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The PROV Ontology (PROV-O) expresses the PROV Data Model using the OWL2 Web Ontology Language (OWL2). It provides a set of classes, properties, and restrictions that can be used to represent and interchange provenance information generated in different systems and under different contexts. It can also be specialized to create new classes and properties to model provenance information specific to different domain applications.

KnowWE implements a (refined) concept of semantic wikis: Besides basic ontological knowledge - such as the definition of classes, taxonomic and user-defined properties - KnowWE is able to represent problem-solving knowledge that is applied on selected classes of the ontology. Every wiki page embeds not only semantically annotated text and multimedia but also explicit problem-solving knowledge. The embedded knowledge can be used to actually derive the concept related to the particular wiki article.

"This category is a local alias for the dcmitype:Software (dcmitype | DCMI Metadata Types (Classes)) Class. It is the top category for all software tools listed on this wiki, ie, all tools are automatically classified as being of type dcmitype:Software."

The Missing Link in Semantic Metadata Generation, Auto classification, and Taxonomy Management Concept Searching's conceptual metadata generation, auto-classification, and taxonomy management tools are still unique in the industry.

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"PoolParty is a world-class semantic technology suite that offers sharply focused solutions to your knowledge organization and content business."

Best in class semantic search discovery tool DISQOVER is a semantic search platform that integrates disparate life sciences data. The data is made navigable through a novel indexing engine. Complex queries can be run intuitively and are delivered at speed, enabling you to find smarter data faster with DISQOVER.

The TeraText suite of products includes a number of technologies for solving complex archival, search, and text-oriented problems. These include an enterprise-class email and attachments search platform, a high- performance repository for text-rich assets, and document management and metadata publishing systems.

OntoClean is a methodology for analyzing ontologies based on formal, domain-independent properties of classes (the metaproperties and their modifiers). See below for a bibliography. OntoCleanPaper provides definitions.

The "LOV Search" Features gives you the possibility to search for an existing element (property, class or vocabulary) in the Linked Open Vocabularies Catalogue. LOV Aggregator endpoint and metrics about the use of vocabularies in the Semantic Web are used to bring you some relevant results.

Following the workshop in Video on the Web, the goal of the Video in the Web activity is to make video a "first class citizen" of the Web. Video on the Web (and this includes audio, as the two are typically used together) has seen explosive growth, improving the richness of the user experience but leading to challenges in content discovery, searching, indexing and accessibility. Enabling users (from individuals to large organizations) to put video in the Web requires that we build a solid architectural foundation that enables people to create, navigate, search, link and distribute video, effectively making video part of the Web instead of an extension that doesn't take full advantage of the Web architecture.

LogMap is an ontology matching tool developed as part of the LogMap project. LogMap is highly scalable ontology matching system with 'built-in' reasoning and diagnosis capabilities. LogMap can deal with semantically rich ontologies containing tens (and even hundreds) of thousands of classes such as NCI, FMA and SNOMED CT.

The "LOV Search" Features gives you the possibility to search for an existing element (property, class or vocabulary) in the Linked Open Vocabularies Catalogue. LOV Aggregator endpoint and metrics about the use of vocabularies in the Semantic Web are used to bring you some relevant results.

"The DL-Learner software learns concepts in Description Logics (DLs) from user-provided examples. Equivalently, it can be used to learn classes in OWL ontologies from selected objects. It extends Inductive Logic Programming to Descriptions Logics and the Semantic Web. The goal of DL-Learner is to provide a DL/OWL based machine learning tool to solve supervised learnings tasks and support knowledge engineers in constructing knowledge and learning about the data they created. Read more ..."

This specification describes the FOAF language, defined as a dictionary of named properties and classes using W3C's RDF technology.FOAF is a project devoted to linking people and information using the Web. Regardless of whether information is in people's heads, in physical or digital documents, or in the form of factual data, it can be linked. FOAF integrates three kinds of network: social networks of human collaboration, friendship and association; representational networks that describe a simplified view of a cartoon universe in factual terms, and information networks that use Web-based linking to share independently published descriptions of this inter-connected world. FOAF does not compete with socially-oriented Web sites; rather it provides an approach in which different sites can tell different parts of the larger story, and by which users can retain some control over their information in a non-proprietary format.

The OWL 2 Web Ontology Language, informally OWL 2, is an ontology language for the Semantic Web with formally defined meaning. OWL 2 ontologies provide classes, properties, individuals, and data values and are stored as Semantic Web documents. OWL 2 ontologies can be used along with information written in RDF, and OWL 2 ontologies themselves are primarily exchanged as RDF documents.

The OWL 2 Web Ontology Language, informally OWL 2, is an ontology language for the Semantic Web with formally defined meaning. OWL 2 ontologies provide classes, properties, individuals, and data values and are stored as Semantic Web documents. OWL 2 ontologies can be used along with information written in RDF, and OWL 2 ontologies themselves are primarily exchanged as RDF documents. The OWL 2 Document Overview describes the overall state of OWL 2, and should be read before other OWL 2 documents.

We are experts in the Semantic Web standards and have developed a number of RDF and OWL tools such as our OWL Editor. We were part of the team that originally developed MODAF, and are recognised as world class experts in MODAF, DoDAF and EA in general.

A WebID is a way to uniquely identify a person or other entity, such as a company, an organization, a web site, or other resource. The term "WebID" was coined by Dan Brickley and Tim Berners-Lee in 2000. As of 2010, the term "WebID" is used for a class of solutions, not any one technology. W3C may attempt to standardize one particular identity technology, which may use the term "WebID" more definitively. One of the current approaches using the name "WebID" is the FOAF+SSL WebID, a certificate-based solution. However, the concept of a WebID does not always depend upon FOAF (Friend-of-a-Friend).

ConceptBase.cc is a multi-user deductive database system with an object-centered data model. Its ability to represent information at any abstraction level (data, class, metaclass, meta-metaclass, etc.) makes it a powerful tool for metamodeling and engineering of customized modeling languages. The system is accompanied by a highly configurable graphical user interface that builds upon the logic-based features of the ConceptBase.cc server.