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  • lexinfo - LexInfo Ontology
    http://www.lexinfo.net/ontology/2.0/lexinfo
    Version 2.0 of LexInfo Ontology, based on Lemon @en
  • mads - Metadata Authority Description Schema
    http://www.loc.gov/mads/rdf/v1
    MADS/RDF (Metadata Authority Description Schema in RDF) is a knowledge organization system (KOS) designed for use with controlled values for names (personal, corporate, geographic, etc.), thesauri, taxonomies, subject heading systems, and other controlled value lists @en
  • tisc - Open Time and Space Core Vocabulary
    http://www.observedchange.com/tisc/ns#
    TISC, the Open Time and Space Core Vocabulary, is a lightweight spatiotemporal vocabulary aiming to provide spatial and temporal terms such as "happensAt", "locatedAt", "rightOf" to enable practitioners to relate their data to time and space. @en
  • lmm2 - Lexical MetaModel Level 2
    http://www.ontologydesignpatterns.org/ont/lmm/LMM_L2.owl
    An ontology for aligning existing linguistic ontologies, and for describing the research objects of NLP. @en
  • remetca - ReMetCa Ontology
    http://www.purl.org/net/remetca#
    Ontology for poetry description @en
  • tmo - Translational Medicine Ontology
    http://www.w3.org/2001/sw/hcls/ns/transmed/
    The Translational Medicine Ontology (TMO) is a high-level, patient-centric ontology that extends existing domain ontologies to integrate data across aspects of drug discovery and clinical practice. The ontology has been developed by participants in the World Wide Web Consortium's Semantic Web for Health Care and Life Sciences Interest Group @en
  • vs - SemWeb Vocab Status ontology
    http://www.w3.org/2003/06/sw-vocab-status/ns
    An RDF vocabulary for relating SW vocabulary terms to their status. @en
  • adms - Asset Description Metadata Schema
    http://www.w3.org/ns/adms
    ADMS is a profile of DCAT, used to describe semantic assets (or just 'Assets'), defined as highly reusable metadata (e.g. xml schemata, generic data models) and reference data (e.g. code lists, taxonomies, dictionaries, vocabularies) that are used for eGovernment system development. @en
  • acl - Basic Access Control ontology
    http://www.w3.org/ns/auth/acl
    Defines the element of Authorization and its essential properties, and also some classes of access such as read and write. @en
  • vartrans - Lexicon Model for Ontologies - Vartrans
    http://www.w3.org/ns/lemon/vartrans
    A model for the representation of lexical information relative to ontologies. Variation and translation module. @en
  • rr - RDB to RDF Mapping Language Schema
    http://www.w3.org/ns/r2rml#
    A vocabulary which can be used to specify a mapping of relational data to RDF. @en
  • rov - Registered Organization Vocabulary
    http://www.w3.org/ns/regorg
    The Registered Organization Vocabulary is a profile of the Organization Ontology for describing organizations that have gained legal entity status through a formal registration process, typically in a national or regional register. @en
  • mls - Machine Learning Schema
    http://www.w3.org/ns/mls
    ML-Schema is a collaborative, community effort with a mission to develop, maintain, and promote standard schemas for data mining and machine learning algorithms, datasets, and experiments @en
  • 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
  • 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