Disco Hyperdata Browser The Disco - Hyperdata Browser is a simple browser for navigating the Semantic Web as an unbound set of data sources. The browser renders all information, that it can find on the Semantic Web about a specific resource, as an HTML page. This resource description contains hyperlinks that allow you to navigate between resources. News 04.03.2007: SemanticWebCentral provides another Linked Data browser called Objectviewer. 03.10.2007: OpenLink has published a new Data Web Browser which, like Disco, also enables you to browse Linked Data on the Web. 01.16.2007: Ivan Herman has written a Disco Bookmarklet. 1. The browser is a server-side application that can be used without installing anything on your machine. The screenshot below shows the browser user interface: You start browsing the Semantic Web by entering a URI into the navigation box. 2. The browser allows you to navigate an unbounded set of data sources. 3. The Semantic Web Client Library is multithreaded to allow faster retrieval. 4.
RDF Book Mashup The RDF book mashup demonstrates how Web 2.0 data sources like Amazon, Google or Yahoo can be integrated into the Semantic Web. The RDF book mashup makes information about books, their authors, reviews, and online bookstores available on the Semantic Web. This information can be used by RDF tools and you can link to it from your own Semantic Web data. Contents News 2009/07/17: GoodRelations support added. 1. The vision of the Semantic Web is to build a global information space consisting of linked data. The goal of the RDF book mashup is to show how Web 2.0 data sources can be integrated into the Semantic Web, meaning that Web 2.0 data can be browsed using generic RDF browsers like Tabulator and can be crawled and cached by Semantic Web search engines like SWSE, SWOOGLE or the Semantic Web Client Library, which will eventually make it possible to query the complete Web using the SPARQL query language. The book mashup applies these principles to Web 2.0 data about books. 2. 3. 4. 5. 6.
Marbles Linked Data Engine Resource Description Framework The Resource Description Framework (RDF) is a family of World Wide Web Consortium (W3C) specifications[1] 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. RDF was adopted as a W3C recommendation in 1999. Overview[edit] RDF is an abstract model with several serialization formats (i.e. file formats), so the particular encoding for resources or triples varies from format to format. This mechanism for describing resources is a major component in the W3C's Semantic Web activity: an evolutionary stage of the World Wide Web in which automated software can store, exchange, and use machine-readable information distributed throughout the Web, in turn enabling users to deal with the information with greater efficiency and certainty. History[edit] <?
Planet RDF Generating RDF from data.gov - Data-gov Wiki From Data-gov Wiki Overview Many of the datasets in data.gov are available as tables (spreadsheets). This makes it easy to translate the datasets into RDF by generating a triple for each table cell where the row id is the subject, the column name is the predicate, and the cell content is the object. Our work adopted the following principles: In the first principle, we minimize our translation by (i) preserving the functional structure of the original tables and (ii) skipping additional understanding of the cell content. In the second principle, we keep the translated RDF friendly to Web users. Our third principle was approached by using a semantic wiki to host user contributed extensions. In our fourth principle we preserve knowledge provenance of the converted RDF documents by embedding metadata about their sources, creators, and creation date time using the well-known Dublin Core and FOAF vocabularies. The Problem Datasets at data.gov are organized in the following structure parse raw data
Semantic desktop In computer science, the Semantic Desktop is a collective term for ideas related to changing a computer's user interface and data handling capabilities so that data is more easily shared between different applications or tasks and so that data that once could not be automatically processed by a computer could be. It also encompasses some ideas about being able to automatically share information between different people. This concept is very much related to the Semantic Web but is distinct insofar as its main concern is the personal use of information. General description[edit] The vision of the semantic desktop can be considered as a response to the perceived problems of existing user interfaces. Without good metadata, computers cannot easily learn many commonly needed attributes about files. Secondly there is the problem of relating different files with each other. A definition of Semantic Desktop was given (Sauermann et al. 2005): Different interpretations of the semantic desktop[edit]
Tracker Tracker is a search engine, search tool and metadata storage system. It allows you to find the proverbial needle in your computer's haystack as well as providing a one stop solution to the organisation, storage and categorisation of your data. User Resources Getting in Touch IRC channel Mailing list File a bug Maintainers: Martyn Russell nickname martyn Jürg Billeter nickname juergbi Carlos Garnacho nickname garnacho Philip Van Hoof nickname pvanhoof Ivan Frade nickname frade Mikael Ottela nickname ottela Aleksander Morgado nickname aleksander Development Resources RelFinder - Visual Data Web Are you interested in how things are related with each other? The RelFinder helps to get an overview: It extracts and visualizes relationships between given objects in RDF data and makes these relationships interactively explorable. Highlighting and filtering features support visual analysis both on a global and detailed level. Check out the following links for some examples: The RelFinder can easily be configured to work with different RDF datasets. The RelFinder can also be more deeply integrated with your project: Integrating the RelFinder See the following examples of how the RelFinder is integrated into other projects: Ontotext applies the RelFinder to enable an exploration of relationships in the biomedical domain. The RelFinder is readily configured to access RDF data of the DBpedia project and only requires a Flash Player plugin to be executed (which is usually already installed in web browsers). All tools on this website are research prototypes that might contain errors.
IsaViz Overview News IsaViz and Java 1.6 (2007-10-21) IsaViz 2.x is not compatible with Java 1.6 or later. It is recommended to download IsaViz 3.0 which does work with any version of Java. An alpha release is available (see Download section), which should be as stable as IsaViz 2.1 except for the new, still under development, Fresnel and FSL features. IsaViz and GraphViz (2007-05-23) IsaViz 2.x is not compatible with GraphViz 2.10 or later. Several bugs have been fixed in the FSL engines for Jena, Sesame and the visual FSL debugger embedded in IsaViz. Fresnel in IsaViz (2006-05-19) IsaViz 3.0 now supports Fresnel lenses and several elements of the Core Format Vocabulary. FSL for Sesame 2-alpha-3 (2006-04-25) The FSL engine for Sesame 2 now works with version 2alpha3 instead of version 2alpha1. FSL for Sesame 1.2.2 (2005-12-06) In addition to the Sesame 2.0 implementation of FSL, there is now a Sesame 1.2.2 implementation written by Ryan Lee from project Simile. Java FSL Documentation available (2005-11-18)
Ontology creation for the rest of us… COE is a project whose goal is to develop an integrated suite of software tools for constructing, sharing and viewing OWL encoded ontologies based on CmapTools, a concept mapping software used in educational settings, training, and knowledge capturing. Concept maps provide a human-centered interface to display the structure, content, and scope of an ontology. Currently, our work focuses on developing conventions for constructing new Cmap OWL ontologies that will assist and guide users when forming class and property relationships among the concepts in the ontology. In addition, we are working on clustering and searching techniques that support the reuse of existing ontologies. An overview presentation is here. Startup instructions are here. The manual is here. Papers OWL Templates People Adding IHMC Public Ontologies Download Updater for V5.0.3
Semantic Technology’s Role in Big Data Solutions? Forbes has published an article that points out an opportunity for Semantic Technology companies. The article discusses the lack of understanding in companies around big data. Author Gil Press writes, “Listening to Gartner analysts Sheila Childs and Merv Adrian talking yesterday about big data infrastructure challenges, I was reminded of a story Mike Ruettgers, former EMC CEO, liked to tell about similar challenges in the early 1990s. He goes on, “Visiting the CIO of John Deere, Ruettgers asked him whether he saw these ‘distributed systems’ coming back to be managed by the IT department. Press notes, “You may find that all of your best DW, BI, MDM practices for SDLC, PMO and Governance aren’t directly applicable to or just don’t work for Big Data. SemanticWeb community, let’s not let Mr. Image: Courtesy Flickr/ justgrimes
Web Ontology Language Un article de Wikipédia, l'encyclopédie libre. Pour les articles homonymes, voir OWL. Le langage OWL est basé sur les recherches effectuées dans le domaine de la logique de description. Il peut être vu en quelque sorte comme un standard informatique qui met en oeuvre certaines logiques de description, et permet à des outils qui comprennent OWL de travailler avec ces données, de vérifier que les données sont cohérentes, de déduire des connaissances nouvelles ou d'extraires certaines informations de cette base de données. Une extension de RDF[modifier | modifier le code] En pratique, le langage OWL est conçu comme une extension de Resource Description Framework (RDF) et RDF Schema (RDFS) ; OWL est destiné à la description de classes au travers de caractéristiques des instances de cette classes et de types de propriétés. RDF permet par exemple de décrire que <Jean> est le père de <Paul>, au travers des individus <Jean>, <Paul>, et de la relation est le père de. .
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