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Jack Park

Cognition Announces "World's Largest Semantic Map" - ReadWriteWeb - 0 views

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    A Semantic Map is kind of like a dictionary, in that it's a representation of Cognition's ability to define things. Cognition claims that its Semantic Map has over 10 million semantic connections; over 4 million semantic contexts (word meanings that create contexts for specific meanings of other related words); over 536,000 word senses (word and phrase meanings); 75,000 concept classes (or synonym classes of word meanings); 7,500 nodes in the technology's ontology or classification scheme; and 506,000 word stems (roots of words) for the English language.
Jack Park

danbri's foaf stories » OpenSocial schema extraction: via Javascript to RDF/OWL - 0 views

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    OpenSocial's API reference describes a number of classes ('Person', 'Name', 'Email', 'Phone', 'Url', 'Organization', 'Address', 'Message', 'Activity', 'MediaItem', 'Activity', …), each of which has various properties whose values are either strings, references to instances of other classes, or enumerations. I'd like to make them usable beyond the confines of OpenSocial, so I'm making an RDF/OWL version. OpenSocial's schema is an attempt to provide an overarching model for much of present-day mainstream 'social networking' functionality, including dating, jobs etc. Such a broad effort is inevitably somewhat open-ended, and so may benefit from being linked to data from other complementary sources.
Jack Park

OpenVocab - 0 views

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    OpenVocab is ideal for properties and classes that don't warrant the effort of creating or maintaining a full schema. OpenVocab allows anyone to create and modify vocabulary terms using their web browser. Each term is described using appropriate elements of RDF, RDFS and OWL. OpenVocab allows you to create any properties and classes; assign labels, comments and descriptions; declare domains and ranges and much more.
Jack Park

Using Semantic Word Classes in Text Information Retrieval Systems (ResearchIndex) - 0 views

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    In this paper an application of methodologies to automatically acquire semantic word classes and to use them in text information retrieval systems is described.
Jack Park

ecai2008_naturalowl.pdf (application/pdf Object) - 0 views

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    See also: http://lists.w3.org/Archives/Public/semantic-web/2008Apr/0005.html NaturalOWL is an open-source natural language generation engine written in Java. It produces descriptions of individuals (e.g., items for sale, museum exhibits) and classes (e.g., types of exhibits) in English and Greek from OWL DL ontologies. The ontologies must have been annotated in RDF with linguistic and user modeling resources. We demonstrate a plug-in for Protege that can be used to produce these resources and to generate texts by invoking NaturalOWL. We also demonstrate how NaturalOWL can be used by robotic avatars in Second Life to describe the exhibits of virtual museums. NaturalOWL demonstrates the benefits of Natural Language Generation (NLG) on the Semantic Web. Organizations that need to publish information about objects, such as exhibits or products, can publish OWL ontologies instead of texts. NLG engines, embedded in browsers or Web servers, can then render the ontologies in multiple natural languages, whereas computer programs may access the ontologies directly.
Jack Park

OWL 2 Web Ontology Language:Primer - 0 views

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    The W3C OWL 2 Web Ontology Language (OWL) is a Semantic Web language designed to represent ontologies - information about how individuals are grouped and fit together in a particular domain. OWL can represent rich and complex information about classes of individuals and their properties. OWL is a logical language, where every construct has a well-defined meaning, meanings that fit together to support exact and useful representation of many different kinds of information. OWL groups information into ontologies in the form of documents that can be stored and transmitted across the World Wide Web in the same way that data and other kinds of information are and that can be completely and effectively processed by tools that extract the information implicit in an ontology.
Jack Park

OntoClean ontology - 0 views

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    This ontology supports the development of Protégé ontologies using the OntoClean methodology (PDF). This methodology for ontological analysis was developed by N. Guarino and C. Welty. The OntoClean methodology applies the notions used for ontological analysis in philosophy to analyzing conceptual modeling in information systems. If you include this Protégé ontology in your ontology, you can annotate your classes with meta-properties of identity, unity, essence, and dependence. The OntoClean ontology in Protégé also contains constraints in the Protégé Axiom Language (PAL) enabling you to verify whether the ontology is "clean"---does not violate any of the constraints based on these properties.
Jack Park

Education City Qatar - 0 views

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    Qatar Foundation is headquartered in a unique Education City, a 2,500-acre campus on the outskirts of Doha which hosts branch campuses of some of the world's leading universities, as well as numerous other educational and research institutions. Supported by abundant residential and recreational facilities, Education City is envisioned as a community of institutions that serve the whole citizen, from early childhood education to post-graduate study. Moreover, Education City is envisioned as a hub for the generation of new knowledge -- a place that provides researchers with world-class facilities, a pool of well-trained graduates, the chance to collaborate with likeminded people and the opportunity to transfer ideas into real-world applications.
Jack Park

NCBO BioPortal - 0 views

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    Welcome to the National Center for Biomedical Ontology's BioPortal. BioPortal is a Web-based application for accessing and sharing biomedical ontologies. New features in BioPortal 2.0 include: * Full ontology navigation using Flash visualization * Web-service access to BioPortal content and capabilities, which enables developers to use our BioPortal services in their tools. * Ability to add Marginal Notes to classes in BioPortal ontologies, a feature that enables the community to comment on ontologies and to discuss their contents * Ability to create Point to Point Mappings between concepts in different BioPortal ontologies * Bulk export of ontology-to-ontology mappings in RDF format * Navigation of multiple ontologies, which enables users to have several ontologies opened simultaneously in different tabs in the user interface * URIs for all ontology content, which enable developers to access and share BioPortal content from their applications * Improved support through Protégé for ontologies in OWL format
Jack Park

HCLSIG BioRDF Subgroup/aTags - ESW Wiki - 1 views

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    # The primary intention of creating aTags is not the categorization of the document, but the representation of the key facts inside the document. Key facts in the biomedical domain might be, for example, "Protein A interacts with protein B" or "Overexpression of protein A in tissue B is the cause of disease C". # An aTag is comprised of a set of associated entities. The size of the set is arbitrary, but will typically lie between 2 and 5 entities. For example, the fact "Protein A binds to protein B" can be represented with an aTag comprising of the three entities "Protein A", "Molecular interaction" and "Protein B". Similarly, the fact "Overexpression of protein A in tissue B is the cause of disease C" can be represented with an aTag comprising of the four entities "Overexpression", "Protein A", "Tissue B" and "Disease C". # Each document or database entry can be described with an arbitrary number of such aTags. Each aTag can be associated with the relevant portions of text or data in a fine granularity. # The entities in an aTag are not simple strings, but resources that are part of ontologies and RDF/OWL-enabled databases. For example, "Protein A" and "Protein B" are resources that are defined in the UniProt database, whereas "Molecular Interaction" is a class in the branch of biological processes of the Gene Ontology. They are identified with their URIs.
Jack Park

An Overview of OntoClean - 0 views

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    OntoClean is a methodology for validating the ontological adequacy of taxonomic relationships. It is based on highly general ontological notions drawn from philosophy, like essence, identity, and unity, which are used to characterize relevant aspects of the intended meaning of the properties, classes, and relations that make up an ontology. These aspects are represented by formal metaproperties, which impose several constraints on the taxonomic structure of an ontology.
Jack Park

COSMO Common Semantic Model - Semantic Community Wiki - 0 views

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    COSMO is the proposed Common Semantic Model, viewed as consisting of a lattice of ontologies which will serve as a set of basic logically-specified concepts (classes, relations, functions, instances) with which the meanings of all terms and concepts in domain ontologies can be specified. The most important function of the COSMO is to serve as a Foundation Ontology that has a sufficient inverntory of fundamental concept representations so that it can support utilities to translate assertions of fundamentally different ontologies into the terminology and format of each other. The use of a common set of defining concepts will permit accurate interoperability of knowledge-based systems using the logical relations of their ontologies as the basis for reasoning in the system. The COSMO can also be used as the starting ontology for creation of more specialized domain ontologies.
Jack Park

Easy RDF and SPARQL for LAMP systems - ARC RDF Classes for PHP - 0 views

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    ARC is a flexible RDF system for semantic web and PHP practitioners. It's free, open-source, easy to use, and runs in most web server environments. RDF and SPARQL for LAMP systems
Jack Park

Easy RDF and SPARQL for LAMP systems - ARC RDF Classes for PHP - 0 views

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    ARC is a flexible RDF system for semantic web and PHP practitioners. It's free, open-source, easy to use, and runs in most web server environments.
Jack Park

SPARQLScript - ARC RDF Classes for PHP - 0 views

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    Many RDF toolkits provide SPARQL/Update functionality and move from simple query operations to more powerful data manipulation. SPARQLScript goes another step further and enables or simplifies the implementation of * semantic Mashups, * custom, portable rule and inference scripts using a SPARQL-based syntax * Output templates for RDF data and SPARQL query results * RDF/SPARQL-driven Yahoo! Pipes-like systems
Jack Park

Proposed Upper Ontology for the Semiotics of Complex Systems - 0 views

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    This is a brief sketch of the kind of upper ontology I envision to support an ontological treatment of semiotics, which in turn would support sign-based ontologies of complex systems.
Swarna Srinivasan

Automotive technology: The connected car | The Economist - 0 views

  • A modern car can have as many as 200 on-board sensors, measuring everything from tyre pressure to windscreen temperature. A high-end Lexus contains 67 microprocessors, and even the world’s cheapest car, the Tata Nano, has a dozen. Voice-driven satellite navigation is routinely used by millions of people. Radar-equipped cruise control allows vehicles to adjust their speed automatically in traffic. Some cars can even park themselves. document.write(''); Once a purely mechanical device, the car is going digital. “Connected cars”, which sport links to navigation satellites and communications networks—and, before long, directly to other vehicles—could transform driving, preventing motorists from getting lost, stuck in traffic or involved in accidents. And connectivity can improve entertainment and productivity for both driver and passengers—an attractive proposition given that Americans, for example, spend 45 hours a month in their cars on average. There is also scope for new business models built around connected cars, from dynamic insurance and road pricing to car pooling and location-based advertising. “We can stop looking at a car as one system,” says Rahul Mangharam, an engineer at the University of Pennsylvania, “and look at it as a node in a network.”
  • The best known connected-car technology is satellite navigation, which uses the global-positioning system (GPS) in conjunction with a database of roads to provide directions and find points of interest. In America there were fewer than 3m navigational devices on the road in 2005, nearly half of which were built in to vehicles. But built-in systems tend to be expensive, are not extensible, and may quickly be out of date. So drivers have been taking matters into their own hands: of the more than 33m units on the road today, nearly 90% are portable, sitting on the dashboard or stuck to the windscreen.
  • Zipcar, the largest car-sharing scheme, shares 6,000 vehicles between 275,000 drivers in London and parts of North America—nearly half of all car-sharers worldwide. Its model depends on an assortment of in-car technology. “This is the first large-scale introduction of the connected car,” claims Scott Griffith, the firm’s chief executive
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  • Zipcar’s available vehicles report their positions to a control centre so that members of the scheme can find nearby vehicles through a web or phone interface. Cars are unlocked by holding a card, containing a wireless chip, up against the windscreen. Integrating cars and back-office systems via wireless links allows Zipcar to repackage cars as a flexible transport service. Each vehicle operated by Zipcar is equivalent to taking 20 cars off the road, says Mr Griffith, and an average Zipcar member saves more than $5,000 dollars a year compared with owning a car.
  • “It is a chicken and egg problem,” says Dr Mangharam, who estimates it would take $4.5 billion to upgrade every traffic light and junction in America with smart infrastructure
  • And adoption of the technology could be mandated by governments, as in the case of Germany’s Toll Collect system, a dynamic road-tolling system for lorries of 12 tonnes or over that has been operating since late 2004. Toll Collect uses a combination of satellite positioning, roadside sensors and a mobile-phone data connection to work out how much to charge each user. Over 900,000 vehicles are now registered with the scheme and there are plans to extend this approach to road-tolling across Europe from 2012. Eventually it may also be extended to ordinary cars.
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