Pillars of a Data Space
Functionalities of a successful data space
Data-based decision-making will revolutionise the way mobility connects Europe. However, current technical, legal, and economic barriers prevent leveraging the vast amounts of mobility data generated every day. Through a series of engagement activities with industry experts from diverse stakeholder groups, PrepDSpace4Mobility has been analysing the necessary functionalities of the future common European mobility data space (EMDS). Clear frameworks for sharing and exchanging data have to be provided while ensuring compliance with laws and regulations and putting citizens and businesses in control over their information.
Currently, we are working on providing clear recommendations for each of the six pillars constituting a data space explained below.
The final results and visualisation of the these pillars and their building blocks for the EMDS will be available this September.
GOVERNANCE FRAMEWORK
Within a data space, a governance framework is needed to coordinate the necessary decisions and actions of the various participants and roles involved in the data space to achieve their goals and progress through the different lifecycle stages of the data space. The governance framework is the set of principles, standards, policies, and practices that define how a data space is governed and how decisions are made. It provides a structure for the management of the data space and outlines the roles, responsibilities and accountabilities of the various stakeholders. Governance in a data space is multi-layered and includes business and legal as well as technical and operational aspects.
BUSINESS MODELS
Data spaces represent a collaborative and federative approach to data sharing by creating a level playing field for data sharing. A data space as a trusted intermediary provides an alternative to legacy (platform-based) collaboration models and hyperscalers that is compliant with European values. As such, the business models of a data space should not only enable its participants to create, deliver and capture value through viable use cases, but also enable service providers to create and operate the data space environment in a financially sustainable manner. Various (mixed) public and private funding mechanisms are to be evaluated. Moreover, the business model of a data space is essentially multi-faceted, encompassing not only business and technical aspects but also legal and organisational elements.
LEGAL FRAMEWORK
Several legal issues affect the creation and operation of data spaces. It is important to ensure compliance with horizontal legislation (such as privacy, data protection, competition and intellectual property laws), whilst also complying with sector specific regulations (applicable to (sharing of) specific types of data for both mobility and logistics). Navigating the legal aspects of data governance can be challenging due to the complex mixture of national and EU legal entitlements to data, the ambitious European legislative agenda, and the intricate interplay between various regulatory instruments. Moreover, as data spaces often involve participants with different interests, contracts are also important in the legal framework of data spaces by setting out the terms and conditions for data sharing and cooperation between different participants.
DATA VALUE CREATION
When data is transformed into useful information, it can be utilised to make well-informed decisions, increase efficiency, and in general, generate economic, social, or environmental value. However, to be able to create value, participants in a data space must be able to discover and access data shared by others and enable the creation of multi-sided markets. This requires a common means of describing data services and data service offerings, as well as their associated terms and conditions (which may include pricing), facilitating the publication and discovery of such services, and ensuring accountability for contracts and data sharing transactions. Therefore, data value creation requires capabilities to describe, publish and discover offerings of data and services by means of catalogues such as currently similarly provided by National Access Points (NAPs) and marketplaces to acquire them and account of their usage.
DATA INTEROPERABILITY
In a data space, participants need to be able to share and exchange data in a standardised way, both within a specific area (e.g., between different stakeholders in traffic management), as well as across domains (e.g., mobility and tourism to improve traffic management in touristic areas). As such, data interoperability is essential as it enables data to be accessible across different formats and platforms. It allows a participant to maximise value from its data and overcome the significant challenges posed by proprietary data assets (company- or sector-specific formats). Data interoperability requires capabilities to enable semantic interoperability – the ability to exchange data with unambiguous, commonly agreed meaning – between participants in a data space. In practice this means enabling participants to specify their (domain specific and cross-domain) semantics, link them to (common) technical interfaces, and record which data was exchanged with whom.
DATA SOVEREIGNTY AND TRUST
Data sovereignty is the concept of retaining authority and control over one's data, allowing individuals or organisations to determine who can access their data and for what purposes. Trust, on the other hand, establishes confidence in the truthfulness and quality of received information, ensuring reliability and adherence to ethical standards. Data spaces should bring technical means for guaranteeing that participants in a data space can trust each other and exercise sovereignty over the data they share, e.g. by defining access and usage control policies and (both legally and technically) enforcing these. Moreover, ensuring trust in the data space means having assurance in the accuracy and integrity of the information. Data sovereignty and trust call for the adoption of common standards for managing the identity of participants and capabilities for the verification of their truthfulness. Further, it requires the definition of, agreement upon, and enforcement of data access and usage control conditions.