Wiki - Semantic Web Standards Semantic Web The promise of web standards W3C standards define an open web platform for application development. The web has the unprecedented potential to enable developers to build rich interactive experiences, that can be available on any device. The platform continues to expand, but web users have long ago rallied around HTML as the cornerstone of the web. Many more technologies that W3C and its partners are creating extend the web and give it full strength, including CSS, SVG, WOFF, WebRTC, XML, and a growing variety of APIs. Read more about W3C Standards Why W3C web standards? W3C publishes recommendations, that are considered web standards. W3C develops technical specifications according to the W3C Process, which is designed to maximize consensus, ensure quality, earn endorsement and adoption by W3C Members and the broader community. W3C web standards are optimized for interoperability, security, privacy, web accessibility, and internationalization. Value of creating standards at W3C
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. 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) Screenshots
Books - Semantic Web Standards This page contains information on books that are strictly on the Semantic Web and Linked Data. There are, of course, lots of other books on Knowledge Representation, Logic, XML, Databases, etc, that are all relevant for the Semantic Web, but adding these to this list would be counter productive… Keeping such list up-to-date is obviously a problem. It can be hoped that the community at large will help maintaining these pages. The order in the listings below does not reflect any assessment of the product or tool; simple year and alphanumeric order is used. Beyond the obvious sources (Amazon and other listings), the initial set in this list reused publication lists that were published elsewhere, eg, Nova Spivak’s Listmania list, or the lists maintained by Danny Ayers or Uldis Bojārs a.k.a. Thanks to the book mashup service set up by Chris Bizer and friends the RDF data (providing such information as Amazon's relevant data) for most of the books is also available. Textbooks
Kuchen für alle! 15 hilfreiche Tools für die Datenvisualisierung Datenvisualisierung bietet sich immer dann an, wenn man Informationen an andere Menschen weitergeben will, die mit dem untermauernden Zahlenmaterial nicht vertraut sind. Je größer die Datensätze, desto komplizierter wird eine händische Aufbereitung. Entsprechende Tools können die Arbeit erheblich erleichtern und schicke Charts basteln – wie beispielsweise unser Artikel zur Datenvisualisierung mit Charts.js zeigt. In den vergangenen Jahren hat das Angebot an webbasierten Lösungen und Desktop-Anwendungen für das Sammeln, Analysieren und visuelle Aufbereiten von Daten erheblich zugenommen. Wer mit großen Datensammlungen hantiert und auf perfekte Organisation, optimale Lesbarkeit oder ein individuelles Design nicht verzichten will, muss allerdings technische Kenntnisse und grafisches Knowhow mitbringen. Axiis Bei Axiis handelt es sich um ein Framework für die Datenvisualisierung, das sich sowohl an Einsteiger als auch fortgeschrittene Entwickler richtet. BirdEye Bonsai Ember Charts Envision.js
Extensible use of RDF in a Business Context Kerstin Forsberg, Viktoria Institute and Adera, O Hamngatan 41-43, S-411 10 Gothenburg Sweden, kerstin.forsberg@aderagroup.com Lars Dannstedt, Volvo Information Technology, Web Program Center, S-405 08, Gothenburg Sweden, it1.larsd@memo.volvo.se Abstract The next generation of intranets should facilitate the structuring of information as well as the organising of communication in networking organisations. Keywords: Metadata, RDF, XML, Intranet 1. The first generation of intranets provided easy access to large amount of information using (hyper)links. The introduction of XML (eXtensible Markup Language) will make information self-describing [2] and facilitate information discovering. Currently, many organisations use the Dublin Core schema [7] for information resources on the public Internet as a template for recommending schemas for intranets. The framework could be seen as a meta model for a shared information spaces. The rest of the paper is structured as follows. 2. 3. 4. Figure 1. 5.
OWL at Manchester FlowingData How to publish Linked Data on the Web This document provides a tutorial on how to publish Linked Data on the Web. After a general overview of the concept of Linked Data, we describe several practical recipes for publishing information as Linked Data on the Web. This tutorial has been superseeded by the book Linked Data: Evolving the Web into a Global Data Space written by Tom Heath and Christian Bizer. This tutorial was published in 2007 and is still online for historical reasons. The Linked Data book was published in 2011 and provides a more detailed and up-to-date introduction into Linked Data. The goal of Linked Data is to enable people to share structured data on the Web as easily as they can share documents today. The term Linked Data was coined by Tim Berners-Lee in his Linked Data Web architecture note. Applying both principles leads to the creation of a data commons on the Web, a space where people and organizations can post and consume data about anything. This chapter describes the basic principles of Linked Data.
Knowledge representation and reasoning Knowledge representation and reasoning (KR) is the field of artificial intelligence (AI) devoted to representing information about the world in a form that a computer system can utilize to solve complex tasks such as diagnosing a medical condition or having a dialog in a natural language. Knowledge representation incorporates findings from psychology about how humans solve problems and represent knowledge in order to design formalisms that will make complex systems easier to design and build. Knowledge representation and reasoning also incorporates findings from logic to automate various kinds of reasoning, such as the application of rules or the relations of sets and subsets. Examples of knowledge representation formalisms include semantic nets, Frames, Rules, and ontologies. Examples of automated reasoning engines include inference engines, theorem provers, and classifiers. Overview[edit] This hypothesis was not always taken as a given by researchers. History[edit] Characteristics[edit]