The Dataset Quality Vocabulary (daQ) is a lightweight, extensible core vocabulary for attaching the result of quality benchmarking of a linked open dataset (usually an expensive process) to that dataset. daQ is designed to be extended by custom quality metrics. Use cases include filtering and ranking datasets by quality.
The Activity Streams 2.0 Vocabulary defines a set of abstract types and properties that describe past, present and future activities. The vocabulary is defined in two parts:
- A Core set of properties describing the generalized structure of an Activity; and
- An Extended set of properties that cover specific types of Activities and Artifacts common to many social Web application systems.
Vocabulary for describing test results. The primary motivation for developing this vocabulary is to facilitate the exchange of test results between Web accessibility evaluation tools in a vendor-neutral and platform-independent format. It also provides reusable terms for generic quality assurance and validation purposes.
An RDF representation of XHTML 2.0's built-in link types. It is based on the Metainformation Attributes Module of XHTML2, and uses W3C's RDF Schema (RDFS) and Web Ontology (OWL) languages to describe several kinds of relationship that can hold between information resources.
VoID is an RDF Schema vocabulary for expressing metadata about RDF datasets. It is intended as a bridge between the publishers and users of RDF data, with applications ranging from data discovery to cataloging and archiving of datasets. This document is a detailed guide to the VoID vocabulary. It describes how VoID can be used to express general metadata based on Dublin Core, access metadata, structural metadata, and links between datasets. It also provides deployment advice and discusses the discovery of VoID descriptions.
The Simple Knowledge Organization System (SKOS) is a common data model for sharing and linking knowledge organization systems via the Semantic Web. SKOS-XL defines an extension for the Simple Knowledge Organization System, providing additional support for describing and linking lexical entities.This document provides a brief description of the SKOS-XL vocabulary.
OWL-Time is an OWL-2 DL ontology of temporal concepts, for describing the temporal properties of resources in the world or described in Web pages. The ontology provides a vocabulary for expressing facts about topological (ordering) relations among instants and intervals, together with information about durations, and about temporal position including date-time information. Time positions and durations may be expressed using either the conventional (Gregorian) calendar and clock, or using another temporal reference system such as Unix-time, geologic time, or different calendars.
An RDF vocabulary for describing the basic structure and content of concept schemes such as thesauri, classification schemes, subject heading lists, taxonomies, 'folksonomies', other types of controlled vocabulary, and also concept schemes embedded in glossaries and terminologies.
SHACL Shapes Constraint Language is a language for validating RDF graphs against a set of conditions. These conditions are provided as shapes and other constructs expressed in the form of an RDF graph. RDF graphs that are used in this manner are called “shapes graphs” in SHACL and the RDF graphs that are validated against a shapes graph are called “data graphs”. As SHACL shape graphs are used to validate that data graphs satisfy a set of conditions they can also be viewed as a description of the data graphs that do satisfy these conditions. Such descriptions may be used for a variety of purposes beside validation, including user interface building, code generation and data integration.
The Simple Knowledge Organization System (SKOS) is a common data model for sharing and linking knowledge organization systems via the Semantic Web.This document provides a brief description of the SKOS Vocabulary.
This is the RDF Schema for the RDF vocabulary terms in the RDF Namespace, defined in RDF Concepts.
Named Graphs is the idea that having multiple RDF graphs in a single document/repository and naming them with URIs provides useful additional functionality built on top of the RDF Recommendations.
Named Graphs and corresponding technologies are currently developed by participants of the Semantic Web Interest Group. The intent is to introduce them into the W3C process in an appropriate way once initial versions are finished.
RDF Schema provides a data-modelling vocabulary for RDF data. RDF Schema is an extension of the basic RDF vocabulary.
Vocabulary for describing organizational structures, specializable to a broad variety of types of organization.
This ontology partially describes the built-in classes and properties that together form the basis of the RDF/XML syntax of OWL 2. The content of this ontology is based on Tables 6.1 and 6.2 in Section 6.4 of the OWL 2 RDF-Based Semantics specification, available at http://www.w3.org/TR/owl2-rdf-based-semantics/.
Please note that those tables do not include the different annotations (labels, comments and
rdfs:isDefinedBy links) used in this file. Also note that the descriptions provided in this ontology do not provide a complete and correct formal description of either the syntax or the semantics of the introduced terms (please see the OWL 2 recommendations for the complete and normative specifications).
Furthermore, the information provided by this ontology may be misleading if not used with care. This ontology SHOULD NOT be imported into OWL ontologies. Importing this file into an OWL 2 DL ontology will cause it to become an OWL 2 Full ontology and may have other, unexpected, consequences.
The Web Annotation Vocabulary specifies the set of RDF classes, predicates and named entities that are used by the Web Annotation Data Model. It also lists recommended terms from other ontologies that are used in the model, and provides the JSON-LD Context and profile definitions needed to use the Web Annotation JSON serialization in a Linked Data context.
Vocabulary for representing pointers ― entities that permit identifying a portion or segment of a piece of content ― making use of the Resource Description Framework (RDF). It also describes a number of specific types of pointers that permit portions of a document to be referred to in different ways. When referring to a specific part of, say, a piece of web content, it is useful to be able to have a consistent manner by which to refer to a particular segment of a web document, to have a variety of ways by which to refer to that same segment, and to make the reference robust in the face of changes to that document. This specification is part of the Evaluation And Report Language (EARL) but can be reused in other contexts too.
The i18n namespace is used for describing combinations of language tag and base direction in RDF literals.
It is used as an alternative mechanism for describing the BCP47 language tag and base direction of RDF literals that would otherwise use the
A vocabulary that defines a collection of RDF classes and properties that represent the HTTP vocabulary as defined by the HTTP specification RFC2616. These RDF terms can be used to record HTTP or secure HTTP request and response messages in RDF format, such as by automated Web accessibility evaluation tools that want to describe Web resources, including the various headers exchanged between the client and server during content negotiation.
The Dataset Usage Vocabulary (DUV) is used to describe consumer experiences, citations, and feedback about datasets from the human perspective.
Datasets published on the Web are accessed and experienced by consumers in a variety of ways, but little information about these experiences is typically conveyed. Dataset publishers many times lack feedback from consumers about how datasets are used. Consumers lack an effective way to discuss experiences with fellow collaborators and explore referencing material citing the dataset. Datasets as defined by DCAT are a collection of data, published or curated by a single agent, and available for access or download in one or more formats. The Dataset Usage Vocabulary (DUV) is used to describe consumer experiences, citations, and feedback about the dataset from the human perspective.
By specifying a number of foundational concepts used to collect dataset consumer feedback, experiences, and cite references associated with a dataset, APIs can be written to support collaboration across the Web by structurally publishing consumer opinions and experiences, and provide a means for dataset consumers and producers advertise and search for published open dataset usage.
The Data Quality Vocabulary (DQV) provides a framework in which the quality of a dataset can be described, whether by the dataset publisher or by a broader community of users. It does not provide a formal, complete definition of quality, rather, it sets out a consistent means by which information can be provided such that a potential user of a dataset can make his/her own judgment about its fitness for purpose.