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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
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semiotics- A content ontology pattern that encodes a basic semiotic theory, by reusing the situation pattern.A content ontology pattern that encodes a basic semiotic theory, by reusing the situation pattern. The basic classes are: Expression, Meaning, Reference (the semiotic triangle), LinguisticAct (for the pragmatics), and Agent. A linguistic act is said to be context for expressions, with their meanings and references, and agents involved. Based on this pattern, several specific linguistic acts, such as 'tagging', 'translating', 'defining', 'formalizing', etc. can be defined, so constituting a formal vocabulary for a pragmatic web. @en
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The nanopub ontology @en
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pimsii- Physicalistic Interpretation of Modelling and Simulation - Interoperability Infrastructure (PIMS-II)The Physicalistic Interpretation of Modelling and Simulation - Interoperability Infrastructure (PIMS-II) is a mid-level ontology with a focus on documenting cognitive processes and epistemic metadata @en
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Creative Commons Ontology, extending RDF file at http://creativecommons.org/schema.rdf @en
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A set of annotation properties to be used for ontology design patterns @en
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An RDF vocabulary for relating SW vocabulary terms to their status. @en
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This is (the start of) an event-based model of the W3C process; e.g. RECdd is the class of Recommendation Director's Decisions; i.e. messages to w3c-ac-members announcing a new W3C Recommendation. @en
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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
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This ontology was used as example in the first OWL Recommendation (February 2004) @en
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Along with Wine Ontology, was used as example in the first OWL Recommendation (February 2004) @en
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This vocabulary is for describing relationships between standards/specifications, profiles of them and supporting artifacts such as validating resources. This model starts with [http://dublincore.org/2012/06/14/dcterms#Standard](dct:Standard) entities which can either be Base Specifications (a standard not profiling any other Standard) or Profiles (Standards which do profile others). Base Specifications or Profiles can have Resource Descriptors associated with them that defines implementing rules for the it. Resource Descriptors must indicate the role they play (to guide, to validate etc.) and the formalism they adhere to (dct:format) to allow for content negotiation. A vocabulary of Resource Roles are provided alongside this vocabulary but that list is extensible. @en
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The Open Digital Rights Language (ODRL) provides flexible and interoperable mechanisms to support transparent and innovative use of digital content in publishing, distribution, and consumption of of digital media across all sectors and communities. The ODRL Policy model is broad enough to support traditional rights expressions for commercial transaction, open access expressions for publicly distributed content, and privacy expressions for social media. @en
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RADion, and the higher level vocabularies that build upon it, are intended as a model that facilitates federation and co-operation. It is not the primary intention that repository owners redesign or convert their current systems and data to conform to RADion, but rather that it acts as a common layer among repositories that want to exchange data. @en
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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