Planet RDF 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]
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. The RDF 1.0 specification was published in 2004, the RDF 1.1 specification in 2014. 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. As RDFS and OWL demonstrate, one can build additional ontology languages upon RDF. History[edit] The W3C published a specification of RDF's data model and an XML serialization as a recommendation in February 1999.[9] RDF topics[edit] RDF vocabulary[edit] Classes[edit] rdf[edit] rdfs[edit] <?
Metacrap 0.1. Version History Version 1.3, August 26 2001. Fixed typos. First published version. Version 1.2, May 23 2001. Version 1.1, May 18 2001. Version 1.0, May 15 2001. 1. Metadata is "data about data" -- information like keywords, page-length, title, word-count, abstract, location, SKU, ISBN, and so on. If everyone would subscribe to such a system and create good metadata for the purposes of describing their goods, services and information, it would be a trivial matter to search the Internet for highly qualified, context-sensitive results: a fan could find all the downloadable music in a given genre, a manufacturer could efficiently discover suppliers, travelers could easily choose a hotel room for an upcoming trip. A world of exhaustive, reliable metadata would be a utopia. 2.2 People are lazy You and me are engaged in the incredibly serious business of creating information. But info-civilians are remarkably cavalier about their information. This laziness is bottomless. 3. Of course not.
Marbles Linked Data Engine Semantic reasoner A semantic reasoner, reasoning engine, rules engine, or simply a reasoner, is a piece of software able to infer logical consequences from a set of asserted facts or axioms. The notion of a semantic reasoner generalizes that of an inference engine, by providing a richer set of mechanisms to work with. The inference rules are commonly specified by means of an ontology language, and often a description language. Many reasoners use first-order predicate logic to perform reasoning; inference commonly proceeds by forward chaining and backward chaining. There are also examples of probabilistic reasoners, including Pei Wang's non-axiomatic reasoning system[citation needed], and Novamente's probabilistic logic network[citation needed]. List of semantic reasoners[edit] Existing semantic reasoners and related software: Commercial software[edit] Free to use (Closed Source)[edit] Free software (open source)[edit] See also[edit] References[edit] External links[edit]
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. 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. To find more details, please go to The Problem Here is an example <? <?
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. Secondly there is the problem of relating different files with each other. Related to this a user will often access a lot of data from the Internet which is segregated from the data stored locally on the computer, being accessed through a browser or other programs. Standardization effort[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. The RelFinder is based on the open source framework Adobe Flex, easy-to-use and works with any RDF dataset that provides standardized SPARQL access. 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. 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. 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) Documentation for the three existing Java FSL engine implementations (for Jena, Sesame and IsaViz) is now available. FSL for Sesame 2.0 (2005-11-15) Fresnel comes with a companion proposal specifying a path language for RDF called FSL. Screenshots
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. At the time, the reigning buzzword was ‘client/server computing,’ signaling a shift to relatively inexpensive servers based on the UNIX operating system. The early adopters were not the people in the glass houses, the data center managers. 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.