Glossary

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In the context of the data economy and the Gaia-X ecosystem, some terms appear that are either not precisely defined or can have multiple meanings. Therefore, you will find an explanation of some important terms in the following list.

Brief explanation of some important terms

Artificial Intelligence (AI)

Research field where human thinking and learning are imparted onto machines, aiming to grant them intelligence. The term is often used synonymously with or as a generic term for processes of machine learning. Our white paper “AI and Gaia‑X” provides an overview of AI in the Gaia‑X context and projects that deal with this technology in more detail.

Cloud Computing

In this model, computing power, services or storage are distributed across several computers, servers or data centers and billed according to their usage. This means that users or companies do not have to maintain the corresponding capacities themselves, but can flexibly access scalable resources.

Data Economy

This term revolves around the economic benefit, as well as the commercialization and monetization of data, a trend that is gaining momentum through the evolution of new data-driven business models. Gaia-X plays a crucial role in enabling a secure and convenient utilization of the data.

Data Space

A federated, open infrastructure for sovereign data sharing, based on common agreements, rules, and standards. Find out more in our white paper “What is a Data Space“?

Data Trustee

Independent, neutral entity that transmits data between a provider and a user in a trustworthy and legally compliant manner. You can find a detailed explanation of the concept in our publication "Data trusts, data intermediation services and Gaia-X"

Digital Sovereignty

Ability to make well-considered decisions about digital processes, infrastructures, and data exchange.

Digital Twin

Virtual representation or simulation of a product, component, or process, based on real data such as from sensors.

Domains

Working groups within the national hubs that usually represent a certain industry and analyse its specific requirements or use cases when implementing Gaia-X.

Edge Computing

In contrast to Cloud Computing, data processing and storing in this model is not carried out via central nodes, but decentral at the edge of a network. It is particularly used for applications that require real-time data processing, e.g., face recognition in smartphones.

Federated Catalogue

This Gaia-X Federation Service enables users to search and choose providers or services in the Gaia-X ecosystem. Basically, data is annotated with descriptions, enabling targeted searches on specific use cases.

Federated Learning

This term refers to a specific technique of machine learning. In contrast to the usual procedure, a model is not trained on one sole data set, but on several devices with differing data.

Federated Systems

Coalition of individual systems that maintain their respective independence.

Gaia-X European Association of Data and Cloud

In 2019, the Gaia-X Association was founded as a non-profit association in Brussels (french: association sans but lucrative). It develops the technical framework and operates the Gaia-X Federation Services.

Hub

The national Gaia-X Hubs act independently and serve as first point of contact for those interested in Gaia-X in the respective countries.

Hyperscalers

Providers of IT resources for deploying cloud computing solutions that are highly scalable, allowing their performance or capacity to be flexibly increased. Notable hyperscalers include AWS (Amazon Web Services), Alphabet (Google) and Microsoft (Azure).

Industry 4.0

Intelligent interconnection of machines and processes in the manufacturing industry using information and communication technology. For more information, visit the page on our domain Industry 4.0.

Internet of Things (IoT)

On the Internet of Things, everyday devices or industrial equipment is interconnected via the internet and can interact with each other or with humans. This technology and the communication between machines are the necessary precondition for Industry 4.0, e.g., the full automation of industrial processes.

Interoperability

Possibility to link and coordinate devices or systems with each other, through the same technical standard and interfaces.

Machine Learning

Using algorithms and static models, a machine develops a sophisticated model based on training data and discerns patterns that allow classifications and predications. This technology is already employed in everyday applications such as spam filters in email clients or translation programs.

Self Sovereign Identity (SSI)

Approach for digital identities with a focus on the user: The users regain the full control of their personal digital identity and can manage it from a digital device of their choice, such as a smartphone, without relying on a central identity provider. As a result, individuals can authenticate themselves, e.g., for renting a car or checking into a hotel, using a simple QR code on their smartphone, eliminating the need to inconveniently present and store documents like ID cards or driver’s licenses.

Use Case

Gaia-X is developing standards for a secure, transparent, and sovereign data exchange. Through the illustration of so-called use cases (practical application scenarios), it demonstrates the practical solutions that can be implemented across various industries. The Gaia-X Association lists a comprehensive collection of use cases on its website.