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Metadata is "data about data".[1] There are two "metadata types;" structural metadata, about the design and specification of data structures or "data about the containers of data"; and descriptive metadata about individual instances of application data or the data content. The main purpose of metadata is to facilitate in the discovery of relevant information, more often classified as resource discovery. Metadata also helps organize electronic resources, provide digital identification, and helps support archiving and preservation of the resource. Metadata assists in resource discovery by "allowing resources to be found by relevant criteria, identifying resources, bringing similar resources together, distinguishing dissimilar resources, and giving location information." [2] Definition[edit] Metadata (metacontent) is defined as the data providing information about one or more aspects of the data, such as: Metadata is data. Libraries[edit] Photographs[edit] Video[edit] Web pages[edit] [edit] [edit]

Métadonnée Un article de Wikipédia, l'encyclopédie libre. Un exemple type est d'associer à une donnée la date à laquelle elle a été produite ou enregistrée, ou à une photo les coordonnées GPS du lieu où elle a été prise. Historique[modifier | modifier le code] Tous les établissements qui ont à gérer de l'information, bibliothèques, archives ou médiathèques ont déjà une longue pratique dans la codification du signalement ou des contenus des documents qu'ils manipulent. Ces descriptions ont ensuite été informatisées sous la forme de notices bibliographiques et normalisées (voir par exemple les formats MARC en 1964 utilisant la norme ISO 2709 dont la conception a démarré en 1960). Les bibliothèques numériques ont eu recours aux mêmes dispositifs pour gérer et localiser des documents électroniques. Le terme métadonnée (en anglais : metadata) est apparu dans le cadre de la description de ressources sur Internet dans les années 1990 et s'est ensuite généralisé. Généralisation[modifier | modifier le code]

Sistema de gestión de bases de datos Un sistema de gestión de bases de datos (SGBD) es un conjunto de programas que permiten el almacenamiento, modificación y extracción de la información en una base de datos, además de proporcionar herramientas para añadir, borrar, modificar y analizar los datos. Los usuarios pueden acceder a la información usando herramientas específicas de interrogación y de generación de informes, o bien mediante aplicaciones al efecto Los SGBD también proporcionan métodos para mantener la integridad de los datos, para administrar el acceso de usuarios a los datos y para recuperar la información si el sistema se corrompe. Permite presentar la información de la base de datos en variados formatos. La mayoría de los SGBD incluyen un generador de informes. Hay muchos tipos de SGBD distintos según manejen los datos y muchos tamaños distintos según funcionen sobre ordenadores personales y con poca memoria a grandes sistemas que funcionan en mainframes con sistemas de almacenamiento especiales. [editar]

Ontologie (informatique) Un article de Wikipédia, l'encyclopédie libre. Par analogie, le terme est repris en informatique et en science de l'information, où une ontologie est l'ensemble structuré des termes et concepts représentant le sens d'un champ d'informations, que ce soit par les métadonnées d'un espace de noms, ou les éléments d'un domaine de connaissances. L'ontologie constitue en soi un modèle de données représentatif d'un ensemble de concepts dans un domaine, ainsi que des relations entre ces concepts. Elle est employée pour raisonner à propos des objets du domaine concerné. Plus simplement, on peut aussi dire que l' « ontologie est aux données ce que la grammaire est au langage ». L'objectif premier d'une ontologie est de modéliser un ensemble de connaissances dans un domaine donné, qui peut être réel ou imaginaire. Les ontologies informatiques sont des outils qui permettent précisément de représenter un corpus de connaissances sous une forme utilisable par un ordinateur. Notes

Database Management System: Basics Beyond Social: Read/Write in The Era of Internet of Things This blog was founded in 2003 on the philosophy of a read/write Web - a Web in which people can create content as easily as they consume it. This trend eventually came to be known as Web 2.0 - although others preferred Social Web - and was popularized by activities like blogging and social networking. It would be easy to say that the 'social' element is still the primary part of today's Web, since the popular products of this era enable you to say what's on your mind (Facebook), what's happening (Twitter), or where you are (Foursquare). All of these are mostly social activities. But more significantly, these and other products output data that will increasingly be used to build personalized services for you. The more data there is, the better Web services will be at delivering personal value to you. How We Went Beyond Social So how did we arrive at a Web that is less about social and more about you? It's not how much content you consume that is important, it's about what you do with data.

Definición: 3.0 Semantic Web The Semantic Web is a collaborative movement led by international standards body the World Wide Web Consortium (W3C).[1] The standard promotes common data formats on the World Wide Web. By encouraging the inclusion of semantic content in web pages, the Semantic Web aims at converting the current web, dominated by unstructured and semi-structured documents into a "web of data". The Semantic Web stack builds on the W3C's Resource Description Framework (RDF).[2] 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".[2] The term was coined by Tim Berners-Lee for a web of data that can be processed by machines.[3] While its critics have questioned its feasibility, proponents argue that applications in industry, biology and human sciences research have already proven the validity of the original concept. History[edit] Purpose[edit] Limitations of HTML[edit] Semantic Web solutions[edit]

Database Database management systems (DBMSs) are specially designed software applications that interact with the user, other applications, and the database itself to capture and analyze data. A general-purpose DBMS is a software system designed to allow the definition, creation, querying, update, and administration of databases. Well-known DBMSs include MySQL, MariaDB, PostgreSQL, SQLite, Microsoft SQL Server, Oracle, SAP HANA, dBASE, FoxPro, IBM DB2, LibreOffice Base and FileMaker Pro. Terminology and overview[edit] Formally, "database" refers to the data themselves and supporting data structures. A "database management system" (DBMS) is a suite of computer software providing the interface between users and a database or databases. Outside the world of professional information technology, the term database is sometimes used casually to refer to any collection of data (perhaps a spreadsheet, maybe even a card index). The interactions catered for by most existing DBMSs fall into four main groups:

Forecast 2020: Web 3.0+ and Collective Intelligence « simple processes “We know what we are, but we know not what we may become” – Shakespeare The ancient Chinese curse or saying — “May you live in interesting times.” — is upon us. We are in the midst of a new revolution fueled by advancements in the Internet and technology. Currently, there is an abundance of information and the size of social interaction has reached a colossal scale. Past and Present (Web 1.0 and Web 2.0) The best way to explain what Web 2.0 is to compare it to Web 1.0, its earlier version. Afterwards, there was a sudden shift to Web 2.0. Fast Forward to 10 Years from Now (Web 3.0 and beyond) In 10 years, humans and computers will join forces to create “collective intelligence”. Let’s focus on the resulting element — the “collective intelligence”. Please refer to the following diagram where I illustrate how man and machines will achieve such an amazing accomplishment. Obviously this is part thought-experiment and part prophesy. Like this: Like Loading...

Metadata: The definitions, mappings, and other characteristics used to describe how to find, access, and use the company’s data and software components.

Found in: Hurwitz, J., Nugent, A., Halper, F. & Kaufman, M. (2013) Big Data For Dummies. Hoboken, New Jersey, United States of America: For Dummies. ISBN: 9781118504222. by raviii Jan 1