EU LDT Toolbox glossary
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A visual interface that displays key information, metrics, and tools in one place, allowing users to monitor and manage their work efficiently.
An entity that retrieves or subscribes to data assets from the data space to derive value or insight.
A machine-readable agreement that defines the conditions under which data is shared or consumed within a data space.
The layer responsible for storing and managing all persistent application data, ensuring data integrity, managing relationships between entities, and providing efficient retrieval capabilities.
An EU LDT Toolbox tool that allows connecting to a city's databases and sensors. It provides access to real-time and historical data for simulations and analyses.
An EU LDT Tool that collects and organises data from different sources across cities and municipalities, making it easy to access for planning, monitoring, and visualising city services.
A functionality that allows querying data from multiple sources (files, databases, Kafka topics, APIs) using SQL as a unified query language.
A registered source of data in the platform, such as an IoT device, database, file storage, or external API.
The principle that data owners maintain control over their data, including access rights, usage policies, and revocation.
A federated infrastructure that enables sovereign, interoperable, and secure data exchange among participants, based on commonly agreed rules, standards, and governance models.
A secure data repository and exchange environment where maturity framework data and other assets can be sent for archival or integration with external systems. It supports interoperability and allows external stakeholders to access city progress data in a compliant format.
The originating location where data is stored or collected, serving as the point from which information is extracted, processed, or analysed.
A structured discussion space within a participatory process where citizens can share opinions.
The process of installing and running an application or service on a target infrastructure (e.g., Kubernetes cluster).
A software development approach that integrates development and operations teams to improve automation, speed, and reliability.
An export format that packages the data schema along with a Dockerfile and necessary dependencies. This allows the data generator to be deployed as a standalone container in any environment supporting Docker.