Glossary

The M2M ecosystem considers the stakeholders and their interactions within the M2M value chain, such as M2M module producers, communication service providers like mobile network operators, software vendors, M2M module integrators, data center operators, as well as providers of M2M products and services.

This refers to a rarely used expression that can be found predominantly in English-language articles and specialized publications. For example, phrases like "M2M is the plumbing of the Internet of Things" or "M2M is often referred to as 'plumbing', while the IoT is seen as a universal enabler" make use of this expression.

Electronic services utilizing M2M components are services that facilitate remote operations, including activities such as remotely accessing meter readings, controlling temperatures, or managing window blinds from a distance, usually through internet connectivity.

The term "machine data" refers to digital information that is generated by computers, mobile phones, embedded systems, and other devices connected to a network. This type of data has become increasingly common with the advancement of technologies like radio frequency identification (RFID) and telematics. Moreover, the rise of the Internet of Things (IoT), Hadoop, and other big data management technologies has further emphasized the importance of machine data.

Machine learning is a branch of artificial intelligence that focuses on enhancing statistical models by utilizing past data. This improvement process, known as training, is facilitated by a learning algorithm. Once the model has been trained, it can be utilized to address the same kind of tasks that were covered by the training data. As a result, machine learning offers a substitute for explicit coding of a function.

Distributed machine learning is a technique used when it is not desirable to transmit local data to a central server for the purpose of machine learning. This approach enables local nodes to train models locally and then periodically send the models to the central server. Once there, the models are combined and then redistributed to the local nodes for further use.

Machine-generated data (MGD) refers to information generated by mechanical or digital devices. It commonly encompasses data produced by an organization's industrial control systems and mechanical devices specifically designed for performing a singular function.

This pertains to the exchange of information among machines, such as between control units that manage business or operational processes, and sensors or actuators.

The fairs, originally initiated by the magazine Make, serve the purpose of presenting diverse projects in the fields of art, crafts, science, and technology. They promote the concept of do-it-yourself and foster enthusiasm for creative endeavors.

Managed C# is a programming language supported by Microsoft that builds on the C# syntax and is used to develop applications under the .NET Framework platform.

A Managed Service refers to a software offering that is provided and maintained by a third-party provider. This can include a variety of services such as AWS EC2, Azure SQL Database, and GCP Pub/Sub, as well as other software offerings that can be utilized by an application.

An MSP, or managed service provider, offers various network, system, application, and e-management services to numerous enterprises through a network, using a pricing model where customers pay only for what they use. A "pure play" MSP concentrates primarily on providing management services. The MSP industry also encompasses services from other providers, such as ASPs (application service providers), web hosting companies, and NSPs (network service providers), who supplement their standard services with management services.

One of the three levels of interoperability within Gaia-X is the Federated level, which is an extension of the common digital governance provided by the Federators of the relevant ecosystems. This level does not cover specific ecosystem governance rules as they are considered out of scope for Gaia-X.

A Kubernetes manifest is a description of a Kubernetes API object in YAML or JSON format that specifies the desired state of the object. When a manifest is applied to a Kubernetes cluster, Kubernetes will ensure that the actual state of the object matches the desired state specified in the manifest. A single configuration file can contain multiple manifests for different Kubernetes objects.

Manufacturing as a Service (MaaS) refers to the use of networked manufacturing infrastructures for producing goods on-demand. The customer initiates the production of goods by the manufacturing companies through MaaS, and the order assignment is fully automated. This allows the customer to avoid spending significant amounts of time searching for suitable suppliers with the right skills and capacities. Instead, they can use an efficient algorithm that selects the best possible supplier based on certain factors. MaaS also benefits suppliers by allowing them to focus on their core manufacturing business while handing over the administrative work of customer acquisition and order processing to MaaS. For more information, please refer to the team landing page on Manufacturing as a Service (MaaS).

Catena-X Automotive Network e.V.

The manufacturing bill of materials is a product of the planning process, which includes auxiliary materials. It is a comprehensive list of all required parts and their respective quantities needed for the production of a product or assembly. However, due to site-specific manufacturing variations, the list may differ slightly within the eBOM specifications for each site.

Catena-X Automotive Network e.V.

A multi-layer manufacturing management system includes different layers, one of which operates close to the process.

Data mapping refers to connecting fields from different databases. It forms the fundamental step for successful data migration, data integration and other data management tasks.

Mapping, also known as matching, involves aligning the semantics and attributes of capabilities with skills. This is done by comparing the requirements of the product or customer (i.e., capabilities) with the capabilities of the machine or service provider (i.e., skills). Mapping can be done at different levels of detail, and the result is a list of modules that either fit or do not fit. This list can then be further filtered and prioritized based on additional criteria, such as which modules fit best, are most cost-efficient, or offer the best quality.

Catena-X Automotive Network e.V.

The term "Batch Processing" refers to the automatic, sequential, and complete execution of data contained in input files. The program runs independently, without user intervention, after being initiated. The data to be processed is handled one by one. The results can be stored, for example, in files or databases. Apache Hadoop MapReduce is a common example of batch processing in Big Data.

An intermediary in a data space offering features like catalogues and online transaction tools (e.g., ordering, billing, payment) for data product trading.

On the Internet, the term "Mashup" describes the creation of new content by integrating and processing existing content. Originally, the term comes from music. There are various software technologies for this kind of creative work.

MOOCs are online courses that have a theoretically unlimited number of participants. They use a combination of traditional knowledge delivery methods such as videos and reading materials, as well as interactive forums where instructors and learners can collaborate and build communities.

Massively parallel processing (MPP) refers to the simultaneous execution of a program by numerous processors that operate on different portions of the program, each using its own memory and operating system.

The term "Master" was used in the past as a synonym for nodes that hosted the Kubernetes control plane components. Although it is a legacy term, some provisioning tools such as kubeadm and managed services still use it to label nodes with kubernetes.io/role to control the placement of control plane pods.

Refers to the MDM (Mobility Data Marketplace) project of the BAST (Federal Highway Research Institute).

Mean Time Between Failures (MTBF) describes the expected amount of time a system, facility, or system component can spend in normal operation before a failure occurs.

A unique hardware address, also known as a MAC address, is assigned to each network adapter and allows for the identification of every device in a computer network.

A central data hub or marketplace for sensor data from various medical applications enables the integration and improved availability of information.

The transmission speed is specified in MBit/s, which stands for millions of bits per second.