Decoding Data Spaces (part I): A guide for companies

September 9, 2024

In a world awash with information, businesses need tools that make it easier to collaborate with each other and monetize their data, all while maintaining data security and privacy. Data Spaces present themselves as the solution. In this first part of our guide, we will explore the fundamental pillars of Data Spaces, the key roles involved and the benefits they can bring to your business.

What is a Data Space?

A Data Space is an ecosystem where value is generated to data through voluntary sharing, in an environment governed by sovereignty, trust, and security.

In a Data Space it is possible to establish who can access certain data and under what conditions, facilitating in this way the implementation of diverse use cases that respond to the specific needs of each participant, without compromising data privacy.

Operating as a controlled but open, heterogeneous, and decentralized environment, Data Spaces promote a free and equitable flow of information becoming the ideal scenario to monetize information in a secure manner.

Data Spaces are set to become essential tools for the exchange of information between the so-called “participants” (companies, associations, and administrations, but also individual users depending on what each Data Space allows). These digital ecosystems in the cloud allow participants to collaborate through coordinated and regulated data management.

The benefits of Data Spaces

Data Spaces can offer a number of benefits in different sectors. Some of them are highlighted below:

Economic benefit: Data Spaces have a business model associated with them for the participants (especially for those who contribute or consume data), so the first benefit is directly obtained from the profitability of the information.
Fostering innovation: Data spaces catalyze the development of new products and services by facilitating access to a variety of data and insights that no single participant has on its own.
Creation of strategic alliances: They enable collaboration between different organizations, which can lead to the creation of new business models and joint market strategies.
Process optimization: Improving operational efficiency by enabling the analysis of data sets to identify inefficiencies and opportunities for improvement.
Competitiveness improvement: The use of data to identify areas for improvement allows companies to adjust their strategies with respect to their competitors.
Positioning: Due to data sharing and visibility, organizations can strengthen their position in the marketplace.

Challenges

There are currently several standards being developed simultaneously, such as the International Data Space Association (IDSA) standard, or the Gaia-X standard. These efforts are critical to shaping the future of data spaces, as the field is still characterized by a certain degree of fragmentation and immaturity.

Different standards and frameworks often focus on specific domains or industries, which can lead to siloed approaches and hinder the creation of a unified, global data space ecosystem.

Figure. Challenges of a Data Space.

Building blocks

Despite these challenges, the potential benefits of data spaces are undeniable. Data spaces can unlock new business models, foster innovation and drive economic growth by enabling the secure and standardized exchange of data.

In this sense, any Data Space proposal must take into account the basic building blocks that are taken as a reference in different organizations (DSSC, OpenDEI, etc.). These blocks identify the business and technical components that must be developed in each Data Space to be considered useful, secure and productive.

Figure 1. Overview of the building blocks of a data space.

In this way, a series of main pillars to consider when we talk about data spaces are identified:

Figure 2. Main pillars of a data space.

Business: The essential and necessary concepts for the development of the business model of a data space should be provided. When talking about business models in the context of Data Spaces, we must make a clear distinction between:
- The business model of the Data Space as an infrastructure that can support multiple use cases.
- The business models of the individual Data Space participants involved in one or more Data Space use cases.
Governance: Governance will need to adapt as these evolve. This includes two key elements:
- Organizational governance: guides the creation of governance authorities to ensure inclusive and transparent management.
- Data sharing governance: establishes common rules for efficient and secure data transactions.
Compliance: Ensure compliance with the law and the establishment of a robust contractual framework. This includes two main components:
- Regulatory compliance: provides initiatives with an understanding of the legal environment and helps assess applicable regulatory requirements to ensure legal compliance and, typically, alignment with EU values (as drivers of GAIA-X).
- Contractual framework: establishes clear and enforceable rights and obligations for space participants and provides contractual remedies to regulate their data transactions.
Interoperability: Data interoperability is a main pillar for the smooth and efficient integration of heterogeneous systems. In this sense, maximizing interoperability mechanisms with other sectoral and European data spaces is crucial to foster collaboration, efficiency and innovation. In this regard, it is important to consider:
- Adoption of recognized interoperability standards.
- Participation and alignment with European initiatives and projects: DSSC (Data Space Support Center), DBSA (Data Spaces Business Alliance)...
Sovereignty and trust: Data sovereignty and trust are two fundamental aspects. Thus, the Data Space must have clear rules that establish who has access to what data and under what conditions, as well as establish limitations on its use.
Value creation: The creation of value through data sharing, whether in the form of a new product, service or the generation of efficiencies, is another key pillar. As a general rule, data sharing occurs when the value of sharing is greater than the cost of making that data available.

It is important to keep in mind that the value of the data is not only about its monetization, but other factors such as the generation of benefits or opportunities, as well as risk reduction (i.e. the generation of new partnerships) must be taken into account.

Any new Data Space has to define the value creation models to get participants to join this space.

Roles in a Data Space

A Data Space is made up of different participants who play different roles depending on the scope of action they are focused on:

Figure 3. Roles in the data space

Resource providers and consumers: The participants that provide data and can interact with the data of other participants.
Technology provider: The participant that provides components for the space to operate correctly, making it a secure and trusted environment.
Intermediaries: The participant that encompasses third parties that provide the services necessary for publishing, searching resources and recording transactions.
Operators of the space: Participants dedicated to the complete administration of the space. They are also in charge of certifying participants, overseeing the governance of the data space and establishing the roadmap for the development of new functionalities.

AUTHORS
Santiago Morante
AI Alliances and Solutions Development Manager
Paula Valles
Data Sales Consulting

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