924
results
-
The Construction Tasks Ontology (CTO) describes tasks operating on construction elements, spatial zones and/or damages. The tasks are either planned or executed depending on the dataset metadata context of the dataset its used in. Five different types of tasks are defined: instalment, removal, modification, repair and inspection. Consequences of tasks on the dataset, i.e. added and/or deleted triples, are modeled using reified statements. The tasks can link to a reified statement using the CTO relations. @en
-
Simple ontology for Cloud Computing Services. This ontology allows to define model of prices used in large cloud computing providers such as Google, Amazon, Azure, etc., including options for regions, type of instances, prices specification, etc. @en
-
The Building Concrete Monitoring Ontology (BCOM) is defined for capturing information of concrete work, concrete curing and testing of concrete properties. Further Information on the development and usage of the Ontology can be found in the following publication: Liu et al. (2021): An ontology integrating as-built information for infrastructure asset management using BIM and semantic web. In: Proceedings of 2021 European Conference on Computing in Construction, Online eConference, URL: https://ec-3.org/publications/conferences/2021/paper/?id=167 @en
-
The module Location models information related to the localization and georeferencing of a cultural property. In this module are used as template the following Ontology Design Patterns: - http://www.ontologydesignpatterns.org/cp/owl/collectionentity.owl - http://www.ontologydesignpatterns.org/cp/owl/classification.owl - http://www.ontologydesignpatterns.org/cp/owl/place.owl - http://www.ontologydesignpatterns.org/cp/owl/timeindexedsituation.owl - http://www.ontologydesignpatterns.org/cp/owl/situation.owl @en
-
domOS Common Ontology (dCO) represents a common information model to share a unified understanding for humans and machines and to ensure semantic interoperability in a heterogeneous IoT infrastructure. This ontology allows the decoupling of the infrastructure from the software services and applications. @en
-
Ontology that defines the topology of damages in constructions. @en
-
The Data Privacy Vocabulary (DPV) provides terms (classes and properties) to represent information about processing of personal data, for example - purposes, processing operations, personal data, technical and organisational measures. @en
-
The scope of the DIO is the domain of design intent or design rationale that needs to be documented while undertaking the design of any artifact @en
-
Digital Twin ontology used to define Digital Twins and Semantic Digital Twins and aggregations by dimensions using Web of Things. @en
-
To ensure comparability between schemas from different data models, the Description of a Data Source (DSD) vocabulary has been developed. @en
-
The DINGO ontology (Data Integration for Grant Ontology) defines the terms of the DINGO vocabulary and provides a machine readable extensible framework to model data relative to projects, funding, project and funding actors, and, notably, funding policies. It is designed to yield high modeling power and elasticity to cope with the huge variety in funding and project practices, which makes it applicable to many areas where funding is an important aspect: first of all research, but also the arts, cultural conservation, and many others. @en
-
Extension to the Data Privacy Vocabulary (DPV) providing additional categories of personal data @en
-
An ontology that represents concepts in the legal domain. @en
-
This ontology describes wildlife observations generated by sensors. @en
-
An ontology for describing changes between OWL ontology versions @en