Cwm (pronounced koom) is a general-purpose data processing software for the Semantic Web, similar to sed or awk for text files or XSLT for XML. It is a forward chaining semantic reasoner that can be used for querying, checking, transforming and filtering information. Its core language is RDF, extended to include rules, it can use RDF/XML or RDF/N3 (see Notation3 Primer) serializations.
cwm can perform the following tasks:
cwm was written in Python from 2000-10 onwards by Tim Berners-Lee and Dan Connolly of the W3C.
The Semantic Web 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.
The Resource Description Framework (RDF) is a family of World Wide Web Consortium (W3C) specifications originally designed as a metadata data model. It has come to be used as a general method for conceptual description or modeling of information that is implemented in web resources, using a variety of syntax notations and data serialization formats. It is also used in knowledge management applications.
A topic map is a standard for the representation and interchange of knowledge, with an emphasis on the findability of information. Topic maps were originally developed in the late 1990s as a way to represent back-of-the-book index structures so that multiple indexes from different sources could be merged. However, the developers quickly realized that with a little additional generalization, they could create a meta-model with potentially far wider application. The ISO standard is formally known as ISO/IEC 13250:2003.
RDF Schema is a set of classes with certain properties using the RDF extensible knowledge representation data model, providing basic elements for the description of ontologies, otherwise called RDF vocabularies, intended to structure RDF resources. These resources can be saved in a triplestore to reach them with the query language SPARQL.
SPARQL is an RDF query language—that is, a semantic query language for databases—able to retrieve and manipulate data stored in Resource Description Framework (RDF) format. It was made a standard by the RDF Data Access Working Group (DAWG) of the World Wide Web Consortium, and is recognized as one of the key technologies of the semantic web. On 15 January 2008, SPARQL 1.0 was acknowledged by W3C as an official recommendation, and SPARQL 1.1 in March, 2013.
Notation3, or N3 as it is more commonly known, is a shorthand non-XML serialization of Resource Description Framework models, designed with human-readability in mind: N3 is much more compact and readable than XML RDF notation. The format is being developed by Tim Berners-Lee and others from the Semantic Web community. A formalization of the logic underlying N3 was published by Berners-Lee and others in 2008.
GRDDL is a markup format for Gleaning Resource Descriptions from Dialects of Languages. It is a W3C Recommendation, and enables users to obtain RDF triples out of XML documents, including XHTML. The GRDDL specification shows examples using XSLT, however it was intended to be abstract enough to allow for other implementations as well. It became a Recommendation on September 11, 2007.
Simple Knowledge Organization System (SKOS) is a W3C recommendation designed for representation of thesauri, classification schemes, taxonomies, subject-heading systems, or any other type of structured controlled vocabulary. SKOS is part of the Semantic Web family of standards built upon RDF and RDFS, and its main objective is to enable easy publication and use of such vocabularies as linked data.
RDFLib is a Python library for working with RDF, a simple yet powerful language for representing information. Through this library, Python is one of the main RDF manipulation languages, the other being Java. This library contains parsers/serializers for almost all of the known RDF serializations, such as RDF/XML, Turtle, N-Triples, & JSON-LD, many of which are now supported in their updated form. The library also contains both in-memory and persistent Graph back-ends for storing RDF information and numerous convenience functions for declaring graph namespaces, lodging SPARQL queries and so on. It is in continuous development with the most recent stable release, rdflib 5.0.0 having been released on 18 April, 2020. It was originally created by Daniel Krech with the first release in November, 2002.
Oracle Spatial and Graph, formerly Oracle Spatial, is a free option component of the Oracle Database. The spatial features in Oracle Spatial and Graph aid users in managing geographic and location-data in a native type within an Oracle database, potentially supporting a wide range of applications — from automated mapping, facilities management, and geographic information systems (AM/FM/GIS), to wireless location services and location-enabled e-business. The graph features in Oracle Spatial and Graph include Oracle Network Data Model (NDM) graphs used in traditional network applications in major transportation, telcos, utilities and energy organizations and RDF semantic graphs used in social networks and social interactions and in linking disparate data sets to address requirements from the research, health sciences, finance, media and intelligence communities.
The Semantic Web Rule Language (SWRL) is a proposed language for the Semantic Web that can be used to express rules as well as logic, combining OWL DL or OWL Lite with a subset of the Rule Markup Language.
Terse RDF Triple Language (Turtle) is a syntax and file format for expressing data in the Resource Description Framework (RDF) data model. Turtle syntax is similar to that of SPARQL, an RDF query language. It is a common data format for storing RDF data, along with N-Triples, JSON-LD and RDF/XML.
An RDF query language is a computer language, specifically a query language for databases, able to retrieve and manipulate data stored in Resource Description Framework (RDF) format.
Apache Jena is an open source Semantic Web framework for Java. It provides an API to extract data from and write to RDF graphs. The graphs are represented as an abstract "model". A model can be sourced with data from files, databases, URLs or a combination of these. A model can also be queried through SPARQL 1.1.
A semantic reasoner, reasoning engine, rules engine, or simply a reasoner, is a piece of software able to infer logical consequences from a set of asserted facts or axioms. The notion of a semantic reasoner generalizes that of an inference engine, by providing a richer set of mechanisms to work with. The inference rules are commonly specified by means of an ontology language, and often a description logic language. Many reasoners use first-order predicate logic to perform reasoning; inference commonly proceeds by forward chaining and backward chaining. There are also examples of probabilistic reasoners, including non-axiomatic reasoning systems, and probabilistic logic networks.
N-Triples is a format for storing and transmitting data. It is a line-based, plain text serialisation format for RDF graphs, and a subset of the Turtle format. N-Triples should not be confused with Notation3 which is a superset of Turtle. N-Triples was primarily developed by Dave Beckett at the University of Bristol and Art Barstow at the World Wide Web Consortium (W3C).
The Semantic Web Stack, also known as Semantic Web Cake or Semantic Web Layer Cake, illustrates the architecture of the Semantic Web.
Named graphs are a key concept of Semantic Web architecture in which a set of Resource Description Framework statements are identified using a URI, allowing descriptions to be made of that set of statements such as context, provenance information or other such metadata.
Knowledge extraction is the creation of knowledge from structured and unstructured 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, the main criteria 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 or the generation of a schema based on the source data.
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 set of three entities that codifies a statement about semantic data in the form of subject–predicate–object expressions.