Glossary
BIM Building Information Modeling (BIM)
A structured and standardised approach to managing information throughout the lifecycle of a built asset by using its shared digital representation to facilitate design, construction and operational processes and to form a data-driven basis for project decision-making.
Source:
What is Building Information Modelling?
Citizen Science
The essence of Citizen Science is that citizens participate in a scientific project. An obvious example of Citizen Science involves involving citizens in the collection of data that cannot easily be generated in a lab.
Source:
Citizen Science, what is it and why? — Open Science
CityGML
Standardized conceptual model and exchange format for representation, storage and exchange of virtual 3D city models.
CityGML standard facilitates the integration of urban geodata for a variety of applications for Smart Cities and Urban Digital Twins, including urban and landscape planning; Building Information Modeling (BIM); mobile telecommunication; disaster management; 3D cadastre; tourism; vehicle & pedestrian navigation; autonomous driving and driving assistance; facility management, and; energy, traffic and environmental simulations.
Source:
CityGML Standard | OGC Publications
Read more:
Basic Information - CityGML Wiki
OGC City Geography Markup Language (CityGML) 3.0 Conceptual Model Users Guide
Data Driven Decision-making (DDDM)
Alias: Evidence Based Decision Making, Evidence Informed Decision Making
An approach that puts emphasis on using facts, data and metrics to make desicions, rather than intuition or observation alone.
Most cited:
Data Science and its Relationship to Big Data and Data-Driven Decision Making | Big Data
Data ethics decision aid (DEDA)
A tool developed by the Utrecht Data School (University of Utrecht) and the City of Utrecht. It supports data analists, project managers and policymakers to recognize and approach ethical issues in data projects, management and governance.
Source:
Utrecht Data School, 2022. Data Ethics Decision Aid (DEDA) Handbook: Assessing ethical issues with regard to governmental data projects.
Read more:
De Ethische Data Assistent (DEDA) | Data School
Definition of Done (DoD)
The “Definition of Done” is a term that is mainly used in agile project management methods like scrum. It describes the set of criteria defined by the team that a product increment must meet to be considered complete and ready for customers.`
Source: What is a Definition of Done? | Scrum.org
Data provenance
Data provenance defines the, origin, history, and processing steps of geospatial data, ensuring transparency, trustworthiness, and reproducibility in distributed environments. It leverages standards like W3C PROV to track data transformations, supporting FAIR principles and enhancing reliability in AI-driven, automated workflows. Data provenance appeared to be relevant for trustworthiness and audits.
As part of a smart city project, the origin of all data used is documented: for example, traffic flow data comes from sensors from company X, was collected on date xy, and adjusted on date xx. This data origin is important for making planning decisions transparent and building trust. It can be found in well-documented work in the metadata.
Digital Twin Situation
An approach defined by Twin4Resilience partners, as basis for the training modules. In this case, a 'situation' is as a set of circumstances in which one finds oneself with the Digital Twin initiative, the state of affairs, the location, and the surroundings of that place.
European Qualifications Framework (EQF)
A common reference framework which assits in comparing national qualifications systems, frameworks and their levels. It makes qualifications more readable and understandable across different countries and systems in Europe.
Read more:
The European Qualifications Framework (EQF) | Europass
FAIR Data Principles
A set of principles that aim to maximize the use of data and other digital objects such as code and software. Their aim is to facilitate, enocurage and guide researchers towards making their data easily findable, accessible, interoperable and reusable.
Source:
Wilkinson, M., Dumontier, M., Aalbersberg, I. et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data 3, 160018 (2016).
The FAIR Guiding Principles for scientific data management and stewardship | Scientific Data
Read more:
FAIR Principles - GO FAIR
The FAIR principles - Research Data Management Support - Utrecht University
Federated data model
Alias: European Data Spaces
Data model that integrates data from distributed sources without storing it centrally – this is important for data protection and scalability.
The city administration does not operate a central data storage facility, but uses a federated data model in which, for example, traffic data remains with the traffic authority, energy data with the municipal utility company, and environmental data with the environmental agency. The digital twin accesses these distributed sources live without copying them.
Freedom of Information (FOI)
The Freedom of Information Act provides people the right to request access to records from any federal agency. It is often described as the law that keeps citizens in the know about their government.
Source:
FOIA.gov - Freedom of Information Act
General Data Protection Regulation (GDPR)
The General Data Protection Regulation (GDPR) is the toughest privacy and security law in the world. Though it was drafted and passed by the European Union (EU), it imposes obligations onto organizations anywhere, so long as they target or collect data related to people in the EU.
Source:
What is GDPR, the EU’s new data protection law? - GDPR.eu
Geographic Information System (GIS)
A system that is used to create, manage, analyze, and map all types of data.
GIS connects data to a map, integrating location data (where things are) with all types of descriptive information (what things are like there). This provides a foundation for mapping and analysis that is used in science and almost every industry. GIS helps users understand patterns, relationships, and geographic context. The benefits include improved communication, efficiency, management, and decision-making.
Source:
What is GIS? | Geographic Information System Mapping Technology
Geospatial analytics
Analysis of geographically referenced data, e.g., to identify spatial patterns in cities.
Geospatial analyses can be used for a number of applications, eg, to identify heat islands in a city district by analyzing data on soil sealing, vegetation, and surface temperatures. Urban planners use these findings to plan targeted greening measures (e.g., city trees, green roofs).
These terms of service ("Terms", "Agreement") are an agreement between the website ("Website operator", "us", "we" or "our") and you ("User", "you" or "your"). This Agreement sets forth the general terms and conditions of your use of this website and any of its products or services (collectively, "Website" or "Services").
These terms of service ("Terms", "Agreement") are an agreement between the website ("Website operator", "us", "we" or "our") and you ("User", "you" or "your"). This Agreement sets forth the general terms and conditions of your use of this website and any of its products or services (collectively, "Website" or "Services").
These terms of service ("Terms", "Agreement") are an agreement between the website ("Website operator", "us", "we" or "our") and you ("User", "you" or "your"). This Agreement sets forth the general terms and conditions of your use of this website and any of its products or services (collectively, "Website" or "Services").
Local Digital Twin
An LDT is a virtual representation of the physical assets, processes, and urban intelligence within a geographically located community, which reflect and derive from cross-sectorial, historical, and (near) real-time data. It aims to enhance evidence-informed decision-making according to ethical standards and principles at the operational, strategic, and tactical levels to better meet communities’ needs. LDTs support predictive simulation modelling, combining multiple technologies offering open and interoperable components, allowing integration with legacy systems and other components in a federated architecture.
Source:
Introduction: Defining Local Digital Twins | Springer Nature Link
Milestone
A milestone is an event of particular importance in project management. Milestones divide the project process into stages with verifiable intermediate goals, thus facilitating both project planning and monitoring progress.
Minimal Interoperability Mechanisms (MIMs)
The minimal interoperability mechanisms (MIMs) enable a minimal but sufficient level of interoperability for data, systems and services specifically in the context of smart city solutions. A MIM provides easy-to-use solutions, both technical and non-technical.
Source:
MIMs - Open & Agile Smart Cities & Communities
Minimum Viable Product (MVP)
Simplest version of a product that allows teams to validate ideas and gather feedback with minimal effort.
Source:
Minimum viable product (MVP): What is it & how to start | Atlassian
Read more:
MVP (Minimum Viable Product): From Concept to Reality - isixsigma.com
Minimum Viable Product Requirements: Complete Development Guide - TechEnhance
Ontology
Ontology is the philosophical study of being. It is traditionally understood as the subdiscipline of metaphysics focused on the most general features of reality. Ontology in data science is a formal, structured framework that defines the concepts, relationships, properties, and rules within a specific domain to make data understandable by machines and humans. It provides a semantic layer for data integration, improves data quality, supports automated reasoning, and facilitates interoperability across diverse systems.
A city administration creates an ontology for urban infrastructure that defines what, for example, a “green space,” a “traffic area,” or a “supply network” is and how these relate to each other. This ontology is used in a digital twin to link data from different departments (e.g., environment, transportation, energy) and evaluate it consistently.
Semantic interoperability
Semantic interoperability is the ability of computer systems to exchange data with unambiguous, shared meaning. Semantic interoperability is a requirement for enabling machine-computable logic, inference, knowledge discovery, and data federation across information systems. Semantic interoperability is therefore concerned not just with the packaging of data (syntax), but the simultaneous transmission of the meaning with the data (semantics). This is accomplished by adding data about the data (metadata), linking each data element to a controlled, shared vocabulary.
In an urban transport project, the transport companies, the building authority, and an external service provider use different software systems. Thanks to semantic interoperability, all parties can exchange information on “bus stops,” even though one system uses the term “stop,” another uses “public transport hub,” and a third uses “public transport stop”-because they all have the same meaning.
These terms of service ("Terms", "Agreement") are an agreement between the website ("Website operator", "us", "we" or "our") and you ("User", "you" or "your"). This Agreement sets forth the general terms and conditions of your use of this website and any of its products or services (collectively, "Website" or "Services").
LDT Usecase
An LDT use case describes a specific application scenario for a Local Digital Twin where digital representations of real urban infrastructures or processes are used to support data-driven decision-making.
User Centric Design (UCD)
Alias: User-Driven Development (UDD)
A design approach that puts the needs and desires of users at the centre, in each phase of the design process. Users are involved throughout this process, with the goal to create usable and accessible products or tools.