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  • sosa - Sensor, Observation, Sample, and Actuator (SOSA) Ontology
    http://www.w3.org/ns/sosa/
    This ontology is based on the SSN Ontology by the W3C Semantic Sensor Networks Incubator Group (SSN-XG), together with considerations from the W3C/OGC Spatial Data on the Web Working Group. @en
  • caso - Context Aware System Observation Ontology
    http://www.w3id.org/def/caso#
    CASO (Context Aware System Observation) is an ontology for context aware system and observation services. Its goal is to describe all the processing of the context. @en
  • atts - Air Traffic Temporal and Spacial Vocabulary
    https://data.nasa.gov/ontologies/atmonto/general#
    Defines temporal / spatial concepts and general-purpose datastructures @en
  • glc - GLACIATION Metadata Reference Model
    https://glaciation-project.eu/MetadataReferenceModel
    The GLACIATION platform develops a novel Distributed Knowledge Graph (DKG) that stretches across the edge-core-cloud architecture to reduce energy consumption, improving data processing and optimizing data movement operations. Towards this aim, the platform needs to consume the data and metadata that are fed into the DKG. The metadata can affect and inform the decision-making processes in the GLACIATION architecture and introduces the GLACIATION Metadata Reference Model that will be used for modelling the metadata in the DKG. The GLACIATION Reference Metadata Model makes data ingestion and processing interoperable inside the GLACIATION platform. Linked Data allows for a high level of flexibility and to tackle the variety and merging issues that emerge in heterogenous environments, especially due to the wide range of sensors and other data sources that the platform may integrate. The GLACIATION Reference Metadata Model is tailored to fit the specific purposes of the GLACIATION platform, while the GLACIATION use cases define the scope of the model for better interoperability. There are common metadata challenges for all use cases. This stems from the use of the Kubernetes orchestration system as a basis for the GLACIATION platform. In addition, common to the platform is the ingestion of data from other sources into the DKG that can then be used to affect processing decisions. There are direct data flows from sensors within the system, but also data and metadata from sources external to the system. This allows the system to react e.g. to environmental situations like weather or temperature, but also to requirements concerning security or privacy. Exemplary uses and specializations of the reference model to the GLACIATION use cases are also provided. The GLACIATION Metadata Reference Model can be used for scheduling and performing tasks. The model can be considered as a general conceptualization of a tasks scheduling problem that considers various measuring indicators over the deployed resources. It captures the assignment of time-constrained tasks to time constrained and energy consuming resources, that can satisfy various hard and soft constraints, even compositions of such constraints. The tasks can be monitored through various measuring resources using a variety of single or aggregated, predicted or real measurements. The model is generic, by being both domain and application independent, describing the scheduling tasks, without providing specific solutions on how they can be solved. It can be easily adjusted to each of the current three GLACIATION use cases, covering also the Kubernetes orchestration and its Telemetry System deployed by the project. The proposed model makes it feasible to answer the competency queries defined by each of the Glaciation's use case. @en
  • istex - Istex ontology for scholarly documents and extracted entities
    https://data.istex.fr/ontology/istex#
    ISTEX is a platform that aims to provide the entire French higher education and research community with an online access to retrospective collections of scientific literature in all disciplines. This unparalleled reservoir of multidisciplinary resources is complemented by a significant number of value-added services that can be used to optimise operations through content discovery and interactive valuation tools. @en
  • rma - Verisav RMA / Ticketing Vocabulary
    https://ns.verisav.fr/rma#
    Vocabulary for Return Merchandise Authorization (RMA) and service ticket management, standardizing communication between consumers, retailers, and repairers. @en
  • dpp - Verisav Digital Product Passport Vocabulary
    https://ns.verisav.fr/dpp#
    Vocabulary for Digital Product Passports (DPP) managing product lifecycle, warranties, repairs, and compliance with EU regulations (ESPR EU 2024/1781). Aligned with GS1 Digital Link standards, including GTIN, GLN, granularity (model/batch/serial) and compound identifier support. @en
  • tresiot - Ontology for Trust Recommendation in Social Internet of Things
    https://liidr.org/trust-recommendation-in-social-internet-of-things/
    This ontology models trust recommendation concepts in SIoT to bridge the gap between abstract trust concepts and real-world device concepts. @en
  • eqp - Aircraft Equipment Vocabulary
    https://data.nasa.gov/ontologies/atmonto/equipment#
    Defines aircraft models, aircraft systems / subsystems, and aircraft characteristics @en
  • atd - Air Traffic Data
    https://data.nasa.gov/ontologies/atmonto/data#
    Defines concepts related to airport status, including weather, forecasts, and airport operations @en
  • ci - A Content Inventory Vocabulary
    https://privatealpha.com/ontology/content-inventory/1#
    This vocabulary defines a number of concepts peculiar to content strategy which are not accounted for by other vocabularies. @en
  • wty - Verisav Warranty & Contracts Vocabulary
    https://ns.verisav.fr/wty#
    Vocabulary for machine-readable warranties and contracts, enabling complete automation of payment decisions and coverage assessment in after-sales service. @en
  • psn - Product Supply Network Vocabulary
    https://purl.org/psn/vocab#
    A small ontology to model supply networks (supply chains) from all industries through products that are interlinked based on derivational dependencies. @en
  • vas - VAS. A Semantic Model for Earth Observation Remote Sensing
    https://robotica.uv.es/proyectos/ASOTVAS/def/ciencia-tecnologia/vas
    The VAS ontological model enables the semantic integration of the heterogeneous observations used in ASOTVAS project ( https://robotica.uv.es/proyectos/ASOTVAS/ ), including ground measurements, UAV acquisitions and satellite products. Built as an extension of the W3C SOSA ontology (Janowicz et al., 2018), it incorporates a domain-specific vocabulary tailored to the needs of the Valencia Anchor Station as a CEOS LPV supersite. The model provides additional classes and properties to represent, in a homogeneous way, the different observational platforms: field sensors installed at VAS stations, UAVs equipped with multispectral cameras, and satellite missions such as Sentinel-2 and Sentinel-3. All observations follow a common SOSA pattern and share the same structure for results, units and timestamps. By aligning field, UAV and satellite observations under a unified semantic framework, the VAS ontology supports interoperable data access, consistent representation across scales, and integrated analysis of the multi-source measurements collected in ASOTVAS. @en
  • saref - SAREF: the Smart Appliances REFerence ontology
    https://saref.etsi.org/core/
    The Smart Appliances REFerence (SAREF) ontology is a shared model of consensus that facilitates the matching of existing assets (standards/protocols/datamodels/etc.) in the smart appliances domain. The SAREF ontology provides building blocks that allow separation and recombination of different parts of the ontology depending on specific needs. @en