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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.

"Big Data Public Private Forum (BIG) is working towards the definition and implementation of a clear strategy that tackles the necessary efforts in terms of research and innovation, while also it provides a major boost for technology adoption and supporting actions for the successful implementation of the Big Data economy."

The Web Services Description Language (WSDL, pronounced 'wiz-dəl') is an XML-based language that provides a model for describing Web services. The meaning of the acronym has changed from version 1.1 where the D stood for Definition.

wiki contains the infobox-to-ontology and the table-to-ontology mappings which are used by the DBpedia extraction framework as well as the ontology definition itself. The framework collects the templates defined in this Wiki and extracts the Wikipedia content according to them (As of March 2010, only the dump extraction uses the mappings. DBpedia Live is going to follow shortly).

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).

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.

Media Cloud performs five basic functions -- media definition, crawling, text extraction, word vectoring, and analysis. First, we define the set of media sources we want to collect and discover the feeds for each media source (which in the case of many newspapers includes hundreds of feeds). Second, we crawl each of those feeds several times each day to discover any new stories published by each feed and then download the html of each new story. Third, we extract just the substantive content of each story from each html page, leaving behind the ads, navigation, and other cruft. Fourth, we break that substantive text down into a set word counts so that we can count, down to the level of individual sentences, which words which media sources are using to talk about which topics. And finally, we have a set of tools for analyzing those word counts, including the Media Dashboard tool that acts as the front page for http://mediacloud.org.