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The Structured Data Linter is a tool aiding webmasters and web developers to verify the structured data present in their HTML pages. Search engines use structured data to understand webpages more accurately and to present enhanced search results. The Linter understands the microdata, JSON-LD and RDFa formats according to their latest specifications. Note however that it does not guarranty that all consumers (e.g. search engines) will make use of all the structured data available in your page. The linter does not currently support microformats (contributions welcome).

"KBpedia is a comprehensive knowledge structure for promoting data interoperability and knowledge-based artificial intelligence, or KBAI. The KBpedia knowledge structure combines six (6) public knowledge bases - Wikipedia, Wikidata, OpenCyc, GeoNames, DBpedia and UMBEL - into an integrated whole. KBpedia's upper structure, or knowle"

"Wikibase is the software that enables MediaWiki to store structured data or access data that is stored in a structured data repository. Wikibase basically consists of two MediaWiki extensions, Wikibase Repository and Wikibase Client, that can be enabled individually or together for a certain MediaWiki installation to turn it into a structured data repository, a client of a structured data repository or both."

OpenStructs is an education and distribution site dedicated to open source software for converting, managing, viewing and manipulating structured data. Structured data can represent any existing data struct from the simplest attribute-value pair formats to fully specified relational database schema. Material on this OpenStructs site ranges from individual tools to complete open semantic frameworks (OSF) with which to builld comprehensive semantic instances. All OpenStructs tools are premised on the canonical RDF (Resource Description Framework) data model. Thus, OpenStructs tools either convert existing data structures to RDF, extract structure from content as RDF, or manage and manipulate RDF. All OpenStructs tools and approaches are as compliant as possible with existing open standards from the W3C. The intent is to achieve maximum data and software interoperabililty.

RDF is a standard model for data interchange on the Web. RDF has features that facilitate data merging even if the underlying schemas differ, and it specifically supports the evolution of schemas over time without requiring all the data consumers to be changed. RDF extends the linking structure of the Web to use URIs to name the relationship between things as well as the two ends of the link (this is usually referred to as a "triple"). Using this simple model, it allows structured and semi-structured data to be mixed, exposed, and shared across different applications.

"The OpenLink Structured Data Sniffer (OSDS) is a browser extension for Google Chrome, Mozilla Firefox, Opera, and Vivaldi (with builds planned for Apple Safari and Microsoft Edge) that unveils structured metadata embedded within HTML documents and web pages."

conStruct SCS is a distro of the Drupal framework that aims to set a new standard in data integration and as a structured content system (SCS). With conStruct, you can let your data and its structure drive your applications. You can easily interoperate your diverse internal information with public content on the Web. And you can leverage a platform designed from the ground up for knowledge management and collaboration. We invite you to learn more and take some test drives. And, like Drupal, conStruct is of course free and open source.

Extracting Structured Data from the Common Web Crawl More and more websites have started to embed structured data describing products, people, organizations, places, events into their HTML pages. The Web Data Commons project extracts this data from several billion web pages and provides the extracted data for download. Web Data Commons thus enables you to use the data without needing to crawl the Web yourself.

Extracting Structured Data from the Common Web Crawl More and more websites have started to embed structured data describing products, people, organizations, places, events into their HTML pages. The Web Data Commons project extracts this data from several billion web pages and provides the extracted data for download.

"Sehrch is a new semantic search engine developed in the UK. You can search their index by entering a regular query, like on Bing or Google, or you can benefit from their structured data by formulating advanced searches and get precise results."

SIREn: Efficient semi-structured Information Retrieval for Lucene Efficient, large scale handling of semi-structured data (including RDF) is increasingly an important issue to many web and enterprise information reuse scenarios.

DBpedia.org is a project aiming to extract structured information from the information creadted as part of the Wikipedia project. This structured information is then made available on the World Wide Web.

Turn Web content into structured data, Extractiv lets you transform unstructured web content into highly-structured semantic data.

DBpedia is a project aiming to extract structured information from the information created as part of the Wikipedia project. This structured information is then made available on the World Wide Web. DBpedia allows users to query relationships and properties associated with Wikipedia resources, including links to other related datasets. DBpedia has been described by Tim Berners-Lee as one of the more famous parts of the Linked Data project.

the wiki for the community of users, administrators and developers of the Semantic MediaWiki extension to the MediaWiki application, and all its spinoff extensions, including Semantic Forms, Semantic Drilldown, Semantic Result Formats, Halo, Semantic Maps and others. The wiki itself uses many of these extensions, in order to provide a flexible yet structured interface to the data. Here you will find information on people and organizations in the Semantic MediaWiki community, a listing of SMW-based sites, a list of extensions themselves, a list of SMW-related events, a list of requested features for the extensions, and a list of "packages", which are collections of wiki pages defining properties, templates, forms etc. that can be imported into one's wiki to create an instant data structure.

Semantic matching is a type of ontology matching technique that relies on semantic information encoded in lightweight ontologies to identify nodes that are semantically related. Given any two graph-like structures, like classifications, database or XML schemas and ontologies, matching is an operator that identifies those nodes in the two structures which semantically correspond to one another. For example, applied to file systems it can identify that a folder labeled "car" is semantically equivalent to another folder "automobile" because they are synonyms in English. This information can be taken from a linguistic resource like WordNet.

OpenStructs is an education and distribution site dedicated to open source software for converting, managing, viewing and manipulating structured data. Structured data can represent any existing data struct from the simplest attribute-value pair formats to fully specified relational database schema. Material on this OpenStructs site ranges from individual tools to complete open semantic frameworks (OSF) with which to builld comprehensive semantic instances.

"Cognonto is an IT consulting boutique specializing in semantic technologies, knowledge graphs, and knowledge-based artificial intelligence. We are the developers of, and have unique expertise in, the knowledge structure KBpedia and its use in machine learning and data interoperability. Cognonto principals are scientists and acknowledged experts in knowledge representation, natural language understanding, and distributed knowledge sharing."

"This Wikiproject aims to provide structured data to study people's names throughout history, in the whole world, in all languages, for all people present in Wikidata, through structural properties and linguistic information."

"KBpedia is a computable knowledge structure that combines six (6) public knowledge bases - Wikipedia, Wikidata, OpenCyc, GeoNames, DBpedia and UMBEL - into an integrated whole. The knowledge graph that organizes this computable framework is the KBpedia Knowledge Ontology (KKO). KBpedia is the entirety of the combined knowledge bases; KKO is the schema by which these combined sources are made coherent.[1]"