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      "_index": "lov",
      "_type": "vocabulary",
      "_id": "http://www.w3.org/2006/time",
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        "type": "vocabulary",
        "uri": "http://www.w3.org/2006/time",
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        "http://purl.org/dc/terms/title@en": "Time Ontology",
        "http://purl.org/dc/terms/description@en": "This vocabulary defines temporal entities such as time intervals, their properties and relationships.",
        "tags": [
          "Time"
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        "http://purl.org/dc/terms/title@en": "The Time Interval Pattern",
        "http://purl.org/dc/terms/description@en": "This pattern is extracted from DOLCE-UltraLite by partial clone of elements and expansion. Two datatype properties have been added which allow to express the boundaries of the time interval.",
        "tags": [
          "Time"
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        "http://purl.org/dc/terms/title@en": "Time Indexed Situation",
        "http://purl.org/dc/terms/description@en": "A generic pattern usable for all situations that require a temporal indexing.",
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        "http://purl.org/dc/terms/title@en": "The SEAS Time Ontology.",
        "http://purl.org/dc/terms/description@en": "This ontology defines:\n- a set of subclasses of `seas:Evaluation` to better interpret evaluations of quantifiable properties.\n- a set of sub properties of `seas:hasProperty` to qualify time-related properties.",
        "tags": [
          "Industry",
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        "http://purl.org/dc/terms/title@en": "Gouda Time Machine Ontology",
        "http://purl.org/dc/terms/description@en": "The Gouda Time Machine Ontology describes the geo-temporal classes and properties used within the Gouda Time Machine.",
        "tags": [
          "Geography",
          "Time"
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        "http://purl.org/dc/terms/title@en": "The Semantic Time Series Ontology",
        "http://purl.org/dc/terms/description@en": "SemTS is an ontology designed to identify and describe segments within time series data, which are specific data points or intervals that can overlap. These segments encompass characteristic knowledge about the time interval they cover, including common time series features, structural anomalies, motifs, or information provided by domain experts. By classifying and semantically representing this knowledge, SemTS promotes organized reusability and efficient propagation, potentially reducing resource expenditure while enhancing future analyses. It employs established semantic approaches. Examples are DCAT to reference associated time series data, OWL-Time to define the index structure of time series data and segments or ML-Schema to expand the expressiveness regarding data analysis task information. SemTS's design involves categorizing time series knowledge and mapping it to specific intervals and dimensions of time series data. It introduces a class called TimeSeriesSegment to model these segments, extending the DCAT Dataset class to enable segments to be part of other segments. This structure allows for the association of knowledge, such as anomalies, with particular intervals or data points. TimeIndex specifications extend OWL-Time classes, while dimensional details are represented by DataDimension. The segment-wise consideration of knowledge indirectly serves as an index structure, linking meaningful time series data with categorized knowledge. At the highest level of abstraction, time series knowledge is divided into three categories: DataKnowledge, ScenarioKnowledge, and MethodKnowledge. DataKnowledge refers to insights extracted directly from the data or through analytical methods, such as class membership from time series clustering. ScenarioKnowledge describes verified contexts, including data annotations or domain-specific process knowledge, often equating to expert-provided a priori information and can also define facts derived from inferred knowledge. MethodKnowledge encompasses effective analytical method presets or mathematical/logical equivalents of established process information.",
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        "http://purl.org/dc/terms/title@en": "The Time-indexed Value in Context",
        "http://purl.org/dc/terms/description@en": "A pattern for the description of scenarios that involve entities having some value during a particular time and within a particular context.",
        "tags": [
          "Time"
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      "_id": "http://www.observedchange.com/tisc/ns#",
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        "http://purl.org/dc/terms/title@en": "Open Time and Space Core Vocabulary",
        "http://purl.org/dc/terms/description@en": "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.",
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        "http://purl.org/dc/terms/title@en": "Intervals Ontology",
        "http://purl.org/dc/terms/description@en": "An ontology for time intervals",
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        "http://purl.org/dc/terms/title@en": "OntoMedia Date Part Representation",
        "http://purl.org/dc/terms/description@en": "OntoMedia (Ontology for Media) Date Component has been designed to describe the different ways of marking time in media.",
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        "http://purl.org/dc/terms/title@en": "Linked Science Core Vocabulary",
        "http://purl.org/dc/terms/description@en": "LSC, the Linked Science Core Vocabulary, is a lightweight vocabulary providing terms to enable publishers and researchers to relate things in science to time, space, and themes.",
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        "prefix": "pro",
        "http://purl.org/dc/terms/title@en": "The Publishing Roles Ontology",
        "http://purl.org/dc/terms/description@en": "PRO, the Publishing Roles Ontology, is an ontology for describing the role(s) in the publication process of a particular agent over a defined period of time. It forms part of SPAR, a suite of Semantic Publishing and Referencing Ontologies.",
        "tags": [
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        "http://purl.org/dc/terms/title@en": "Sequence Pattern",
        "http://purl.org/dc/terms/description@en": "Intended to represent sequence schemas. It defines the notion of transitive and intransitive precedence and their inverses.  It can then be used between tasks, processes, time intervals, spatially locate objects, situations, etc.",
        "tags": [
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        "http://purl.org/dc/terms/title@en": "Semantic Sensor Network Ontology",
        "http://purl.org/dc/terms/description@en": "This ontology describes sensors, actuators and observations, and related concepts. It does not describe domain concepts, time, locations, etc. these are intended to be included from other ontologies via OWL imports.",
        "tags": [
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        "http://purl.org/dc/terms/title@en": "Ontology for modelling historic administrative information.",
        "http://purl.org/dc/terms/title@de": "Ontologie zur Modellierung historischer Verwaltungsinformationen.",
        "http://purl.org/dc/terms/description@en": "The Genealogisches Orts-Verzeichnis (GOV) contains information about current and historical political, ecclesiastical and legal administrative affiliations of settlements and administrative units. In addition several time-dependent values (such as names, population numbers, postal codes etc.) are given.",
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