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Resource Description Framework
The Resource Description Framework (RDF) is a World Wide Web Consortium (W3C) standard originally designed as a data model for metadata. It has come to be used as a general method for description and exchange of graph data. RDF provides a variety of syntax notations and data serialization formats with Turtle (Terse RDF Triple Language) currently being the most widely used notation. RDF is a directed graph composed of triple statements. An RDF graph statement is represented by: 1) a node for the subject, 2) an arc that goes from a subject to an object for the predicate, and 3) a node for the object. Each of the three parts of the statement can be identified by a URI. An object can also be a literal value. This simple, flexible data model has a lot of expressive power to represent complex situations, relationships, and other things of interest, while also being appropriately abstract. RDF was adopted as a W3C recommendation in 1999. The RDF 1.0 specification was published in 2004, th ...
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Entity–relationship Model
An entity–relationship model (or ER model) describes interrelated things of interest in a specific domain of knowledge. A basic ER model is composed of entity types (which classify the things of interest) and specifies relationships that can exist between entities (instances of those entity types). In software engineering, an ER model is commonly formed to represent things a business needs to remember in order to perform business processes. Consequently, the ER model becomes an abstract data model, that defines a data or information structure which can be implemented in a database, typically a relational database. Entity–relationship modeling was developed for database and design by Peter Chen and published in a 1976 paper, with variants of the idea existing previously, but today it is commonly used for teaching students the basics of data base structure. Some ER models show super and subtype entities connected by generalization-specialization relationships, and an ER mode ...
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Knowledge Management
Knowledge management (KM) is the collection of methods relating to creating, sharing, using and managing the knowledge and information of an organization. It refers to a multidisciplinary approach to achieve organisational objectives by making the best use of knowledge. An established discipline since 1991, KM includes courses taught in the fields of business administration, information systems, management, library, and information science. Other fields may contribute to KM research, including information and media, computer science, public health and public policy. Several universities offer dedicated master's degrees in knowledge management. Many large companies, public institutions, and non-profit organisations have resources dedicated to internal KM efforts, often as a part of their business strategy, IT, or human resource management departments. Several consulting companies provide advice regarding KM to these organizations. Knowledge management efforts typically fo ...
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Meta Content Framework
Meta Content Framework (MCF) is a specification of a content format for structuring metadata about web sites and other data. History MCF was developed by Ramanathan V. Guha at Apple Computer's Advanced Technology Group between 1995 and 1997. Rooted in knowledge-representation systems such as CycL, KRL, and KIF, it sought to describe objects, their attributes, and the relationships between them. One application of MCF was HotSauce, also developed by Guha while at Apple. It generated a 3D visualization of a web site's table of contents, based on MCF descriptions. By late 1996, a few hundred sites were creating MCF files and Apple HotSauce allowed users to browse these MCF representations in 3D. When the research project was discontinued, Guha left Apple for Netscape, where, in collaboration with Tim Bray, he adapted MCF to use XML and created the first version of the Resource Description Framework The Resource Description Framework (RDF) is a World Wide Web Consortium (W3C) ...
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Dublin Core
220px, Logo image of DCMI, which formulates Dublin Core The Dublin Core, also known as the Dublin Core Metadata Element Set (DCMES), is a set of fifteen "core" elements (properties) for describing resources. This fifteen-element Dublin Core has been formally standardized as ISO 15836, ANSI/NISO Z39.85, and IETF RFC 5013. The Dublin Core Metadata Initiative (DCMI), which formulates the Dublin Core, is a project of the Association for Information Science and Technology (ASIS&T), a non-profit organization. The core properties are part of a larger set of DCMI Metadata Terms. "Dublin Core" is also used as an adjective for Dublin Core metadata, a style of metadata that draws on multiple Resource Description Framework (RDF) vocabularies, packaged and constrained in Dublin Core application profiles. The resources described using the Dublin Core may be digital resources (video, images, web pages, etc.) as well as physical resources such as books or works of art. Dublin Core metadata may ...
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Platform For Internet Content Selection
The Platform for Internet Content Selection (PICS) was a specification created by W3C that used metadata to label webpages to help parents and teachers control what children and students could access on the Internet. The W3C Protocol for Web Description Resources project integrates PICS concepts with RDF. PICS was superseded by POWDER, which itself is no longer actively developed. PICS often used a content labeling from the Internet Content Rating Association, which has also been discontinued by the Family Online Safety Institute's board of directors. An alternative self-rating system, named Voluntary Content Rating, was devised by Solid Oak Software in 2010, in response to the perceived complexity of PICS. Internet Explorer 3 was one of the early web browsers to offer support for PICS, released in 1996. Internet Explorer 5 added a feature called ''approved sites'', that allowed extra sites to be added to the list in addition to the PICS list when it was being used.
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Ontology Language
In computer science and artificial intelligence, ontology languages are formal languages used to construct ontologies. They allow the encoding of knowledge about specific domains and often include reasoning rules that support the processing of that knowledge. Ontology languages are usually declarative languages, are almost always generalizations of frame languages, and are commonly based on either first-order logic or on description logic. Classification of ontology languages Classification by syntax Traditional syntax ontology languages * Common Logic - and its dialects * CycL * DOGMA (Developing Ontology-Grounded Methods and Applications) * F-Logic (Frame Logic) * FO-dot (First-order logic extended with types, arithmetic, aggregates and inductive definitions) * KIF (Knowledge Interchange Format) ** Ontolingua based on KIF * KL-ONE * KM programming language * LOOM (ontology) * OCML (Operational Conceptual Modelling Language) * OKBC ( Open Knowledge Base Connectivity) * P ...
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SHACL
Shapes Constraint Language (SHACL) is a World Wide Web Consortium (W3C) standard language for describing Resource Description Framework (RDF) graphs. SHACL has been designed to enhance the semantic and technical interoperability layers of ontologies expressed as RDF graphs. SHACL models are defined in terms of constraints on the content, structure and meaning of a graph. SHACL is a highly expressive language. Among others, it includes features to express conditions that constrain the number of values that a property may have, the type of such values, numeric ranges, string matching patterns, and logical combinations of such constraints. SHACL also includes an extension mechanism to express more complex conditions in languages such as SPARQL and JavaScript. SHACL Rules add inferencing capabilities to SHACL, allowing users to define what new statements can be inferred from existing (asserted) statements. The growing adoption of SHACL may influence the future of linked data. Termin ...
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Web Ontology Language
The Web Ontology Language (OWL) is a family of knowledge representation languages for authoring ontologies. Ontologies are a formal way to describe taxonomies and classification networks, essentially defining the structure of knowledge for various domains: the nouns representing classes of objects and the verbs representing relations between the objects. Ontologies resemble class hierarchies in object-oriented programming but there are several critical differences. Class hierarchies are meant to represent structures used in source code that evolve fairly slowly (perhaps with monthly revisions) whereas ontologies are meant to represent information on the Internet and are expected to be evolving almost constantly. Similarly, ontologies are typically far more flexible as they are meant to represent information on the Internet coming from all sorts of heterogeneous data sources. Class hierarchies on the other hand tend to be fairly static and rely on far less diverse and more struct ...
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RDFS
RDF Schema (Resource Description Framework Schema, variously abbreviated as RDFS, , RDF-S, or RDF/S) is a set of classes with certain properties using the RDF extensible knowledge representation data model, providing basic elements for the description of ontologies. It uses various forms of RDF vocabularies, intended to structure RDF resources. RDF and RDFS can be saved in a triplestore, then one can extract some knowledge from them using a query language, like SPARQL. The first version was published by the World-Wide Web Consortium (W3C) in April 1998, and the final W3C recommendation was released in February 2014. Many RDFS components are included in the more expressive Web Ontology Language (OWL). Terminology RDFS constructs are the RDFS classes, associated properties and utility properties built on the vocabulary of RDF. Classes ; : Represents the class of everything. All things described by RDF are resources. ; : An ''rdfs:Class'' declares a resource as a class for ot ...
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Ontology (computer Science)
In computer science and information science, an ontology encompasses a representation, formal naming, and definition of the categories, properties, and relations between the concepts, data, and entities that substantiate one, many, or all domains of discourse. More simply, an ontology is a way of showing the properties of a subject area and how they are related, by defining a set of concepts and categories that represent the subject. Every academic discipline or field creates ontologies to limit complexity and organize data into information and knowledge. Each uses ontological assumptions to frame explicit theories, research and applications. New ontologies may improve problem solving within that domain. Translating research papers within every field is a problem made easier when experts from different countries maintain a controlled vocabulary of jargon between each of their languages. For instance, the philosophy and economics#Definition and ontology of economics, definition a ...
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Relational Model
The relational model (RM) is an approach to managing data using a structure and language consistent with first-order predicate logic, first described in 1969 by English computer scientist Edgar F. Codd, where all data is represented in terms of tuples, grouped into relations. A database organized in terms of the relational model is a relational database. The purpose of the relational model is to provide a declarative method for specifying data and queries: users directly state what information the database contains and what information they want from it, and let the database management system software take care of describing data structures for storing the data and retrieval procedures for answering queries. Most relational databases use the SQL data definition and query language; these systems implement what can be regarded as an engineering approximation to the relational model. A ''table'' in a SQL database schema corresponds to a predicate variable; the contents of a tabl ...
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Knowledge Representation
Knowledge representation and reasoning (KRR, KR&R, KR²) is the field of artificial intelligence (AI) dedicated to representing information about the world in a form that a computer system can use to solve complex tasks such as diagnosing a medical condition or having a dialog in a natural language. Knowledge representation incorporates findings from psychology about how humans solve problems and represent knowledge in order to design formalisms that will make complex systems easier to design and build. Knowledge representation and reasoning also incorporates findings from logic to automate various kinds of ''reasoning'', such as the application of rules or the relations of sets and subsets. Examples of knowledge representation formalisms include semantic nets, systems architecture, frames, rules, and ontologies. Examples of automated reasoning engines include inference engines, theorem provers, and classifiers. History The earliest work in computerized knowledge rep ...
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