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A vocabulary to describe opening hours using calendars (recommended: iCal, RDFCal or schema.org) published on the Web. @en
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The BBC ontology is used to describe BBC concepts in the store. For example, the BBC divisions (products) publishing linked data and interfacing with the triplestore, the platforms for which we produce content and the web documents that publish or are relevant to the BBC's content. @en
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A pattern for the description of scenarios that involve entities having some value during a particular time and within a particular context. @en
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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. @en
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The NEPOMUK Calendaring Ontology intends to provide vocabulary for describing calendaring data (events, tasks, journal entries) which is an important part of the body of information usually stored on a desktop. It is an adaptation of the ICALTZD ontology created by the W3C RDF Calendar Task Force of the Semantic Web Interest Group in the Semantic Web Activity. @en
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This vocabulary defines temporal entities such as time intervals, their properties and relationships. @en
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A vocabulary for description of events and calendars @en
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A vocabulary to describe time zones and their geographical coverage. @en
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An entry sub-ontology of time (OWL-Time). @en
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Defines temporal / spatial concepts and general-purpose datastructures @en
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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
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This ontology defines: - a set of subclasses of `seas:Evaluation` to better interpret evaluations of quantifiable properties. - a set of sub properties of `seas:hasProperty` to qualify time-related properties. @en
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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. @en
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The Gouda Time Machine Ontology describes the geo-temporal classes and properties used within the Gouda Time Machine. @en
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