Online Access (Navigation privée) The DBpedia data set can be accessed online via a SPARQL query endpoint and as Linked Data. 1. Querying DBpedia The DBpedia data set enables quite astonishing query answering possibilities against Wikipedia data. 1.1. Public SPARQL Endpoint There is a public SPARQL endpoint over the DBpedia data set at OpenLink Virtuoso as the back-end database engine. There is a list of all DBpedia data sets that are currently loaded into the SPARQL endpoint. You can ask queries against DBpedia using: the Leipzig query builder at the OpenLink Interactive SPARQL Query Builder (iSPARQL) at the SNORQL query explorer at (does not work with Internet Explorer); or any other SPARQL-aware client(s). Fair Use Policy: Please read this post for information about restrictions on the public DBpedia endpoint. 1.2. There is a public Faceted Browser “search and find” user interface at 1.3. here. 1.4. 1.5. 1.6.
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.
Browse:Keyword Search: immunology The Cyc Foundation (Navigation privée) We’re pleased to bring you an update on several recent activities related to OpenCyc and the Semantic Web. UMBELThe lightweight UMBEL ontology is finally live. Mike Bergman and Fred Giasson deserve a big round of applause for the tremendous effort they’ve put into this release. They’ve meticulously selected 20,000 of the most relevant concepts from the more than 300,000 in the Cyc KB. What’s more, relationships between these concepts have been simplified to facilitate discovery of related concepts and alignment with external ontologies. One can use UMBEL to describe things, to help develop new ontologies and to put individuals in context. Wikipedia and OpenCyc AlignmentWe collaborated with Olena Medelyan and Catherine Legg of the University of Waikato, New Zealand in their effort to automatically identify ontologically equivalent concepts in Cyc and Wikipedia. Details and downloadable versions of the mappings can be found at the project website.
Visual Data Web - Visually Experiencing the Data Web 5 Online Media Trends for 2011 As the new year begins, here are five trends that are likely to make an impact in the online media world in 2011. Cloud-based media libraries The idea of ‘iTunes in the cloud’ has been floating around for years and despite rumors throughout 2010, it hasn’t materialized yet. Thus far only small players like mSpot and LaLa (purchased and closed down by Apple in 2010) have addressed cloud-based media solutions in this way. A more readable Web In 2010, the success of the iPad forced publishers to reconsider the way they presented their content and Flipboard was a wakeup call to the idea of reformatting existing content in a more readable way. We recently covered Treesaver, a company that will soon offer a set of customizable templates that publishers can use to present their content with a highly readable magazine-style app. Shakeout in the e-book market As 2010 drew to a close, the battle for the e-book market notched up a gear with the launch of the Google eBookstore. The “Post-blog” Blog
RDF For The Rest Of Us (Navigation privée The web professional's online magazine of choice. In: Articles By Keith Alexander Published on July 30, 2007 You have a website full of information, and you want to make it easier for people to reuse it—but what format should you publish it in? You’ve looked at various XML schemas and microformats, but none of them really describes all the information that you want to publish. This is where RDF comes in. What is RDF? stands for Resource Description Framework. resource is simply a thing; a person, a book, a keyboard, a blog post, a fish tank, an idea: any thing that can be described. RDF for Web Publishers RDF is different. If you find a vocabulary that can be used to describe some part of your data, then great, that data can be interoperable; you still have the freedom to describe the rest of your data with terms from as many other vocabularies as you need. For publishing your data, RDF offers you great flexibility and interoperability. Fantastic. RDF for Web Developers What is an RDF Triple?
Faceted Search Faceted Wikipedia Search allowed users to ask complex queries, like “Which Rivers flow into the Rhine and are longer than 50 kilometers?” or “Which Skyscrapers in China have more than 50 floors and have been constructed before the year 2000?” against Wikipedia. Unfortunately, the application cannot be offered any more. Faceted Search DBpedia Search implements the faceted search paradigm. The User Interface The user interface consists of several interacting components, which are highlighted in the following screenshot and described below. Search Results: The names, abstracts and (if available) images of the Wikipedia entries matching the current criteria are displayed in the center of the page. Background Faceted Wikipedia Search has been jointly developed by neofonie GmbH, Berlin and the Web-based Systems Group at Freie Universität Berlin. Land der Ideen Competition blog post for more details on the price. BIS2010 Paper about Faceted Wikipedia Search
Synthesis Lectures on Information Concepts, Retrieval, and Services Lectures available online | Lectures under development Editor Gary Marchionini, University of North Carolina at Chapel Hill Annual Subscription Pricing for this Series Synthesis Lectures on Information Concepts, Retrieval, and Services is edited by Gary Marchionini of the University of North Carolina. The series will publish 50- to 100-page publications on topics pertaining to information science and applications of technology to information discovery, production, distribution, and management. The scope will largely follow the purview of premier information and computer science conferences, such as ASIST, ACM SIGIR, ACM/IEEE JCDL, and ACM CIKM. Series ISSN: 1947-945X (print) 1947-9468 (electronic) For related titles, please see our series in Data ManagementHuman Language Technologies Lectures available online What is RSS? Digital Library Technologies: Complex Objects, Annotation, Ontologies, Classification, Extraction, and Security Information Concepts: From Books to Cyberspace Identities
The Problem With The Semantic Web: Usability Check out Duane Degler’s presentation User Interfaces for the Semantic Web. In skimming it, I came across this quote from semantic web guru Ora Lassila, which comes from his blog post Semantic Web Soul Searching: After 10+ years of work into various aspects of the Semantic Web and its constituent technologies, I am now fully convinced (read: no longer in denial) that most of the remaining challenges to realize the Semantic Web vision have nothing to do with the underlying technologies involving data, ontologies, reasoning, etc. Instead, it all comes down to user interfaces and usability. Somehow, I repeatedly run into a situation where some use of Semantic Web technologies that would make a nice end-user application is “blocked” by the fact that the user interface is the real challenge. For a long time (longer than I have worked on the Semantic Web) I have wanted to build systems that work on users’ behalf. Like this: Like Loading...
Semantic Search Survey - SWUIWiki From SWUIWiki Hildebrand et al. are conducting a survey on the role of semantics in current end user search applications. An analysis of this survey is described in [1] . On this Wiki we would like to maintain and extend the survey. In addition, we are compiling a common vocabulary of terms (including definitions) that are applicable to semantic search. The generic characteristics of the analyzed systems and links to related papers and demos are listed on the systems overview page . Other resources W3C maintains a list of Semantic Web Tools and various others exists, such as the Developers Guide to Semantic Web Toolkits and the Comprehensive Listing of Semantic Web and Related Tools by Michael K. Analysis of Systems (inProgress) We have started compiling a list of systems that provide access to semantic web data through a graphical user interface. Example Search phase Feature Functionality Interface Components Query construction Free text input keyword(s) natural language Single text entry Stemming
Breakthrough Analysis: Two + Nine Types of Semantic Search -- InformationWeekBreakthrough Analysis: Two + Nine Types of Semantic Search - software Blog There's more to it than offering related results. Here are 11 approaches that join semantics to search. Semantics is hot, but only in a geeky sort of way. Contrast with search, which long ago shed its geeky image to become the Web's #1 utility. Search and semantics have similar goals and rely on similar technologies. Both apply data-structuring techniques to make information more findable and usable. Semantic search is still in a definitional phase, "on its way!" Semantics (in an IT setting) is meaningful computing: the application of natural language processing (NLP) to support information retrieval, analytics, and data-integration that compass both numerical and "unstructured" information. I've come up with a list of eleven approaches that join semantics to search: my two Bing-ers plus nine more. Two + Nine Views of Semantic Search Related searches/queries. More Insights
WikiSummarizer WikiSummarizer is a Web-based application specializing in automatic summarization of Wikipedia articles. Automatic summarization is the creation of a shortened version of a text by a computer program. The result is a summary that presents the most important points of the original text. A summary is a shorter version of the original information. It highlights the major points from the much longer article. WikiSummarizer automatically summarizes the Wikipedia articles. The blending of visualization with summarization, knowledge browsing, mind mapping provides you with a wide range of means to explore relevant content. All the summaries are stored in the WikiSummarizer knowledge base. In fact when we are summarizing, we are zipping through the whole content, homing in on the important chunks. With the ability to summarize web pages everybody can become an instant speed reader. You instantly see what the web page is about. You get more done in less time. The key benefits are: Yes.