Glossary

A sandbox is a self-contained testing environment that allows users to execute programs or access files without impacting the application, system, or platform in which they are operating.

The development stage where a data space initiative consistently attracts new participants and integrates new use cases, demonstrating financial and operational sustainability, and the ability to adapt and expand over time in response to market changes.

Schema on read is a progressive approach to data analysis employed by modern data management tools such as Hadoop and advanced database technologies. In schema on read, data is associated with a structure or schema during retrieval from a stored location, rather than during its initial storage. This stands in contrast to the traditional approach of schema on write, where data is structured and organized before it is stored.

In traditional business intelligence systems based on relational databases, it is necessary to define queries in advance before data is even stored. This process is referred to by technicians as "schema on write."

The Supply Chain Operation Reference (SCOR) is a comprehensive, cross-industry approach to establishing more efficient and effective information exchange within supply networks. SCORVoc is an OWL vocabulary that fully formalizes the latest SCOR standard and addresses any limitations identified in existing formalizations.

On the Service Control Platform (SCP), various standardized service stacks can be implemented. These services encompass different functions such as telephony, voice, desktop video and web conferencing, telepresence, instant messaging, or BYOD and mobility services. They can support a variety of front-end systems.

The capability of data search and discovery empowers users to find, understand, and trust the information essential for making informed decisions based on data. It plays a critical role in fostering a data-driven culture. Irrespective of the existence of data governance or the proficiency of employees in data literacy, ensuring the availability of the required data remains crucial.

Secrets are used to securely store confidential data such as passwords, OAuth tokens, and SSH keys in a Kubernetes cluster. By utilizing Secrets, you can exercise more control over how sensitive data is used and minimize the risk of accidental disclosure. By default, Secret values are encoded as base64 strings and stored unencrypted, but it's possible to configure Secrets to be encrypted when at rest. Pods can reference a Secret in various ways, including as an environment variable or a volume mount. It's worth noting that Secrets are intended for confidential data, while ConfigMaps are better suited for non-confidential data.

Reliable and verifiable representation of an individual's personal information in a digital format. It enables individuals to securely access online services, conduct financial transactions, and protect their personal data.

In contrast to e-mail, De-Mail enables both the unequivocal identification of the communication partners and the verifiable sending and receiving of De-Mails. The contents of De-Mails cannot be read or changed during transmission via the Internet, as secure logon procedures, encrypted connections and transport routes between De-Mail providers ensure confidential communication.

An outdated network protocol for secure data transmission that is no longer current. Since the introduction of SSL version 3.0, the protocol is referred to as TLS.

Security by Design (SBD) is the approach that integrates security requirements into the development phase of a product for software and hardware, in order to prevent security gaps from emerging in the later stages.

The Security Context field allows you to set privilege and access control configurations for a container or Pod in Kubernetes. This field allows you to specify parameters such as the user and group that processes should run as well as the privilege settings. Additionally, you can implement security policies such as SELinux, AppArmor, or seccomp. It's worth noting that the securityContext setting defined within PodSpec applies to all containers within the Pod.

Data in transit refers to any data that is currently being transmitted between components, devices, or systems. Using secure data exchange protocols, such as TLS (Transport Layer Security), helps ensure the confidentiality and integrity of the data while it is being transmitted.

Data Intelligence Hub

A specific collection of security properties for connectors is established that outlines various security aspects such as isolation level, attestation, and authentication. These properties express the minimum requirements that a Data Consumer must meet in order to access the exposed Data Endpoints.

Selectors in Kubernetes enable users to filter a list of resources based on their labels. By applying selectors, it's possible to retrieve a subset of resources from a larger set of resources that match specific label criteria. Selectors are utilized when querying lists of resources to filter them based on their associated labels.

In this context, self-service business intelligence refers to the ability of end users to independently create and implement their own analyses and reports using a set of approved tools and architecture provided and supported by the organization.

A metadata record used by providers to detail themselves, their data product offerings, and the elements and services that make up their data products.

The Self-Description Graph receives data from Self-Descriptions that have been identified by the Catalogue and are presently in an active state within their lifecycle.

Within Gaia-X, a schema refers to a comprehensive set of class data that encompasses shapes, ontologies, and controlled vocabularies. Shapes establish the criteria for validation, whereas ontologies outline the terminology and connections between them, forming the foundation for constructing claims. Controlled vocabularies make up a significant portion of the vocabulary and are more expansive and straightforward than the more intricate ontology, consisting of extensive collections of standard references and country codes.

The entities identified within Gaia-X are defined by the Self-Description Schema, which establishes an inheritance structure. Each entity inherits characteristics from a single entity in the Conceptual Model, resulting in an inheritance hierarchy known as the Self-Description Taxonomy.

Self-sovereign identity (SSI) enables individuals to locally manage and possess their digital identities and other verifiable digital credentials. The usage of a dominant cloud service provider is not mandatory, nor is the creation of a central Gaia-X Identity provider. This grants users complete autonomy from third parties, empowering them to determine which identity information to share with others. All identity data is kept securely in the user's SSI wallet, ensuring that it is exclusively accessible by the individual.predominant cloud service provider, nor is the establishment of a central Gaia-X Identity provider necessary. Users are thus completely independent of third parties and decide themselves which identity data they share with whom, as all identity data is securely stored only with the individual user in their SSI wallet.

Semantically described data refers to information that possesses a specific significance within a particular context. It comprises both data and the relevant contextual details.

A data organization technique that represents the fundamental meaning of data elements and their interconnections.

The semantic data model is a method of structuring data that includes semantic information that adds a basic meaning to the data and the relationships that lie between them.

Semantic models play a vital role in organizing data, providing a foundational understanding of data and its interconnections. In the context of data modeling and organization, semantic models facilitate the seamless development of applications and ensure data consistency. In the Catena-X framework, semantic data models are accessible through a well-suited publishing system called the Semantic Hub. For data and service providers, the Semantic Hub acts as a platform for leveraging and reusing semantic models. As a result, the publication of a semantic data model includes the specification of a version, enhancing transparency and enabling control over all semantic models and their release status.

The term refers to the ability to exchange data between organizations as part of seamless, integrated business processes. It uses an approach designed to avoid misunderstandings and erroneous interpretations in the use of terms, data structures, writing conventions, and so on. Semantic interoperability is crucial for efficient exchange of data within an organization as well as for efficient data integration with external cooperation partners.

Semi-structured data, also referred to as partially structured data, is a form of data that does not adhere to the rigid tabular structure commonly found in relational databases or other structured data tables. Instead, it incorporates tags and metadata to delineate semantic elements and establish hierarchies among records and fields.

Sentiment analysis (also known as opinion mining) is a natural language processing (NLP) technique used to determine whether data is positive, negative, or neutral. Sentiment analysis is often performed on text-based data to help businesses monitor brand and product sentiments in customer feedback and gain a better understanding of customer needs.

Interfaces with serial communication enable data exchange between computers and peripheral devices or components. These interfaces are characterized by the transmission of data in bit sequences. However, different synchronization methods between the sender and receiver, as well as access procedures to the transmission medium, are used. Furthermore, these interfaces differ in their application area: CAN, for example, was developed for automotive applications, while Ethernet is used for LAN applications.