International Data Spaces Association

Europe is developing a common data space for tourism, aiming to integrate various stakeholders, including local and regional authorities, the private sector, and multiple member states. Spain is among them, where several workshops have already been conducted as part of the process to energize the national tourism data space, focusing on discussing the challenges, opportunities, and use cases in the sector.

The future tourism data space is at the core of the transition towards greater sustainability and profound digitization in the tourism sector. This initiative is also aligned with the European data strategy, which envisions creating a single market where information can be freely shared, promoting innovation across different economic sectors and certain areas of public interest. Furthermore, future data spaces hold significant importance in Europe's quest to regain digital sovereignty, reasserting control over data, fostering innovation, and the ability to develop and implement its own legislation in the digital environment.

Even in last year's conference on the Future of the European Union, the importance of data spaces in sectors like tourism and mobility was highlighted, recognizing them as key sectors in the digital transformation. Tourism, in particular, stands to benefit greatly from such initiatives due to its dynamic and ever-evolving nature, heavily reliant on user experiences and the timely access to necessary information.

Therefore, the European common data space for tourism aims to boost data exchange and reuse, establishing a governance model that respects existing legislation. The ultimate goal is to benefit all stakeholders in various ways, including:

• Promoting innovation in the sector by enhancing and personalizing services through access to high-quality information.
• Assisting public authorities in making data-driven decisions for the sustainability of their tourism offerings.
• Supporting specialized businesses in providing better services based on data analysis and market trends.
• Facilitating market access for sector businesses in Europe.
• Improving data availability for the creation of high-quality official statistics.

However, there are several challenges in sharing existing data in the tourism sector, primarily stemming from concerns regarding reciprocity and data reuse. These challenges can be summarized as follows:

1. Data interoperability: Designing and managing a European tourist experience involves handling a wide array of non-personal data across various domains like mobility, environmental management, or cultural heritage, all of which enrich the tourist experience. The primary challenge in this regard is the ability to share and cross-reference information from different sources without duplications, with a reference framework that promotes interoperability between different sectors, utilizing existing standards where possible.
2. Data access: Unlike other sectors, the European Union's tourism ecosystem lacks a single marketplace platform. Various offerings are modeled and cataloged by different actors, both public and private, at national, regional, or local levels. While the tourism data space does not aim to serve as a central booking node, it can greatly contribute by providing effective information search tools, facilitating access to necessary data, decision-making, and fostering innovation in the sector.
3. Data provision by public and private entities: There is a wide variety of data in this sector, from open data like schedules and weather conditions to private and commercial data such as search, bookings, and payments. A significant portion of these commercial data are managed by a small group of large private entities, making it necessary to establish inclusive dialogue for fair and appropriate rules on data access within the shared data space.

To consolidate this initiative, the Transition Path for Tourism emphasizes the need to advance in the creation and optimization of a specific data space for the tourism sector. This aims to modernize and enhance this crucial economic sector in Europe through key actions:

• Governance: The governance of the tourism data space will determine how the main enablers will relate to ensure interoperability. The goal is to ensure that data is accessed, shared, and used lawfully, fairly, transparently, proportionally, and without discrimination to build trust, support research, and foster innovation within the sector.
• Semantics for interoperability: Common data models and vocabularies are needed for effective interoperability. National statistical agencies and Eurostat already have some consensus definitions, but their adoption within the tourism sector remains uneven. Therefore, clarifying definitions within the multilingual European context is crucial to establish a common European data model, accompanied by implementation guidelines. Spain has already made pioneering efforts in semantic interoperability, such as the development of the Tourism Ontology, technical standards for semantic applied to smart tourism destinations, or the model for collecting, exploiting, and analyzing tourism data.
• Technical standards for interoperability: The Data Spaces Support Center (DSSC) is already working to identify common technical standards that can be reused, taking into account existing or ongoing initiatives and regulatory frameworks. Additionally, all data spaces will also benefit from Simpl, a cloud federation middleware that will serve as a foundation for major data initiatives funded by the European Commission. Furthermore, there are specific technical standards in the sector, such as those developed by Eurostat for sharing accommodation data.
• Defining the role of the private sector: The European common data space for tourism will clearly benefit from cooperation with the private sector and the market for new services and tools it can offer. Some platforms already share data with Eurostat, and new agreements are being developed to share other non-personal tourism data, along with the creation of a new code of conduct to foster trust among various stakeholders.
• Supporting SMEs in the transition to a data space: The European Commission has long provided specific support to SMEs through Digital Innovation Hubs (DIHs) and the Enterprise Europe Network (EEN), offering technical and financial support, as well as assistance in developing new digital skills. Some of these centers specialize in tourism. Additionally, the European Tourism Enterprises Network (SGT), with 61 members in 23 countries, also provides support for digitalization and internationalization. This support for SMEs is particularly relevant given that they represent nearly all of the companies in the tourism sector, specifically 99.9%, of which 91% are microenterprises.
• Supporting tourism destinations in the transition to a data space: Tourism destinations must integrate tourism into their urban plans to ensure sustainable and beneficial tourism for residents and the environment. Several Commission initiatives enhance the availability of necessary information for tourism management and the exchange of best practices, promoting cooperation among destinations and proposing actions to improve digital services.
• Proof of concept for the tourism data space: The European Commission, along with several member states and private actors, is currently conducting a series of pilot tests for tourism data spaces through the DSFT and DATES coordination and support actions (CSAs). The main goal of these tests is to align with existing technical standards for accommodation data and demonstrate the value of interoperability and business models that arise from data sharing through a realistic and inclusive approach, focusing on short-term rentals and accommodation. In Spain, the report on the state of the tourism data space explains the current status of the national data space design.

In conclusion, the European Commission is firmly committed to supporting the creation of a space where tourism-related data flows while respecting the principles of fairness, accessibility, security, and privacy, in line with the European data strategy and the Pact for Skills development. The goal is to build a common data space for tourism that is progressive, robust, and integrated within the existing interoperability framework. To achieve this, the Commission urges all stakeholders to share data for the mutual benefit of everyone involved in an ecosystem that will be crucial for the entire European economy.

At the end of October, there will also be a new opportunity to learn more about the tourism data space and the challenges associated with data spaces in general, through the European Big Data Value Forum in Valencia.

Content created by Carlos Iglesias, Open Data Researcher and Consultant, World Wide Web Foundation.

The content and viewpoints reflected in this publication are the sole responsibility of the author.

A data space is a development framework that enables the creation of a complete ecosystem by providing an organisational, regulatory, technical and governance structure with the objective of facilitating the reliable and secure exchange of different data assets for the common benefit of all actors involved and ensuring compliance with all applicable laws and regulations. Data spaces are also a key element of the European Union's new data strategy and an essential building block in realising the goal of the European single data market.

As part of this strategy, the EU is currently exploring the creation of several data space pilots in a number of strategic sectors and domains: health, industry, agriculture, finance, mobility, Green Pact, energy, public administration and skills. These data spaces offer great potential to help organisations improve decision-making, increase innovation, develop new products, services and business models, reduce costs and avoid duplication of efforts. However, creating a successful data space is not a trivial activity and requires first carefully analysing the use cases and then facing major business, legal, operational, functional, technological and governance challenges.

This is why, as a support measure, the Data Spaces Support Centre (DSSC) has also been created to provide guidance, tools and resources to organisations interested in creating or participating in new data spaces. One of the first resources developed by the DSSC was the Data Spaces Starter Kit, the final version of which has recently been published and which provides a basic initial guide to understanding the basic elements of a data space and how to deal with the different challenges that arise when building them. We review below some of the main guidelines and recommendations offered by this starter kit.

The value of data spaces and their business models

Data spaces can be a real alternative to current unidirectional platforms, generating business models based on network effects that respond to both the supply and demand of data. Among the different business model patterns existing in data spaces, we can find:

• Cost sharing: all participants save time and money by sharing data for a common purpose, such as the smart network of connected SCSN providers.
• Joint innovation: innovation is only possible if data is shared as none of the participants have the complete data individually, e.g., the Eona-X platform for mobility, transport and tourism.
• Combined forces: different actors join forces to prevent a single actor from dominating a certain space, as in the EuPro Gigant manufacturing data network.
• Shared market: actors with common interests share data with each other in order to benefit each other, such as the Catena-X automotive network.
• Greater common good: when the public and private sectors share data for a social purpose, as for example in the mobility data space developed in Spain through the Mobility Working Group of the Gaia-X Hub.

The legal aspects

The legal side of data spaces can be a major challenge as they necessarily move between multiple legal frameworks and regulations, both national and European. To address this challenge, the Data Spaces Support Centre proposes the elaboration of a reference framework composed of three main instruments:

• The cross-cutting legal frameworks that will apply to all data spaces, such as contract law, data protection, intellectual property, competition or cybersecurity laws.
• The organisational aspects to consider when establishing models and mechanisms for data governance in each specific case.
• The contractual dimension to be taken into account when exchanging data and the agreements and terms of use to be established to make this possible.

Operational activities

The design of operational activities should address the arrangements that enable the organisational functioning of the data space, such as guidelines for onboarding new participants, decision-making and conflict resolution.

In addition, consideration should also be given to business operations, such as process streamlining and automation, marketing tasks and awareness-raising activities, which are also important components of operational activities.

Functionality of data spaces

Data spaces shall share a number of basic components (or building blocks) that will provide the minimum functionality expected of them, including at least the following elements:

• Interoperability: data models and formats, data exchange interfaces and origin and traceability.
• Trust: identity management, access and usage control and secure data exchanges.
• Data value: metadata and location protocols, data usage accounting, publishing and commercial services.
• Governance: cooperation and service level agreements and continuity models.

While these components can be expected to be common to all data spaces and provide similar functionality, each individual data space can make its own design choices in implementing and realising them.

Technological aspects

Data spaces are designed to be technology agnostic, i.e., defined solely in terms of functionality and with freedom in the choice of specific technologies for implementation. In this scenario it will be important to establish clear references in terms of:

• A formal basis of de facto standards to be followed.
• Specifications to serve as a reference for the different implementations.
• Open source implementations of the basic components carried out by other actors.

Governance of data spaces

Designing, implementing and maintaining a data space requires multiple organisations to collaborate together across different functions. This requires these entities to build a common vision of the key aspects of such collaboration through a governance framework.

This will require a joint design exercise through which stakeholders formalise a set of agreements defining key strategic and operational aspects, such as legal issues, description of the network of participants, code of conduct, terms and conditions of use, data space incorporation and membership agreements, and governance model.

In the near future the DSSC support centre will identify the core components of each of the dimensions described above and provide additional guidance for each of them through the development of a common blueprint for data spaces. So, if you are considering participating in any of the data spaces initiatives that are being launched, but are not quite sure where to start, then this basic starter kit will certainly be a valuable resource in understanding the basic concepts - along with the glossary that explains all the related terminology. Also, don't forget to subscribe to the support centre's newsletter to keep up to date with all the latest news, documentation and support services on offer.

Content prepared by Carlos Iglesias, Open data Researcher and consultant, World Wide Web Foundation.

The contents and views reflected in this publication are the sole responsibility of the author.

We live in the era of data, a lever of digital transformation and a strategic asset for innovation and the development of new technologies and services. Data, beyond the skills it brings to the generator and/or owner of the same, also has the peculiarity of being a non-rival asset. This means that it can be reused without detriment to the owner of the original rights, which makes it a resource with a high degree of scalability in its sharing and exploitation.

This possibility of non-rival sharing, in addition to opening potential new lines of business for the original owners, also carries a huge latent value for the development of new business models. And although sharing is not new, it is still very limited to niche contexts of sector specialisation, mediated either by trust between parties (usually forged in advance), or tedious and disciplined contractual conditions. This is why the innovative concept of data space has emerged, which in its most simplified sense is nothing more than the modelling of the general conditions under which to deploy a voluntary, sovereign and secure sharing of data. Once modelled, the prescription of considerations and methodologies (technological, organisational and operational) allows to make such sharing tangible based on peer-to-peer interactions, which together shape federated ecosystems of data sets and services.

Therefore, and given the distributed nature of data spaces (they are not a monolithic computer system, nor a centralised platform), an optimal way to approach their construction is through the creation and deployment of use cases. 

The Data Office has created this infographic of a 'Model of use case development within data spaces', with the objective of synthetically defining the phases of this iterative journey, which progressively shapes a data space. This model also serves as a general framework for other technical and methodological deliverables to come, such as the 'Use Case Feasibility Assessment Guide', or the 'Use Case Design Guide', elements with which to facilitate the implementation of practical (and scalable by design) data sharing experiences, a sine qua non condition to articulate the longed-for European single data market.

The challenge of building a data space

To make the process of developing a data space more accessible, we could assimilate the definition and construction of a use case as a construction project, in which from an initial business problem (needs or challenges, desires, or problems to be solved) a goal is reached in which value is added to the business, providing a solution to those initial needs. This infographic offers a synthesis of that journey.

The data economy represents a huge business opportunity for companies of all sizes and sectors. According to European Commission estimates, the Data Economy will be worth €829 billion in 2025 for the 27 member states. But for the data economy to develop properly, structures are needed to facilitate the exchange of data and, with it, the development of business models based on its exploration and exploitation.

Data spaces fulfil this function by facilitating the development of an ecosystem where different actors share data in a voluntary and secure manner. To do so, they must follow common governance, organisational, regulatory and technical mechanisms.

One way to ensure that this is done properly is through reference models, such as the IDS-RAM (International Data Spaces Reference Architect Model), an initiative developed by the International Data Space Association and endorsed by the European Union.

What is the International Data Space Association?

IDSA (International Data Spaces Association) is a coalition currently comprised of 133 international, not-for-profit companies, which emerged in 2016 to work on the concept of data spaces and the principles that their design should follow in order to obtain value from data through sharing, based on secure, transparent and fair mechanisms for participants, which guarantee sovereignty and trust. These companies represent dozens of industry sectors and are based in 22 countries around the world.

IDSA is connected to different European initiatives, including BDVA, FIWARE and Plattform Industrie 4.0, participating in more than twenty European research projects, mainly in the Horizon 2020 programme.

IDSA's mission is to drive the global digital economy. To this end, among other things, it promotes an architectural reference model called IDS (International Data Spaces), a secure and sovereign data exchange system. The aim of this model is to standardise data exchange in such a way that participants can obtain all possible value from their information without losing control over it, setting the conditions for the use of their own data.

IDS-RAM architecture

The IDS-RAM (Reference Architecture model) is characterised by an open architecture (they publish their code as open source software), reliable and federated for cross-sector data exchange, facilitating sovereignty and interoperability.

IDS-RAM establishes a series of standardised roles and interactions through a 5-layer structure (business, functional, process, information and system) that are addressed from the perspective of security, certification and governance, as shown in the following figure.

These layers are critical to ensure the success of a data sharing initiative. Let's look at each of them based on the IDSA's own "Reference architecture model" and Planetic's "Positioning on Data Spaces" report, where IDS-RAM is analysed as a success story.

The business layer defines the different existing roles and the interaction patterns between them, including contracts and data usage policies. Specifically, there are four roles:

• Essential participant: any organisation that owns, offers or consumes data.
• Intermediary: trusted entities and intermediaries, such as brokers, clearing houses, identity providers and others.
• Service/Software Provider: companies that provide services and/or software to participants.
• Governance body: such as certification bodies, which are essential to guarantee the capabilities of organisations and generate an environment of trust. The IDS Association itself would also be included in this section.

These roles are related in an ecosystem marked by six categories of requirements, defined in the functional layer:

• Trust, achieved through identity management and user certification.
• Security and data sovereignty, which includes authentication and authorisation, usage policies, trusted communication and technical certification.
• Data Ecosystem, which includes the description of data sources, data brokering and vocabularies used for metadata.
• Standardisation and interoperability, which ensures the operability necessary for successful data exchange.
• Value-added applications, which allow data to be transformed or processed.
• Data marketisation, which covers aspects such as billing, usage restrictions, governance, etc., necessary when data sharing is done under payment models.

The process layer captures the interactions that take place within the data space, including the on-boarding of users, for which they need to acquire an identity provided by a certification body and request a data connector (a technical component to be installed) from a software provider.

identity provided by a certification body and request a data connector (a technical component to be installed) from a software provider. This layer also defines the processes required for data exchange and the publication and use of data apps.

The information layer explains the information model and the common vocabulary to be used to facilitate compatibility and interoperability, so that data exchange can be automated. A proprietary ontology based on an RDF schema is used for its definition.

Finally, the system layer assigns a concrete architecture of data and services to each role in order to guarantee functional requirements.

All these abstractions of layers and perspectives enable the exchange of data between data providers and data consumers, using the appropriate software connectors, accessing the metadata broker where data catalogues and their conditions of use are specified, with the possibility of deploying applications for data processing and keeping track of the transactions carried out (clearing house), all of this guaranteeing the identity of the participants.

Ultimately, it is a functional framework that provides a governance framework for secure and reliable interoperability and an open software architecture to ensure maximum adoption. In this sense, the IDSA has set itself the following objectives:

• Establish the IDS model (RAM) as the international standard for data exchange in the economy of the future.
• Evolve this reference model according to use cases.
• Develop and evolve an adoption strategy for the model.
• Support its deployment based on certifiable software solutions and commercial models.

This standard is already being used by many companies as diverse as Deutsche Telekom, IBM or Volkswagen.

The role of IDS-RAM in Gaia-X and the European Data Strategy

The IDS reference architecture model is part of the initiatives deployed within the overall framework of the EU data strategy.

Through various initiatives, the European Commission seeks to promote and interconnect data spaces in order to foster the consultation, sharing and cross-exploitation of available data, while ensuring their privacy. It is in this framework that Gaia-X has been launched, an European private sector initiative for the creation of an open, federated and interoperable data infrastructure, built on the values of digital sovereignty and data availability, and the promotion of the data economy.

The IDSA association, promoter of the IDS reference architecture, is actively participating in Gaia-X, so that the initiatives currently underway to develop reference models and implementations for data sharing with sovereignty and trust can be brought together in a de facto open standard.

Content prepared by the datos.gob.es team.

There is no doubt that data is a fundamental asset for companies. Properly processed, they generate great competitive advantages, both in decision-making and in the generation of new products and services, enabling technologies such as Artificial Intelligence. This situation has made many organisations wary of sharing their data. However, the situation is changing and more and more companies and organisations are becoming aware of the advantages of this practice.

Data sharing drives efficiency in supply chains, enabling faster and more innovative product development. By sharing their data, organisations also benefit from access to third-party data, which can be of great use in a variety of fields: from training machine learning systems to enriching internal analytics. In addition, the fact that several companies are working in the same field, generating advances, means that the market matures earlier, opening up new business opportunities, as well as reducing the time and costs of marketing products. There are also benefits in terms of transparency and reputation.

Secure and controlled environments, such as data spaces, are necessary for this data exchange to take place in a safe and secure manner.

What are data spaces?

A data space is an ecosystem where diverse actors share data in a voluntary and secure manner, following common governance, organisational, regulatory and technical mechanisms. Some of the characteristics of advanced data spaces include:

• They ensure participants' trust and sovereignty over their data, creating an ecosystem of peer-to-peer data sharing. In a data space, each participant retains control over its own data, indicating the terms and conditions under which it can be used.
• They are independent of the underlying technological solution. This allows for portability and deployment in different physical infrastructures.
• Data is shared under FAIR principles, which facilitates the location, access and use of the data. To this end, datasets must be properly described, including the taxonomies used and their restrictions on use.
• They enable the deployment of different roles, such as data producers, consumers, data service providers, component developers or operators of essential services, facilitating the development of data intermediaries.
• They ensure the identity of the participants, as well as the suitability of the software components used, by means of appropriate approval or certification mechanisms.
• They enable different policies of access and use of information, so that data subjects can determine whether data is shared for free or not, under mechanisms that guarantee its proportionality.
• They ensure interoperability

European data spaces key to boosting the data economy

Data spaces are a key element of the European Data Strategy, which, among other issues, seeks to boost the region's economy through the creation of a single European data market, where data flows between Member States and between sectors of activity, in accordance with the European values of self-determination, privacy, transparency, security and fair competition.

In this strategy, the European Commission has already announced its interest in investing in and developing common data spaces in strategic economic sectors and sectors of public interest, notably those related to manufacturing, sustainable energy, mobility, health, finance, energy, agriculture, public administrations and skills. Once developed, these spaces are expected to be interconnected, so that the data available in them can be cross-exploited.

The creation of these data spaces seeks to overcome the legal and technical barriers linked to data sharing, through common standards, tools and infrastructures in a context of digital sovereignty. According to the European data strategy, the development of European data spaces should be carried out taking into account the following elements:

• The deployment of tools and services for data processing, exchange and sharing, as well as the federation of secure and energy-efficient cloud capabilities and related services. These tools should enable access to data in a fair, transparent, proportionate and non- discriminatory manner.
• The development of clear and reliable data governance structures, in compliance with EU law, with particular attention to the protection of personal data, consumer and competition law.
• Improving the availability, quality and interoperability of data, both within specific domains and across sectors.

In this regard, the European Commission endorses various measures and initiatives for the development of secure and sustainable digital infrastructures. These include Gaia-X, which seeks the development of an open, federated and interoperable data infrastructure in the cloud, and the International Data Spaces Association (IDSA), probably a substantial part of Gaia-X, which promotes an architectural reference model for the development of data spaces.

In the image below you can see these and other European initiatives at different levels related to data spaces. The left and central part shows some of the main European data initiatives, and how these are supported by hardware infrastructures. The right hand side shows the alignment with the most important EU initiatives within the European Data Strategy.

Spain is aligned with Europe in this area: the transition to a data economy is among the axes of the Digital Spain 2025 Plan. Work is currently underway to promote the enabling environment for the creation of sectoral data spaces, through the various data initiatives included in the Recovery, Transformation and Resilience Plan. One example is the Spanish Gaia-X Hub, aimed at deploying a robust ecosystem in the field of industrial data sharing, comprising companies of all sizes. The aim of this type of action is to create a community around data that favours innovation and economic growth, with the consequent benefit for society.

Content written by the datos.gob.es team