http://fr.wikipedia.org/wiki/Ontologie_(informatique)
Related: Web Semantique • NotionsSetting Gold Standards for the Semantic Web A new article out of AI3 discusses the need for so-called “gold standards” in the semantic web and examines several possible gold standards. As the article puts it, “The types of gold standards useful to the semantic Web are similar to those useful to our analogy of human languages. We need guidance on structure (syntax and grammar), plus reference vocabularies that encompass the scope of the semantic Web (that is, everything).” The gold standards that the author, Mike Bergman suggests are RDF, RDFS and OWL (building blocks for languages); Wikipedia (a “standard reference vocabulary of things, concepts, and entities”); WordNet (“lexical language references as an aid to natural language processing”); and UMBEL (“the structural reference for the connectedness of things”).
Ontology (information science) In computer science and information science, an ontology formally represents knowledge as a hierarchy of concepts within a domain, using a shared vocabulary to denote the types, properties and interrelationships of those concepts.[1][2] Ontologies are the structural frameworks for organizing information and are used in artificial intelligence, the Semantic Web, systems engineering, software engineering, biomedical informatics, library science, enterprise bookmarking, and information architecture as a form of knowledge representation about the world or some part of it. The creation of domain ontologies is also fundamental to the definition and use of an enterprise architecture framework. Introduction to: RDF vs XML There has always been a misconception between the relationship of RDF and XML. The main difference: XML is a syntax while RDF is a data model. RDF has several syntaxes (Turtle, N3, etc) and XML is one of those (known as RDF/XML). Actually, RDF/XML is the only W3C standard syntax for RDF (Currently, there is Last Call on Turtle, a new W3C standard syntax for RDF).
Turing Equivalent vs. Turing Complete In my discussion with Sal Cordova in this post, one point came up which I thought was interesting, and worth taking the time to flesh out as a separate post. It's about the distinction between a Turing equivalent computing system, and a Turing complete computation. It's true that in informal use, we often tend to muddy the line between these two related but distinct concepts. But in fact, they are distinct, and the difference between them can be extremely important. In some sense, it's the difference between "capable of" and "requires"; another way of looking at it is "sufficient" versus "necessary". Semantic spectrum The semantic spectrum (sometimes referred to as the ontology spectrum or the smart data continuum or semantic precision) is a series of increasingly precise or rather semantically expressive definitions for data elements in knowledge representations, especially for machine use. Some steps in the semantic spectrum include the following: Typical questions for determining semantic precision[edit] The following is a list of questions that may arise in determining semantic precision.
Defining the Semantic Web in a Few Sentences A Quora user posed this challenge to the network: “How do you explain semantic web to a nine-year old child in one sentence?” The challenge was followed by a quote from Albert Einstein: “If you can’t explain it to a six year old, you don’t understand it yourself.” Some of the best responses so far include, “A web where computers better understand the real meaning of the words we use to communicate with them.” “Hi Timmy, the web is like one giant big book written by a lot of people.
Information géopolitique The FAO geopolitical ontology and related services have been developed to facilitate data exchange and sharing in a standardized manner among systems managing information about countries and/or regions. The geopolitical ontology ensures that FAO and associated partners can rely on a master reference for geopolitical information, as it manages names in multiple languages (English, French, Spanish, Arabic, Chinese, Russian and Italian); maps standard coding systems (UN, ISO, FAOSTAT, AGROVOC, etc); provides relations among territories (land borders, group membership, etc); and tracks historical changes. Geopolitical ontology overview The geopolitical ontology has been populated using FAO, UN and internationally recognized data sources. The geopolitical ontology manages the following information: Area types1:
Presentation: SPARQL, Queries, & Linked Data A new presentation from the ICWE Conference is available online. The presentation is titled An Introduction to SPARQL and Queries over Linked Data: “Nowadays, more and more datasets are published on the Web adhering to the Linked Data principles. The availability of this data, including the existence of data-level connections between datasets, presents exciting opportunities for the next generation of Web-based applications. As a consequence, consuming Linked Data is a highly relevant topic in the context of Web engineering. Our introductory tutorial aims to provide participants with an understanding of one of the basic aspects of Linked Data consumption, that is, querying Linked Data.”
Turing Universal Language Representation model, T-ULRv2, tops XTREME leaderboard Today, we are happy to announce that Turing multilingual language model (T-ULRv2) is the state of the art at the top of the Google XTREME public leaderboard. Created by the Microsoft Turing team in collaboration with Microsoft Research, the model beat the previous best from Alibaba (VECO) by 3.5 points in average score. To achieve this, in addition to the pretrained model, we leveraged “StableTune,” a novel multilingual fine-tuning technique based on stability training. Other models on the leaderboard include XLM-R, mBERT, XLM and more. One of the previous best submissions is also from Microsoft using FILTER. Universal Language Representation
Developers Guide to Semantic Web Toolkits for different Programming Languages Abstract This guide collects links to Semantic Web toolkits for different programming languages and gives an overview about the features of each toolkit, the strength of the development effort and the toolkit's user community. Table of Contents
Ontology Summit 2012 This year's Ontology Summit is titled "Ontology for Big Systems" and seeks to explore, identify and articulate how ontological methods can bring value to the various disciplines required to engineer a "big system." The term "big system" is intended to cover a large scope that includes many of the terms encountered in the media such as: Established disciplines that fall within the summit scope include (but not limited to) systems engineering, software engineering, information systems modelling, and data mining. The principal goal of the summit is to bring together and foster collaboration between the ontology community, systems community, and stakeholders of some of the "big systems."
How Google Organizes the World: Q&A With the Manager of Knowledge Graph In May, Google launched a major overhaul of its search results. The Knowledge Graph on the right-hand side of the page displays facts and images about the subject of your query alongside the usual Web results. Google is moving away from basic keyword matching and toward recognizing real-world things and their relationships.
Metaweb to Google’s Knowledge Graph: An Interview with John Giannandrea Alexis Madrigal of The Atlantic recently shared an interview John Giannandrea regarding Google’s Knowledge Graph. Madrigal writes, “The ugly truth is that computers don’t know anything. They have no common sense. This idea had been circulating in Metaweb co-founder John Giannandrea’s head since 1997 when he was working at Netscape and thinking about how to reveal what you did not know you didn’t know on the web. If you were looking at search results for a hiking trail, say, what other hiking trails might you look at? Giannandrea called it ‘going sideways through the web,’ and he loved the idea, even if he couldn’t execute it back then.”