Resource Description Framework in the context of Semantic web

Biocuration is the field of life sciences dedicated to organizing biomedical data, information and knowledge into structured formats, such as spreadsheets, tables and knowledge graphs. The biocuration of biomedical knowledge is made possible by the cooperative work of biocurators, software developers and bioinformaticians and is at the base of the work of biological databases.

RSS (RDF Site Summary or Really Simple Syndication) is a web feed that allows users and applications to access updates to websites in a standardized, computer-readable format. Subscribing to RSS feeds can allow a user to keep track of many different websites in a single news aggregator, which constantly monitors sites for new content, removing the need for the user to manually check them. News aggregators (or "RSS readers") can be built into a browser, installed on a desktop computer, or installed on a mobile device.

Websites usually use RSS feeds to publish frequently updated information, such as blog entries, news headlines, episodes of audio and video series, or for distributing podcasts. An RSS document (called "feed", "web feed", or "channel") includes full or summarized text and metadata like publishing date and author's name. RSS formats are specified using a generic XML file.

A web resource is any identifiable resource (digital, physical, or abstract) present on or connected to the World Wide Web. Resources are identified using Uniform Resource Identifiers (URIs). In the Semantic Web, web resources and their semantic properties are described using the Resource Description Framework (RDF).

The concept of resource has evolved during the Web's history, from the early notion of static addressable documents or files, to a more generic and abstract definition, now encompassing every "thing" or entity that can be identified, named, addressed or handled, in any way whatsoever, in the web at large, or in any networked information system. The declarative aspects of a resource (identification and naming) and its functional aspects (addressing and technical handling) weren't clearly distinct in the early specifications of the web, and the very definition of the concept has been the subject of long and still open debate involving difficult, and often arcane, technical, social, linguistic and philosophical issues.

Knowledge extraction is the creation of knowledge from structured (relational databases, XML) and unstructured (text, documents, images) sources. The resulting knowledge needs to be in a machine-readable and machine-interpretable format and must represent knowledge in a manner that facilitates inferencing. Although it is methodically similar to information extraction (NLP) and ETL (data warehouse), the main criterion is that the extraction result goes beyond the creation of structured information or the transformation into a relational schema. It requires either the reuse of existing formal knowledge (reusing identifiers or ontologies) or the generation of a schema based on the source data.

The RDB2RDF W3C group is currently standardizing a language for extraction of resource description frameworks (RDF) from relational databases. Another popular example for knowledge extraction is the transformation of Wikipedia into structured data and also the mapping to existing knowledge (see DBpedia and Freebase).

The Semantic Web, sometimes known as Web 3.0, is an extension of the World Wide Web through standards set by the World Wide Web Consortium (W3C). The goal of the Semantic Web is to make Internet data machine-readable.

To enable the encoding of semantics with the data, technologies such as Resource Description Framework (RDF) and Web Ontology Language (OWL) are used. These technologies are used to formally represent metadata. For example, ontology can describe concepts, relationships between entities, and categories of things. These embedded semantics offer significant advantages such as reasoning over data and operating with heterogeneous data sources.These standards promote common data formats and exchange protocols on the Web, fundamentally the RDF. According to the W3C, "The Semantic Web provides a common framework that allows data to be shared and reused across application, enterprise, and community boundaries." The Semantic Web is therefore regarded as an integrator across different content and information applications and systems.

A semantic triple, or RDF triple or simply triple, is the atomic data entity in the Resource Description Framework (RDF) data model. As its name indicates, a triple is a sequence of three entities that codifies a statement about semantic data in the form of subject–predicate–object expressions (e.g., "Bob is 35", or "Bob knows John").

Data Catalog Vocabulary (DCAT) is an RDF vocabulary designed to facilitate interoperability between data catalogs published on the Web. By using DCAT to describe datasets in catalogs, publishers increase discoverability and enable applications to consume metadata from multiple catalogs. It enables decentralized publishing of catalogs and facilitates federated dataset search across catalogs. Aggregated DCAT metadata can serve as a manifest file to facilitate digital preservation.

The original DCAT vocabulary was developed at DERI, as an idea from Vassilios Peristeras and his master student Fadi Maali together also with Richard Cyganiak. The vocabulary was further developed by W3C's eGov Interest Group, then brought onto the Recommendation Track by W3C's "Government Linked Data" Working Group. DCAT is the foundation for open dataset descriptions in the European Union public sector and was adapted by the ISA programme of the European Commission. A 2022 report reviews DCAT‑AP compliance on national data portals.

Freebase was a large collaborative knowledge base consisting of data composed mainly by its community members. It was an online collection of structured data harvested from many sources, including individual, user-submitted wiki contributions. Freebase aimed to create a global resource that allowed people (and machines) to access common information more effectively. It was developed by the American software company Metaweb and run publicly beginning in March 2007. Metaweb was acquired by Google in a private sale announced on 16 July 2010. Google's Knowledge Graph is powered in part by Freebase.

During its existence, Freebase data was available for commercial and non-commercial use under a Creative Commons Attribution License, and an open API, RDF endpoint, and a database dump is provided for programmers.