personalization by using real-time monitoring and context-awareness due to the convergence of Big Data and the overall tourism experience [29], or the example of how Big Data can be used in specific contexts as a generator of customer-based knowledge to improve decision-making in Swedish mountain tourism destinations [30].

The European Data Strategy [31] approved in February 2020 has the primary goal of “making the EU a leader in a data-driven society”. Within this strategy the concept of Data Spaces emerged as a new initiative to promote the data-sharing economy across different sectors for the first time. Tourism was also included.

The European Commission launched twelve different verticals that were defined by implementing projects in the form of Preparatory Actions. In the field of tourism, there were two Preparatory Actions, called DATES and DSFT. Both projects were required to work together to deliver a unified Blueprint [32].

To ensure interoperability among all verticals, the European Commission also launched an umbrella program called Data Space Support Centre (DSSC). Within this framework, we can find research that can be used to analyse the state of the art, both elaborated by the members of the DSSC:

• Designing Data Spaces: the ecosystem approach to competitive advantage [33], applied to the context of Germany, in which tourism is not mentioned as one of the use cases.
• Data Spaces: design, deployment and future directions, published in the framework of the Big Data Value Association [34].

In these two documents, the technical aspects of Data Spaces are defined, as well as key aspects such as the governance, interoperability, and synergies with other sectors.

The scientific literature regarding data spaces is still in a nascent state. Some efforts are being made to define them and explain their basic principles [33,34,35]. The majority of the published works are contributions to very recent conferences, with a limited number of scientific articles and books. A review of these works enables an analysis of the themes that have seen the most progress:

• Health: Li and Quinn (2024) [36] discuss the European Health Data Space, emphasizing the expansion of the right to data portability. This reflects an approach to improving access to and control of personal electronic health data by individuals. Marelli et al. (2023) [37], Kympouropoulos (2023) [38], and Mateus et al. (2023) [39] discuss the political and public management implications of the European Health Data Space.
• Industry: Alexopoulos et al. (2023) [40] focus on resilient manufacturing value chains, highlighting the importance of reliable data sharing. Farahani and Monsefi (2023) [41] and Bevilacqua et al. (2023) [42] address the application of data spaces in the Industrial Internet of Things and Industry 4.0.
• Environment and climate science: Elia et al. (2023) [43] describe a Data Space for Climate Science within the European Open Science Cloud, emphasizing the need for a transformative approach in data management and analysis. Volz et al. (2023) [44] and Pomp et al. (2023) [45] investigate the use of digital twins and data spaces in resource management and the circular economy.
• Smart cities: Battistoni (2023) [46] addresses how data management and sharing are changing in smart cities, underlining the importance of data coexistence rather than integration. Usmani et al. (2023) [47] and Langer et al. (2023) [48] investigate the integration and analysis of data in sectors such as smart cities and data analytics.
• Military systems: Rettore et al. (2023) [49] propose the concept of Military Data Space, focusing on data fusion to improve decision-making.
• Agriculture: Šestak and Copot (2023) [50] delve into data sharing in agri-food supply chains, highlighting the principles of trust in the Agricultural Data Space.
• Data sovereignty and security: Marino et al. (2023) [51] and Meyer Zum Felde et al. (2023) [52] focus on sovereignty and security in data spaces, dealing with issues such as secure exchange and access control.
• Data governance and regulations: Terzis and Santamaria Echeverria (2023) [53], as well as Ferretti (2022) [54], explore aspects of governance and regulation in data spaces, especially in health and the digital economy.
• Energy, science, and technology: Janev et al. (2021) [55] and Solmaz et al. (2022) [56] focus on applications of data spaces in specific sectors such as energy and technology.

As an initial conclusion drawn from the work carried out in relation to data spaces, significant advantages are identified in their implementation across various areas: interoperability and data management, data sovereignty and security, integration of emerging technologies, privacy and regulatory compliance, and value creation from data, resilience in the value chain, facilitation of research and development, support for informed decision-making.

The analysis of data spaces shows a notable gap in the development of tourist data spaces. This gap represents an opportunity that this study aims to address. The creation of a dedicated data space for tourism could significantly enhance tourism management and the overall tourism experience, offering enhanced personalization, resource optimization, improved customer experience, data-driven decision making, and other additional values.

The development of a tourist data space would also have a significant impact on social, economic, and environmental sustainability. It could enhance inclusion and provide equitable access to tourist services, promoting a more inclusive and diverse tourism; encourage a more balanced economic growth in the tourism sector, distributing benefits more fairly among different regions and communities; contribute to a more responsible and sustainable tourism, involving the efficient management of natural resources and a reduction in tourism’s ecological footprint. It would favour better coordination among different stakeholders in tourism, improving decision-making and the implementation of effective tourism policies.

3. Materials and Methods

Based on the scientific question, the methodological approach for this study is structured into three complementary phases, all aimed at offering improved knowledge and facilitating the deployment of Tourism Data Spaces (Figure 1).

Initially, a thorough documentary and bibliographic analysis is conducted to examine the definitions and characteristics that distinguish a smart destination, highlighting the transcendental role of data both in the decision-making process and in the monitoring and evaluation of tourism activity. After analysing the current panorama and existing data exchange practices, the study delves into analysing the legal framework of tourism data spaces, gathering all regulations and initiatives developed in this field (Phase 1).

Secondly, to enhance the understanding and applicability of a tourism data space, a questionnaire was developed for 209 public–private entities related to tourism information across the European Union to identify key issues in implementing tourism data spaces. The selection of the public–private entities analysed was based on a criterion of representativeness in tourism data management developed within the framework of the DATES project [17]. The data were extracted from the DATES Project data sharing initiative: https://www.tourismdataspace-csa.eu/data-sharing-initiatives/ (accessed on 12 November 2023) [57] (Phase 2). A more extensive description of the survey can be seen in Deliverable D.2.1. of the European DATES project [58].

The questionnaire aims to determine whether current actions being developed align with the definition proposed by the Data Space Support Centre (DSSC), to identify gaps and to understand the tourism data exchange initiatives underway in the EU in more detail. The questionnaire covered several aspects, including the diagnosis of practices and perceptions of data exchange in tourism. Issues such as reasons for sharing data, the type of data they consider a priority, and how they became familiar with data-sharing initiatives, among others, were explored.

The survey was carried out using a web form sent to the selected entities. The survey analysis was conducted using Microsoft Excel v18 with the statistical support of SPSS v18.

Thirdly, based on the conceptual and technological analysis, a Conceptual Framework was constructed and applied to create data spaces using the DPSIR model (Phase 3). Although DPSIR originated in the environmental context, its structure is versatile and can be easily adapted to different contexts [59,60,61] including, in this case, the development of tourism data spaces. The relevance of applying DPSIR in creating tourism data spaces lies in the fact that it provides a holistic view of Data Spaces (DSs). This holistic perspective considers both internal and external factors. Furthermore, it helps in the identification of problems and opportunities by breaking down its various components and highlighting problem areas and opportunities for improvement.

In a DPSIR framework applied to the development of tourism data spaces, the following factors should be described (

Table 1. Factors considered in a DPSIR analysis.

Factors	Description	Examples
1. Drivers:	They refer to the social, economic or technological factors that initiate the demand for tourism data spaces.	E.g., increased demand for tourism information to inform supply planning decisions, sustainable tourism growth and personalised experiences, and a boom in international mobility and experiential tourism.
2. Pressures:	Direct results of the drivers.	E.g., an increase in mobile applications that facilitate hotel/restaurant booking, the development of interactive platforms for the design of personalised itineraries, and an increase in the creation of collaborative databases where tourists share their experiences.
3. Status:	They describe the current condition or state of the data ecosystem.	E.g., increase in mobile phone usage and a growing level of digital literacy in the population; consolidated presence of large online booking platforms; existence of fragmented data networks and lack of standardisation in tourism information.
4. Impact:	Effects or outcomes resulting from pressures on the state.	E.g., cybersecurity breaches, social changes due to the use of smartphones or changes in employment due to automation, overloading of popular tourist destinations due to easy access to information, and the emergence of new business models in the tourism sector due to data analytics.
5. Response:	Actions taken or to be taken to address impacts.	E.g., training programmes on the use of smart devices and reinforcement of cybersecurity measures; implementation of unified standards for the exchange of tourism data; creation of sustainability policies based on data analysis to prevent overtourism.

).

The DPSIR model, applied to the construction of tourist data spaces, involves an intricate process. The pillars and their factors are generated through a combination of data taken from surveys, documentary analysis, and an indepthp review of the scientific literature. Each element of the DPSIR framework—Drivers, Pressures, State, Impact, and Responses—is informed by this multi-source data, offering a comprehensive approach to understanding and managing tourism-related data. This methodology ensures that the tourist data space reflects real-world dynamics and is grounded in both empirical data and theoretical insights.

4. Construction of Tourism Data Spaces: Theoretical and Legal Framework

4.1. From Smart Destinations to Tourism Data Spaces

The concept of *Smart Tourism Destinations* (STD) has represented a revolution in the management and promotion of tourism destinations, driving the integration of information and communication technologies to improve tourism competitiveness and visitor experience. The emergence of the concept of “Smart Tourism Destinations” has its roots in the creation and evolution of “Smart Cities” [62]. Indeed, the notion of “Smart Destinations” began to gain relevance a decade after the popularisation of smart cities, adopting practices and learnings from these optimised urban spaces [63].

An instrumental tool in conceptualising smart cities was the “Smart Cities Wheel”, proposed by Cohen in 2014 [64]. This wheel highlighted six essential dimensions for the smartness of a city, including governance, environment, mobility, economy, people, and quality of life. The multiple interpretations and extensions of these dimensions have been studied and discussed in academia.

In Spain, the shift towards “Smart Tourist Destinations” has been driven by the Spanish Standardization Norm (UNE) 178501 standard [65]. This standard establishes key criteria including governance, accessibility, sustainability, innovation, and technology. This standard recognises that a smart destination goes beyond merely implementing technologies; it is about transforming the territory as a whole, promoting sustainable and efficient management systems that benefit both visitors and residents.

In the field of STD, several initiatives have been launched to capitalise on information technologies to enrich the tourism experience and strengthen destination management. [66]. These initiatives have ranged from implementing smart signage systems and interactive mobile applications to data management platforms and IoT sensors for environmental and visitor flow monitoring [67,68,69].

One of the most significant initiatives has been the incorporation of data analytics to better understand tourism dynamics. The analysis of large volumes of data—or *big data*—allows tourism destinations to identify behavioural patterns [70,71] predict trends [72,73,74] and make evidence-based decisions [75]. Notable examples include the use of geolocation data to analyse tourist mobility [76,77] and leverage social networks to understand visitors’ preferences and sentiments [78,79,80,81,82].

The integration of augmented reality systems and mobile applications [83,84,85,86] has further enriched the tourism experience, by providing contextual information and improving accessibility to tourism services. These technologies enable visitors to interact with their surroundings in innovative ways, thereby increasing the added value of destinations.

Another prominent area has been the development of data communication infrastructures [87], such as open data platforms, which foster transparency and stimulate innovation by providing access to a wide range of tourism datasets [88]. The commitment to open standards and interoperability has been essential for collaboration between different actors and for the creation of customised services [89].

These and other initiatives have laid the foundation on which smart destinations have begun to move towards creating tourism data spaces. Building these spaces involves orchestrating technologies, policies, and practices to ensure the collection, integration, management, and analysis of data in a way that is secure, efficient, and beneficial to all stakeholders. This paradigm shift is grounded in the acknowledgement that the true intelligence of a destination lies not only in the technological infrastructure, but also in the ability to integrate, analyse, and apply data from both public and private sources to inform decision-making.

Tourism data spaces are presented as dynamic ecosystems where information flows and is shared between different actors: public administrations, companies in the tourism sector, and tourists themselves. This symbiosis of data opens new avenues for the personalisation of services, the development of more effective public policies, and the creation of enriching tourism experiences [90,91].

The concept of the tourism data space is framed within the European Data Strategy, and its recent calls defined in the Digital Europe programme. This strategy envisages the definition and development of data spaces in various areas, including tourism. Specifically, twelve areas are defined: “Green Deal, mobility, manufacturing, agriculture, finance, health, skills as well as smart communities, language, cultural heritage, media and tourism”. At the beginning of 2022, preparatory actions aimed at establishing a design and roadmap for the foundation of data spaces in each sector emerged.

4.2. Legal Context of Data Sharing in Tourism and Perspectives

Creating a tourism data space poses particular challenges, especially when considering the legislation and regulations affecting providers of tourism products and services. This complexity arises from the multitude of regulations existing at European, national, and regional–local levels. In addition, it is vital to recognise that the geographical area is a determining factor in the framework of tourism data spaces.

Also important are the issues of user privacy and security and the need for standardisation and governance of tourism data. In this context, collaboration between different actors and interoperability commitment are fundamental to building a robust tourism data framework.

The main rules and regulations in this area are listed in

Table 2. Rules and regulations in the context of developing a tourism data space.

Rules/Regulations
Proposed Data Act 2020/0767 https://digital-strategy.ec.europa.eu/es/policies/data-act https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:52020PC0767 (accessed on 12 November 2023)
Data Governance Act 2022/0868 (B2B, B2C, B2G) https://digital-strategy.ec.europa.eu/es/policies/data-governance-act https://eur-lex.europa.eu/legal-content/ES/TXT/PDF/?uri=CELEX:52020SC0296&from=ES https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A32022R0868 (accessed on 12 November 2023)
Proposed Interoperability Act for Europe 2022/0720 https://eur-lex.europa.eu/legal-content/ES/TXT/HTML/?uri=CELEX%3A52022PC0720 https://eur-lex.europa.eu/legal-content/En/TXT/?uri=CELEX%3A52022PC0720 https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A52022DC0710&qid=1697381191732 (accessed on 12 November 2023)
Artificial Intelligence Act (2021) https://www.europarl.europa.eu/RegData/etudes/BRIE/2021/698792/EPRS_BRI(2021)698792_EN.pdf (accessed on 12 November 2023)
Open Data and Re-use Directive (2019) https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:32019L1024&rid=1 (accessed on 12 November 2023)
Public Sector Information (PSI) Directive (2019) https://digital-strategy.ec.europa.eu/es/policies/public-sector-information-directive (accessed on 12 November 2023) Directive 2003/98/EC
High Value Data Directive C/2022/9562 https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=uriserv:OJ.L_.2023.019.01.0043.01.ENG (accessed on 12 November 2023)
Directive Inspire 2007/108 https://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2007:108:0001:0014:en:PDF (accessed on 12 November 2023)
Data Protection Regulation (GDPR) https://eur-lex.europa.eu/eli/reg/2016/679/2016-05-04 (accessed on 12 November 2023)
Regulation on the free movement of non-personal data (FFD) 2018/1807 https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:32018R1807 (accessed on 12 November 2023)
Cybersecurity Act (CSA) Cyberesilience Act (CSA)
Digital Content and Services Provision Directive 2019/770 https://eur-lex.europa.eu/legal-content/ES/TXT/?uri=CELEX%3A32019L0770 (accessed on 12 November 2023)
EU Regulation on relations between platforms and companies (P2) https://eur-lex.europa.eu/legal-content/ES/TXT/?uri=CELEX%3A32019R1150 (accessed on 12 November 2023)
Digital Services Act (DSA) 2019/770 https://eur-lex.europa.eu/legal-content/ES/TXT/?uri=CELEX%3A32019L0770 (accessed on 12 November 2023)
Digital Markets Act (DMA) 2022/1925 https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A32022R1925 (accessed on 12 November 2023)

.

The European Commission has articulated a robust regulatory framework for data exchange, including the following laws and directives:

• The Data Governance Act, adopted in May 2022, aims to promote data availability, boost intermediaries’ trust, and strengthen data-sharing mechanisms across the EU. Its rules of procedure address the following issues:

  ○

  The reuse of certain categories of protected data held by public sector bodies.

  ○

  Encouragement of the emergence of neutral data intermediaries to facilitate data sharing by connecting data supply and demand.

  ○

  The creation of a harmonised framework to encourage data altruism, whereby individuals and companies give their consent or permission to make the data they generate available—voluntarily and without reward—to be used for purposes of general interest.

  ○

  The establishment of the European Data Innovation Board, an advisory body to assist the Commission in all matters related to the Regulation.

• The Commission adopted the proposed Data Act on 23 February 2022 to ensure a fair distribution of value in the data economy. It establishes new data access and usage rights for Business to Business (B2B), Business to Customer (B2C), and Business to Government (B2G) exchanges, and sets out a framework for efficient data interoperability. The European Interoperability Act, introduced on 18 November 2022, ensures a coherent EU approach to interoperability, allowing public administrations to collaborate on cross-border data transfer.
• The Artificial Intelligence Act, proposed in April 2021, focuses on using AI systems and associated risks, proposing risk-based definitions and classifications. It is relevant for the tourism sector, where AI and generative models, such as ChatGPT, are gaining traction.
• The Open Data Directive, which came into force in July 2019, strengthens the rules on data formats and has led the EC to publish a list of high-value datasets, many of which are relevant to the tourism data space.

In addition, regulations such as the GDPR, the FFD, and the CSA also deal with data protection and flows. Other regulations include the Digital Content Directive, which empowers individuals by introducing contractual rights, and the P2B Regulation, which seeks a transparent and predictable online trading environment. The Digital Services Act, introduced in 2020 and adopted in 2022, clarifies the responsibilities of online businesses and promotes a safe environment for the provision of digital services. The DMA, also introduced in 2020 and adopted in 2022, aims to level the playing field between large and small platforms in the digital market, addressing unfair practices and ensuring competitive markets in the EU.

There is, therefore, a complex regulatory landscape to consider when developing tourism data spaces. Indeed, the multitude of new legislation can be overwhelming for smaller companies. Many new and existing bodies at the EU level, such as the European Data Innovation Board and the European Data Protection Board, give guidance related to data exchange. Some existing or new authorities will monitor EU data laws nationally. Over time, data exchange between different parties will also require specific rules, architectures, standards, etc., to complement legislation.

In the specific context of tourism data, it is also essential to recognise a wide range of regulations and rules that establish the environment for inter-institutional collaboration and citizens’ rights.

Table 3. Regulations in the framework of sharing tourism data.

Code of Conduct on data sharing in tourism https://etc-corporate.org/uploads/2023/03/Code-of-Conduct-on-Data-Sharing-in-Tourism_Final.pdf (accessed on 12 November 2023)

Passenger Rights Directive https://www.europarl.europa.eu/factsheets/en/sheet/48/los-derechos-de-los-pasajeros (accessed on 12 November 2023)

Package Travel Directive 2015/2302 https://eur-lex.europa.eu/legal-content/en/ALL/?uri=CELEX%3A32015L2302 (accessed on 12 November 2023)

Directive on patients’ rights in cross-border healthcare 2011/24/EU https://eur-lex.europa.eu/legal-content/En/TXT/?uri=celex%3A32011L0024 (accessed on 12 November 2023)

Consumer Rights Directive 2011/83/EU https://eur-lex.europa.eu/legal-content/En/TXT/?uri=celex%3A32011L0083 (accessed on 12 November 2023)

Unfair Commercial Practices Directive 2005/29/EU https://eur-lex.europa.eu/legal-content/En/TXT/?uri=celex%3A32005L0029 (accessed on 12 November 2023)

Regulation on fairness in relations between trading platforms 2019/1150/EU https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:32019R1150 (accessed on 12 November 2023)

Ecolabel Directive 66/2010 https://eur-lex.europa.eu/legal-content/EN/ALL/?uri=celex%3A32010R0066 (accessed on 12 November 2023)

outlines the main regulations in this field.

Within this regulatory framework, the Code of Conduct on Data Sharing in Tourism highlights some relevant regulations in this context. These include initiatives concerning access to data in specific areas and how these particularly affect the tourism sector. While European legislation directly influences all European citizens and businesses, it is crucial to understand the European legislative process and the different types of legislation that the EU produces. Being inherently about free movement, tourism requires special consideration at the EU level to mitigate distortions and ensure the sector’s efficiency. Furthermore, it is essential to consider certain key pieces of legislation, such as Passenger Rights, the Package Travel Directive, and the Directive on applying patients’ rights in cross-border healthcare, among others. All these laws and directives have an impact at the EU level and implications at regional and local levels.

The regulatory landscape is not only vast in terms of data sharing, but also exhibits significant depth in the realm of tourism. When considering the Consumer Rights Directive and the Unfair Commercial Practices Directive, we see a concerted effort by the EU to ensure transparency and fairness in business-to-consumer interactions. These laws not only seek to protect consumer rights, but also to establish a level playing field for businesses, ensuring that commercial practices are fair and transparent.

5. Assessment of Current Sharing of Tourism Data

The analysis of 211 surveys conducted on various EU-wide data-sharing initiatives has enabled us to identify the current scenario regarding the production, exchange, and use of tourism data within the EU.

Regarding the frequency of selected initiatives by country (Figure 2), it is important to note that more tourism data-sharing initiatives have been found in countries where tourism plays a more significant role in their economy, such as Spain or Italy (Figure 3).

Spain and Italy clearly standout in terms of initiatives related tothe use of tourism data, underlining the priority that both countries give to the sector. However, when we look at the contribution of tourism to GDP in 2022, although Spain and Italy have significant percentages, they are not at the top. This could indicate that, despite having a high number of initiatives, they do not necessarily translate into an equivalent share of contribution to GDP. For example, although Croatia has fewer initiatives in comparison, it boasts the highest percentage of tourism contribution to GDP, reflecting the efficiency or direct impact of its initiatives on its economy.

Another interesting fact is that Portugal has a relatively smaller number of initiatives than Spain or Italy, but its contribution to GDP through tourism is quite prominent. This suggests that initiatives in Portugal may be having a high economic impact, or the country has a significant natural dependence on tourism. On the other hand, countries like France and Germany, with considerably large economies, show a lower contribution of tourism to GDP in 2022 realtive to their size, despite having a reasonable number of initiatives.

Table 4. Type of organisation and role in the producer/consumer of tourism data (%). Source: [57].

	Type of Organisation
Data Role: Producer/Consumer	Large Company	NGO	Public Administration	SME	Start-Up Company	Other	Grand Total
Both	4.7	16.5	23.6	12.3	1.9	11.8	70.8
Data consumer	1.4	4.7	4.7	2.8	0.5	4.2	18.4
Data producer	0.5	1.9	0.9	0.9	2.8	3.8	10.8
Grand total	6.6	23.1	29.2	16.0	5.2	19.8	100.0

provides an insight into the development of the tourism data space and how various entities are interacting with said data. It is evident that public administration is taking the lead in this space, taking an active role in both the production and consumption of tourism data. This highlights the importance they place on information when designing and implementing tourism-related policies and promoting destinations. On the other hand, NGOs are also demonstrating a remarkable engagement with the tourism data space. Their significant involvement as simultaneous producers and consumers suggests that these organisations are seeing the value of data not only to inform their actions, but also to contribute to the overall tourism data ecosystem. This could be motivated by a desire to advocate for more sustainable and responsible tourism.

In the corporate sector, large companies seem to be more focused on consuming data than producing it. This could be due to their reliance on established data sources, or a strategy focused on data application rather than data generation. In contrast, start-ups show a balanced interest in data production and consumption, indicating that these young companies are identifying opportunities to innovate in the tourism space through data.

The “Other” category is also intriguing, as their participation in dual roles suggests that there are many uncategorised entities that are actively contributing to the development of the tourism data space. This could be an area of interest for future research to better understand who these actors are and how they are impacting the sector.

Table 5. Functions of organisations and their role in the use of tourism data (%). Source: [57].

Function of Organisation	Data Consumer	Data Producer	Both	Grand Total
Business development	1.4	0.9	6.6	9.0
Data analytics	3.3	1.4	15.6	20.3
General management	4.7	4.7	16.0	25.5
Marketing	0.9	1.4	3.3	5.7
Operations	0.5	0.5	6.6	7.5
Other	6.6	1.9	18.4	26.9
Public relations	0.9	0.0	3.8	4.7
Purchasing	0.0	0.0	0.5	0.5
Grand total	18.4	10.8	70.8	100.0

provides a comprehensive overview of how different organisational functions interact with tourism data regarding consumption, production and a combined role. Drawing connections to the preceding table allows us to discern intriguing correlations and patterns.

The “Data Analytics” function stands out for its prominence in using tourism data, which is consistent, given that it is their primary function to analyse and derive value from data. They are active data consumers and contribute significantly as producers and play dual roles. This suggests that data analytics organisations actively collaborate in the tourism space and play a crucial role in its evolution. Although universities and research institutions were not included in the survey, data spaces can become an important tool to enrich the research in different fields with these institutions being data consumers and producers.

General management also shows a significant share in all categories. This is logical, as general management often makes data-driven decisions and may also be responsible for data production in larger organisations. In the table above, public administration and NGOs, which may have strong general management components, showed active roles in data production and consumption, which aligns with these findings.

It is interesting to note that business development and operations are also actively participating in dual roles, indicating that these functions see value in tourism information both to inform their strategies and to share their findings with the wider ecosystem.

On the other hand, “Marketing” and “Public relations” show less involvement as producers, which might suggest that these functions are more focused on applying existing data in their strategies rather than generating new datasets.

The “Other” category, which encompasses a variety of unspecified functions, has a considerable share in all categories, similar to the table above. This suggests that organisations have diverse entities and functions that find value in tourism data and actively contribute to the space.

Figure 4 presents a percentage distribution of the need for data exchange in the tourism sector. The key question is: “For which of the following purposes is data exchange most needed in the tourism sector?”

The purpose with the highest percentage, at 27.4%, is “Improving planning and operations of tourism services”. This indicates that many respondents consider data exchange essential to optimise planning and operations in the sector. In second place, with 25.9%, is “Conducting market analysis and informing decision making”. This highlights the importance of having accurate data to analyse market trends and make informed decisions in tourism. The purpose of “Improving tourist interaction and engagement” received 23.1%. This suggests that data sharing is also valuable for improving tourist experience and engagement. On the other hand, “Increasing sustainability and accessibility of the destination” received 21.7%, reflecting a growing concern for making tourism destinations more sustainable and accessible. The “Other” category had a minimal percentage of 1.9%, while the “blank” option recorded no responses, with 0.0%. This shows that the majority of respondents identified with the options provided.

The results confirm the importance of data sharing in different areas of the tourism sector. It is evident that the respondents consider the use of data essential in various aspects of tourism, from planning and operations of tourism services to market analysis. The close proximity in percentages across different categories indicates that no single area is dominant, but that all are seen as important. It is interesting to note that tourist engagement and destination sustainability are also considered relevant, which could reflect current trends in the tourism industry towards a more customer-centred experience and greater environmental awareness. The low response in the “Other” category suggests that the options provided adequately covered respondents’ main concerns regarding data sharing in the sector.

The importance of data typology in the survey shows a diverse distribution of combinations involving four types of data: “Device data”, “Other data”, “Transaction data”, and “User-generated data”. Of these combinations, some are particularly predominant. For example, the combination of “Transaction data; Device data; User-generated data; Other data” accounts for 16.0% of the total, while “Transaction data; User-generated data; Device data; Other data” comprises 17.0%. This indicates that combinations, including transaction data and user-generated data, especially when combined with device data, are particularly common, accounting for 33% of the total.

Combinations involving “User-generated data” have a significant presence, with this category appearing in combinations representing 16.5%. This reiterates the idea that user-generated information is a key component in many datasets.

Figure 5 provides a clear picture of the hierarchy of preferences of tourists in relation to the information they seek when planning or enjoying their trips. This perspective is essential for any entity wishing to establish a tourism data space, as it reflects visitors’ current priorities and needs.

Local Gastronomy, with 12%, tops the list, underscoring the paramount importance of food and culinary culture in the tourism experience. Tourists seek not only to be fed, but also to immerse themselves in the local culture through its flavours and culinary traditions. Historic Places, with 11%, followed closely behind. This clearly indicates that tourists value the history and culture of the places they visit. They are interested in learning about the past, ancient civilisations, and the events that shaped the region. Tourist Routes and Recreational Activities, both at 10%, reflect tourists’ need for clear guidance on what to do and how to maximise their experience in a location. They are looking for reliable recommendations that will allow them to explore in the most efficient and rewarding way possible.

Accommodation and Transport, at 9% and 8%, respectively, are key aspects of any trip. Tourists need up-to-date and reliable information on where to stay and how to get around, reinforcing the idea that logistics remain a major concern. Although further down the list at 7% and 6%, Cultural Events and Special Offers are still essential. These percentages demonstrate that tourists are looking for unique experiences and value-added opportunities.

Table 6. Sources and types of data involved in the construction of a tourism data space. Source: survey analysis. Source: [57].

User-Generated Data	Transactional Data	Data by Device
Direct Data Sources Surveys and Direct Collections Community-collected information on the accessibility of tourist sites -Social Media Platforms Instagram Photos, Facebook Comments, TripAdvisor Reviews, Experiences listed on Get Your Guide Social media reviews Customer posts and reviews on social media Text on social networks (feelings, evaluations), photos, and videos Social media Website and Platform Specific Information Photo and video bank Visitor reviews and opinions on booking portals, social networks, etc. Tourist Information Number of tourists per year and location Identity, payment, preferences Information Formats Textual information and photos/videos Textual information (online reviews, posts, comments on social media, etc.) Textual information and photos/videos.	Reservations and Capacity Reservation details, capacity and number of nights. Search and bookings on platforms such as Booking.com, TripAdvisor and other hotel engines. Commercial Transactions and Payments Business operational data. Credit card transactions: payments in shops, online bookings and purchases. Sales trends and analysis, including flight bookings. Marketing and Advertising Data Data related to campaigns, websites, social media, and marketing analytics. Government and Financial Sector Data Information provided by governments, banking and telecommunications sectors. Tourism Industry Metrics and Ratios Metrics include hotel occupancy, revenue, rooms sold, average price, and RevPar, among others. Platforms and Analysis Tools Tools and platforms such as ISTAT, SIAE, optimizadata.com, Biontrend and social media analytics	Location Data GPS, Mobile Roaming, Movement tracking (including weather and Wi-Fi). Device Data IoT devices, Bluetooth mobile phones, Personal mobile phones. Interaction and Behavioural Data Engagement in digital campaigns and websites, number of visitors, language, interactions, likes and subscriptions. Environmental and Sensor Information Weather data, vehicle traffic, traffic flow, environmental data, and visitor counts in car parks. Timely and Event Information Points of interest such as hotels, restaurants, and tours. Commercial and Consumer Data Types of tourists, mobility, behaviour, use of water and fuel, amount of litter in public.

provides a detailed overview of the different sources and types of data involved in tourism. User-generated data, such as opinions and photos on social media, reflect visitors’ direct perception and experience and are a vital tool for identifying current trends and feeding back into the tourism offer.

Transactional data, such as bookings and commercial transactions, provide an accurate picture of tourism demand and consumption patterns. This data is essential for the operational management of tourism organisations and for understanding tourists’ preferences and behaviours. On the other hand, device-based data, including location information and device data, offer granular insights into tourists’ movements and behaviours in real-time. This data is crucial for urban planning and resource management, and for providing personalised services to visitors.

Other types of data, such as government data, industry metrics, and environmental data, also provide a macro context that enriches the overall understanding of the tourism sector. Combining all these data types, if properly analysed and used, can optimise the tourism sector, benefiting both service providers and tourists.

Table 7. Emerging areas of the tourism sector. Source: [57].

Theme	Subtheme	Description
Ecotourism and Sustainability	Ecological Accommodation Spend	Expenditure on green hotels and eco-friendly lodgings
	Eco-friendly Activity Spend	Spending on environmentally friendly tourist activities
	Tourist Carbon Footprint	Estimated CO2 emissions from tourists
Preferences of tourists and Behaviour	Vegan Dietary Preferences	Tourist preferences for vegan dining options
	Night-time Tour Activities	Popularity of night-time tour activities
	Digital Museum Visits	Count of online museum and exhibit visits
	Adventure Sport Interest	Interest in high-risk or adventure sports while touring
	Underwater Tourism Data	Interest in and visits to underwater attractions
	Elderly Specific Activities	Tourist activities preferred by the elderly
	Space Tourism Interest	Interest in space-related tourist activities
	Solo Female Traveller Data	Insights on Solo Female Travellers
	Culinary Tourism Data	Interest in culinary experiences during travel
	Youth Hostel Bookings	Number of bookings in youth hostels
	Silent Retreats Data	Interest in retreats focusing on silence and meditation
Adventure and Sports Tourism	Adventure Sport Interest	Interest in high-risk or adventure sports while touring
	Cycling Tourism Trends	Popularity of cycling during tourist trips
Cultural and Educational Tourism	Cultural Exchange Programs	Participation in local cultural exchange programs
	Digital Museum Visits	Count of online museum and exhibit visits
Inclusive Tourism	Inclusive Tourism for Disabilities	Data on tourism provisions for the differently abled
	LGBTQ+ Friendly Places	Places popular among LGBTQ+ tourists
Health and Wellness	Wellness and Spa Retreats	Popularity of wellness-focused retreats
	Silent Retreats Data	Interest in retreats focusing on silence and meditation
Specific Themes	Disaster-affected Tourism	Visits to areas affected by natural disasters
	Space Tourism Interest	Interest in space-related tourist activities

provides a comprehensive overview of emerging but not fully established areas within the tourism sector. These data types resonate with current inclinations towards sustainability, inclusivity, and personalisation of tourism experiences.

On the one hand, there is a discernible rise in environmental and sustainable awareness among tourists. Indicators such as spending on green accommodation, environmentally friendly activities, and the economic impact of ecotourism underline the importance of sustainability in the sector. Furthermore, including data on dietary preferences, particularly for vegans, indicates an effort to cater to specific niche travellers with different needs and values. The repeated visits to the same destination and the underlying reasons highlight a focus on customer retention and a keen understanding of what really captivates tourists.

Conversely, the emphasis on night-time excursions and activities shows an interest in expanding tourism options beyond conventional daytime activities. Discovering the areas of cities that are commonly visited at night and identifying the highest rated night-time experiences can pave the way for creating attractions that meet this demand.

The prevailing themes underline the need for a better and more nuanced understanding of modern travellers’ preferences and behaviours, which could serve as a guide for the tourism sector to adapt to contemporary expectations and values.

Once the conceptual bases of data spaces have been defined and analysed the information flows of producers and consumers of tourism information , in the following section, we will propose developing a conceptual framework to support the deployment of tourism data spaces using the DPSIR methodology.

6. DPSIR Conceptual Framework in the Creation of Tourism Data Spaces

The Drivers, Pressures, State, Impacts, Responses (DPSIR) model is a widely used conceptual structure in environmental management [61,93,94], but we believe it adapts satisfactorily to the conceptualisation of tourism data spaces. To establish a tourism data space using the DPSIR model, it is essential to first identify the levers that drive the need for such a space, acknowledge the direct pressures that stem from those drivers, assess the current state of tourism data and systems, consider the potential positive and negative impacts of these pressures, and ultimately propose appropriate responses to optimise benefits and mitigate challenges.

6.1. Drivers

The development of a tourism data space is driven by multiple key factors reflecting changing industry dynamics and consumer expectations. Firstly, increasing market demands and expectations for personalised experiences indicates the need for digitisation and accurate data to deliver tailored and detailed services. Strategically, data-driven decision-making, coupled with crisis monitoring and innovation, underlines the importance of a robust data space. Technological advancements, especially cross-platform integration, and geo-technologies such as GIS and geo-localised applications, are reshaping how tourism businesses interact with customers and oversee their operations. Furthermore, fostering cross-departmental collaboration and data sharing are essential to standardise information and uphold customer trust. Figure 6 includes a list of the main drivers under consideration, which are elaborated upon below:

• Innovation and market trends: This cluster comprises the drivers associated with the need to keep up with emerging market trends and constant innovation in products and services. The competitiveness of a tourism destination can be a strong driver for investment in data technologies and the pursuit of differentiation through innovation [95,96].
• Technological advancements: technological advances are a powerful driver for developing a tourism data space, facilitating the digitisation of services and creating new opportunities to enhance the tourism experience [97].
• Economic development: economic factors act as drivers by promoting investment in infrastructure and highlighting the role of tourism as an important economic engine and employment generator, stimulating the development of robust data spaces to support this sector [98,99].
• Policy and regulation: policy and regulation can act as a driver by establishing a framework that encourages tourism while ensuring data protection and privacy by providing a regulated and secure environment for exchanging tourism information [100,101].
• Social and cultural influence: social and cultural factors include changing consumer preferences, which demand richer and more personalised experiences, and increased awareness of corporate social responsibility, driving the adoption of sustainable and ethical practices in tourism [102,103,104].
• Environmental sustainability: environmental sustainability has become an important driver for the tourism sector, promoting conservation and sustainable tourism. The creation of data spaces can support these initiatives by providing key information for decision-making and environmental impact monitoring [105,106,107].
• Data-driven decision-making: data-driven decision-making is a crucial factor driving the development of tourism data spaces. The ability to analyse large volumes of data and extract valuable information enables organisations to make informed and strategic decisions [108,109,110].
• Stakeholder engagement and collaboration: stakeholder engagement and collaboration, including cross-sectoral collaboration and community participation, are essential drivers for sharing and improving tourism data, as well as forming strategic partnerships that benefit all stakeholders [111,112,113].

6.2. Pressures

The construction of a tourism data space encounters several pressures within the framework of the DPSIR model. The expansion of the tourism industry leads to data saturation, which, combined with the heterogeneity of its sources, poses challenges in the integration and analysis of information. Concerns about data privacy, security, and regulatory changes underline the need for ethical and secure handling of consumer personal information. In addition, technical limitations, the costs associated with advanced infrastructures and the need for training and capacity building constitute significant barriers, especially for SMEs. While larger companies may monopolise certain data sets, smaller organisations could be left trailing in the digital race. This dynamic, coupled with rapid technological evolution and shifts in consumer and market expectations, underscores the importance of adaptability, training and consistent data management to remain relevant and effective in the tourism sector. Figure 7 shows the main pressures to consider in constructing a tourist site.

Factors relating to pressures on the creation of a tourism data space:

• Data quality: This set of pressures relates to the need to maintain a high standard of data quality. Accurate and reliable data in tourism is critical for planning, marketing and personalising the customer experience. Data saturation and information accuracy can be significant challenges, especially when handling large volumes of data from various sources [114,115].
• Technical challenges: These challenges focus on the technical aspects of data management. Interoperability of systems is a major challenge, as different platforms and tools must work together to share and process data. Technical issues can affect the efficiency, scalability, and security of tourism data [116,117].
• Regulatory and ethical: Regulations and ethics are crucial in managing tourism data. Regulation changes, such as data protection laws (GDPR in Europe, for example), may restrict how data is collected, stored, and used. In addition, there are ethical concerns related to the privacy of tourist data and the responsible use of information [118,119].
• Economic and market: Market dynamics and associated costs are significant pressures. The tourism market is highly competitive and subject to rapid economic fluctuations. Businesses must balance the costs of data technology and infrastructure with the need to maintain competitive prices and generate profits [120,121].
• Social and cultural: Consumer expectations and organisational culture changes can pressure tourism data management. Tourists increasingly demand personalised experiences and fast and efficient services, which require smart use of data. In addition, companies must adapt their approach to respect diverse cultures and social behaviours [122,123].
• Technology adaptation: Major challenges include adopting new technologies and closing the digital maturity gap. The tourism sector must keep up with the latest digital technologies to improve customer experience and optimise internal operations, which can be difficult for organisations with limited digital skills or technology infrastructure [97,124].
• Security and privacy: Data privacy protection and security risks are a major concern. Data security incidents can damage the reputation of tourism businesses and diminish consumer confidence. Businesses should implement robust security measures and ensure personal data privacy is handled appropriately [125,126].
• Environmental: The environmental impact of tourism activities and sustainability are increasingly important issues. Data can help to monitor and manage environmental impact. However, there are also pressures to ensure that the data practices are sustainable and do not negatively affect the environment [127,128].
• Human factor: Training and skills development needs are key in the digital age. There is a constant need to train staff in new technologies and data handling practices, which can be challenging due to resistance to change or lack of resources for ongoing training [129,130,131].
• Socioeconomic: Socioeconomic fluctuations can have a direct impact on tourism. Political stability, economics trends and demographic changes influence travel patterns and tourism data, requiring businesses to be agile and adaptable to these changing conditions [132,133,134,135].

6.3. State

The assessment of the state in a DPSIR model for constructing a tourism data space focuses on several critical dimensions. Current data quality, accuracy and geographic coverage are fundamental to ensuring relevant and up-to-date information. The level of technology integration and underlying infrastructure determine how effectively this data can be shared and analysed. The adoption of advanced technologies, such as AI and blockchain, reflects the modernity of the sector. It is crucial to take into account public perception and the involvement of different stakeholders, from the private to the government sector, ensuring that privacy, security, and ethical concerns are addressed. The training and capacity of data management professionals, financial investment, and commitment to sustainability and ethics demonstrate the level of preparedness and responsibility of the sector. Finally, resilience, equity, inclusion and return on investment underline the data space’s robustness, fairness and effectiveness in responding to the changing needs and challenges of the tourism environment. Figure 8 shows the main factors defining the state of the tourism ecosystem implementing a data space.

The factors related to the state for the construction of a tourism data space can be grouped into several categories based on their characteristics and their impact on the sector:

• Data quality and standards: This group focuses on the substance of the data. Accuracy, timeliness, and diversity of data sources are critical to ensure the reliability of the tourism data space. Standards and protocols ensure consistency and quality across different platforms and actors [11,136].
• Technological infrastructure and integration: Technology is the foundation that enables the operation of a data space. The integration of systems and the adoption of advanced technologies are crucial for efficient management and interoperability both locally and internationally [137].
• Engagement and capacity building: Active participation of different stakeholders and government commitment are key to the success of the data space. Training and creating a robust data culture facilitate adapting and effectively using the tourism data space [138,139].
• Policy and regulation: Regulations define the framework within which data can be shared and used, while security, privacy and ethics policies ensure that data is handled responsibly and securely [140].
• Sustainability and innovation: Continuous innovation and sustainable development are fundamental to maintaining the relevance and accountability of the data space. This group also considers the environmental impact of the technological infrastructure used.
• Accessibility and utilization: Accessibility and usability of data are essential for the tourism data space to be effective. Extensive geographic coverage and constant feedback promote improving and updating the data space [141].
• Economic and social impact: This group focuses on the economic and social effects of the data space, including public perception and inclusion. The return on investment is a key indicator of the success and justification of the financial investments made [142,143].
• Security and resilience: Security and resilience are vital to protect the data space against threats and ensure its long-term sustainability, allowing the system to adapt and recover from challenges and adversity [144,145].

6.4. Impact Factors

Constructing a data space under the DPSIR framework presents several impact factors. First, data quality may be compromised due to saturation, leading to the inclusion of repetitive or irrelevant data. This saturation of privacy concerns and security challenges can diminish users’ trust. Moreover, the heterogeneity of data sources and uneven digital maturity pose challenges in data integration and equitable geographic representation. Regulatory changes, technical limitations, and interoperability challenges may constrain accessibility, hinder innovation and complicate international cooperation. These challenges also exert pressure on technological infrastructure and financial resources, requiring constant investment and adaptation. On the other hand, changing market dynamics and consumer expectations influence public perception and data-driven business models. Finally, ethical and responsible management becomes crucial to address potential unethical uses of data, and organisational culture faces challenges in adapting and effectively embracing the new data space. Figure 9 shows the main impact factors under consideration.

These are the impact factors considered:

• Data quality and integrity impacts: Data integrity is fundamental to the utility of the data space. Saturation, complexity, and geographic inconsistencies can undermine accuracy and utility, which can have environmental impacts through the misdirection of resources in sustainable tourism strategies, social impacts by not reflecting or misinterpreting the needs of local communities, and negative economic impacts in decision-making based on poor data [141].
• User trust and engagement: User trust and engagement are vital to the success of the data space. Trust issues and inequalities in access and use can lead to less participation, which has social impacts by excluding certain groups, and economic impacts by decreasing the diversity and richness of data which, in turn, can lead to less informed tourism policy decisions and less inclusive practices [146,147].
• Technical and economic challenges: Technical challenges can translate into direct economic impacts, such as additional costs to address vulnerabilities and maintain infrastructure. These challenges can also stall innovation and thus limit economic growth and job creation in the tourism sector. In addition, pressure on financial resources can divert investment from other critical areas, such as environmental protection and social development [117,148,149,150].
• Socio-environmental and ethical concerns: Socio-environmental and ethical impacts reflect the wider responsibility of the data space. Sustainability challenges and complications in international cooperation may affect the tourism sector’s ability to adapt to global environmental regulations. Ethical issues in data management have profound social implications, such as privacy and fairness. In addition, the environmental impact of data infrastructure and associated energy must be considered and minimised to align with sustainable tourism objectives [128,142].

These realigned categories provide a more comprehensive understanding of how pressures on the state of the tourism data space can translate into tangible environmental, social, and economic impacts. Effectively addressing these impacts requires an integrated approach and collaboration among all stakeholders to ensure that the data space serves commercial and operational purposes and contributes positively to the well-being of communities and the environment.

6.5. Response

In the context of a DPSIR analysis for building a tourism data space, response indicators address multiple facets of the data ecosystem. Training is prioritised through capacity-building strategies that foster skills in data management and emerging technologies. Infrastructure robustness is essential, with plans for upgrading and expansion. Data security, privacy, and equity are key, leading to data protection policies, equitable coverage initiatives and inclusion policies. The importance of public engagement and perception is acknowledged through participation strategies and data awareness campaigns. In addition, sustainable practices, and ethical management are promoted through sustainability programmes and codes of ethics. Systems integration, innovation and resilience are key, as is international cooperation. Finally, audit mechanisms, incentives for participation and funding strategies ensure continuous and sustainable development of the data space, with a focus on adaptability and continuous improvement. Figure 10 includes the main response factors under consideration.

The following themes are proposed for the response indicators in constructing a tourism data space.

• Development and skill enhancement: Training and awareness raising are key to empowering tourism professionals to manage data effectively. These strategies ensure that staff are up to date with the skills needed to make the most of the data space, directly impacting quality and innovation within the sector.
• Infrastructure and technology improvement: Maintaining and upgrading the technology infrastructure is vital to support data’s increasing amount and complexity. Resilience and sustainability are critical to ensure the tourism data space is durable and environmentally responsible.
• Regulatory and ethical frameworks: Regulatory and ethical frameworks set the rules of the game, ensuring privacy, security, and accessibility of data. They are fundamental to maintaining user trust and ensuring ethical and equitable use of information.
• Engagement and inclusivity: Encouraging the participation of all stakeholders and ensuring equitable data representation are important steps in making the data space truly inclusive and representative, which enriches tourism analysis and decision-making.
• Innovation and development support: Innovation and integration are crucial to maintaining the tourism sector’s competitiveness. Supporting innovation through incentives and international cooperation opens new opportunities and enhances global interoperability.
• Monitoring and continuous improvement: Monitoring and feedback mechanisms allow for constant data space review and improvement. This ensures the system adapts and evolves according to sector needs and user expectations.
• Financial and resource management: Sound financial management is necessary to ensure sufficient resources for the data space’s construction, maintenance and enhancement. Sustainable financing models are crucial for the long-term viability of the tourism data space.

Each category reflects a key facet of the responses needed to effectively manage the challenges identified in the tourism data space. These responses must not be implemented in isolation, but as part of an integrated approach taking into account the interdependencies between skills, technology, regulation, inclusivity, innovation, monitoring, and funding, to create a robust, secure and progressive data space.

7. Overview

The DPSIR model, when applied to the construction of a European-wide tourism data space, brings significant benefits by providing a structured framework to identify and analyse the drivers, pressures, states, impacts and responses related to the use and management of data in the tourism ecosystem. This structured approach enables a comprehensive understanding of tourism systems, fostering well-informed decisions and effective policies to ensure the sustainability and competitiveness of the European sector.

However, the model has limitations. Its linear nature may fall short in capturing the complexity and interconnected nature of tourism systems, and it may lack the flexibility to deal with rapid technological changes and the specific dynamics of the European tourism sector. Moreover, adapting a general model such as the DPSIR to such a specialised context may demand adjustments and refinements to accurately reflect the unique characteristiques of the tourism domain.

Figure 11 shows an overview of the components of a DPSIR Framework in developing a tourism data space.

8. Discussion and Conclusions

A Tourism Data Space represents a crucial evolution in how data is managed and used in the tourism industry. This space is conceived to foster collaboration and information exchange between public and private entities, thus improving decision-making and tourism policies. Integrating various related sectors, such as transport-mobility, environment, and smart cities, among others, is central to this approach, underlining the transversality of tourism [32].

Regulations overseeing data sharing must overcome obstacles without stifling innovation, while maintaining a balance between legal certainty and accessibility. In this framework, governance emerges as an essential aspect, delineating responsibilities and rules within the data space for all stakeholders [151,152].

A comprehensive and ongoing evolving European legal framework is available that addresses the challenges of the tourism data space from different angles [31]. Its analysis highlights the need to address the multidimensional challenges of building tourism data spaces by including five components:

• Social: to ensure that data is representative, equitable and inclusive, reflecting all communities and regions and protecting the rights of individuals [143,153,154].
• Economic: supporting innovation and ensuring that data spaces benefit not only large corporations, but also SMEs and other key players in the sector [155].
• Environmental: ensuring that the technological infrastructure behind these data spaces does not have an adverse environmental impact and instead supports the sustainability of the tourism sector [156,157,158].
• Governance: creating an organizational culture and governance system that fosters data management transparency, ethics, and accountability [159].
• Technological: addressing the technological challenges in creating and maintaining robust, secure, and efficient data spaces. This includes the development of advanced algorithms, data processing capabilities, and cybersecurity measures to manage and protect the vast amounts of data generated in the tourism sector. It is essential to stay ahead in technological innovations to ensure the data spaces are not only functional, but also ahead of potential digital threats and challenges [160,161,162].

In the realm of creating and optimising tourism data spaces, it is imperative consider technology and sustainability as fundamental pillars. Technological innovation improves the collection and use of data, enriching the personalisation of tourism marketing and business strategies. Nonetheless, it must be conducted sustainably and respect the environment and local communities.

Creating integrated and enhanced tourism data spaces is a multifaceted process that must address economic, political, socio-cultural, technological, and environmental aspects. A holistic strategy that is proactive and adaptive can drive innovation and promote sustainable growth. Policies aligned with emerging tourism trends, transparent management of privacy and security, and the use of advanced infrastructures and analytics are crucial for effectively developing these spaces.

Continued technological innovation is vital to improve data collection and storage, enriching personalisation and tourism marketing strategies. However, this progress must go hand-in-hand with sustainability and a deep respect for the environment and local communities. The development of data spaces should encourage responsible tourism practices.

The survey analysis of European entities producing or using tourism information shows that data sharing is more frequent in countries where tourism is vital to the economy, such as Spain and Italy [58]. Public administrations are in the lead with tourism data production and consumption, followed by NGOs, indicating a sustainable and responsible tourism trend. Large companies consume more data than they produce, while startups show a balance between production and consumption, suggesting a focus on innovation. The survey highlights the need for data exchange to enhance the planning and operations of tourism services, conduct market analysis, and elevate the overall tourist experience. The most highly regarded data encompass “Device data”, “Transaction data”, and “User-generated data”. In addition, emerging trends in the tourism sector, such as ecotourism, inclusivity and personalisation of the tourism experience, are identified, indicating a shift towards sustainability and a focus on specific niche travellers.

Given its dynamic nature and socio-economic relevance, the tourism industry benefits from the creation of specialised data spaces. However, the DPSIR analysis reveals several challenges and considerations that underline the imperative need for a robust technological, regulatory, and governance framework. Within such a framework, the following factors stand out:

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Drivers and pressures: The drivers behind the creation of these data spaces include the digitisation of the tourism sector, the need for personalisation and the growing demand for sustainability [97]. However, these drivers are exerting pressure on the data ecosystem, leading to challenges such as information overload and heterogeneity of sources.

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Status and impact: While efforts to establish integrated and high-quality data spaces exist, the current state presents challenges. These include declining data quality and declining user trust due to privacy concerns. In addition, uneven geographical representation and interoperability challenges act as constraints, limiting the true potential of a unified European data market.

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Responses: Steps are being taken to address these issues, with examples being data protection policies, public participation strategies and feedback mechanisms. However, despite these efforts, the ecosystem still exhibits notable gaps.

Applying the DPSIR model in socio-technological domains is complex due to the rapid pace of technological evolution, which may not capture all aspects to provide an updated analysis. Technology in the tourism sector involves a complex interaction of factors and plays a transformative role. This circumstance can affect the “states” as well as the “responses”, leading to new pressures. There is significant variation among regions in terms of their technological adaptation, and this could question the model’s applicability. Indeed, what is considered a technological driver in one region might not hold the same significance in another. Hence, adapting the model to different contexts is necessary.

Through a DPSIR analysis conducted on tourist data spaces, this study has successfully met its objectives and validated the previously formulated hypothesis. The analysis demonstrated that effective data integration and management are indeed pivotal in transforming conventional tourist destinations into smart destinations, thereby confirming their substantial influence on enhancing sustainability and competitiveness in the tourism sector.

The construction of a Tourism Data Space lays a solid foundation for the advancement of knowledge on value creation from data sharing in the context of the tourism industry. The results of the survey aimed at understanding why and how data is shared between different tourism entities reinforced by the application of the DPSIR methodologies, show a clear opportunity for creating new added value in the tourism sector. This new added value can have a significant impact in the sustainability of smart tourism destinations, especially in addressing pressing challenges that are generating more interest (human pressure, resources management…). This is important from the point of view that a tourism data space will facilitate the crossing and sharing of data from different sources.

The analysis indicates that the construction of a tourism data space can have a direct positive impact on the decision making mechanisms of the smart tourism destinations, and therefore in the quality of life of residents and tourists.

The construction of a tourism data space encounters different challenges, primarily related to the access of data, both from the public and private sectors. A limitation in the research is also associated with the lack of private data sources available to enrich the analysis.

The reality is that the data economy is already established, and within the European Union, there is a significant momentum for deploying data spaces. In fact, tourism is one of the fields earmarked for EU funds to continue working in this area. This is very promising for the future research, which can delve into analysing the tangible impacts of the implemented tourism data space in addressing real challenges. Indeed, the European Commission has already opened an important call defining specific use cases to address the old and new challenges of the tourism sector. Sustainability takes precedence, but the scope extends to encompass areas like short-term rentals through the utilization of data spaces.