However, one of the main challenges we face is to explain companies, especially those without technical skills, the data space concept and how the “data spaces” paradigm is different from previous data sharing approaches. Furthermore, it must be clearly demonstrated what are the real benefits of using the data space approach and how it can improve data valorization both inside the company and externally.
The data spaces blueprint: guiding implementation and deployment
The Data Space Support Centre is defining the so-called Data Spaces Blueprint: “A consistent, coherent and comprehensive set of guidelines to support the implementation, deployment and maintenance of data spaces. The blueprint contains the conceptual model of data space, data space building blocks, and recommended selection of standards, specifications and reference implementations identified in the data spaces technology landscape”
The conceptual model and building blocks approach provide a good and detailed overview of the main concepts like trust, data sovereignty, interoperability, business models and data governance but they do not provide a non-technical overview of the data space processes, i.e., the steps a company must follow to participate in a data space either as a data provider or as a consumer. Main concepts are easily understood but the operational level, the way in which they apply to the data sharing processes, is not so clear.
Need for non-technical understanding of the data space concept
DATES project is a preparatory action of the Digital Europe Programme where a consortium of 13 partners (including IDSA and Tecnalia), supported by a network of more than 40 organizations representing the whole ecosystem of the tourism sector, is defining the blueprint for the future European Tourism Data Space.
In DATES, we have found that explaining the data space concept as a “participant journey” is very helpful to understand how the building blocks cooperate to provide the whole experience of sharing data in an interoperable and standardized way.
The main steps of this journey, that can be considered as the main phases of the data space engagement life cycle, are the following ones:
While the company follows the necessary steps, the difficulties and challenges of each step are revealed, in addition to understanding how the concepts of sovereignty, trust and valorization are reflected in each of the steps.
Building trust in a data spaces: from on-boarding to monitoring
Let’s take the case of the building block dedicated to trust… such trust is built from the moment of onboarding, materializes when transferring the data and is confirmed by checking the monitoring and auditing capabilities of the data space.
Even a “simple” demonstration of two IDS connectors using the open-source GUI can provide companies with valuable insights into the operational level of a data space. This demonstration starts with two empty connectors and showcases the process of defining the data offering, including the price of the data, the usage policies and specifying how to get the data from the internal company resources. By demonstrating how the consumer connector finds the data offered and how the data is transferred from one connector to the other, companies gain a clear perspective of the whole process, enabling them to understand the data space operational level.
After seeing the demo, most companies start making comments, asking questions and thinking about why a data space is worth participating in and how the data space concept can be the foundation for new business models around data sharing.
Beyond the journey: preparing for data space engagement
However, these steps are only a small part of the overall journey. Companies need to understand that the journey begins long before they begin the process of engaging in a data space. The journey starts when the company begins to manage data like any other company asset.
Thus, a hotel knows perfectly how many rooms it has, their characteristics and how they relate to the quality perceived by the client, their price, the maintenance and cleaning processes, etc.
However, most companies do not manage their data in the same way, there is no comprehensive management of data including the processes needed to maintain data clean, up to date and ready to be shared. Even the definition of “quality” data is not clear. Unfortunately, most data spaces initiatives do not take into consideration this first step.
Explaining data spaces: creating a common ground for discussion
In summary, it is a necessity to evangelize companies about the operational dimension of data spaces so that they can better appreciate their potential. If we want the concept of data space to materialize in distributed data sharing environments, in which different companies, SMEs, large companies, public administrations and even individuals supply and consume data and services around this data with confidence, security and sovereignty we should start by finding a way to explain to companies what data spaces are and what they are for.
The participant journey is a very illustrative way of capturing the life cycle of a data space and has proven to be a good starting point to create a common ground for discussion and co-creation with companies.