background preloader

Tools - Semantic Web Standards

Tools - Semantic Web Standards
Overview This Wiki contains a collection of tool references that can help in developing Semantic Web applications. These include complete development environments, editors, libraries or modules for various programming languages, specialized browsers, etc. The goal is to list such tools and not Semantic Web applications in general (the interested reader may consider looking at the W3C SW Use Case Collection for those.) The tool content of this wiki is still to be maintained by the community and not by the W3C staff. If you are interested in adding to and/or modifying the relevant pages, please consult the separate Tool Contributors’ page. Search possibilities The current Wiki contains references to 336 tools. Search through categories, i.e., reasoners, programming environments, browsers, etc. Last modified/added Tool Data in RDF There is also an option to get one RDF/XML graph for all tools. Other resources Sweet Tools maintained by Michael K. History

http://www.w3.org/2001/sw/wiki/Tools

Related:  VisualisierungrdfxmlWeb sémantique

Semantic Web I have an idea that I think is very important but I haven’t yet polished to the point where I’m comfortable sharing it. I’m going to share it anyway, unpolished, because I think it’s that useful. So here I am, handing you a dull, gray stone, and I’m saying there’s a diamond inside. Maybe even a dilithium crystal. My hope is that a few experts will see what I see and help me safely extract it.

RDF 1.1 Primer Abstract This primer is designed to provide the reader with the basic knowledge required to effectively use RDF. It introduces the basic concepts of RDF and shows concrete examples of the use of RDF. Secs. 3-5 can be used as a minimalist introduction into the key elements of RDF.

W3C Data Activity - Building the Web of Data More and more Web applications provide a means of accessing data. From simple visualizations to sophisticated interactive tools, there is a growing reliance on the availability of data which can be “big” or “small”, of diverse origin, and in different formats; it is usually published without prior coordination with other publishers — let alone with precise modeling or common vocabularies. The Data Activity recognizes and works to overcome this diversity to facilitate potentially Web-scale data integration and processing. It does this by providing standard data exchange formats, models, tools, and guidance. The overall vision of the Data Activity is that people and organizations should be able to share data as far as possible using their existing tools and working practices but in a way that enables others to derive and add value, and to utilize it in ways that suit them.

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.

Flint SPARQL Editor Demo Welcome to Flint, our editor for SPARQL queries. Features Flint 1.0 is now available. This is our first production release. OWL 2 Web Ontology Language Primer (Second Edition) W3C Recommendation 11 December 2012 This version: Latest version (series 2): Latest Recommendation: Linked Data - Design Issues Up to Design Issues The Semantic Web isn't just about putting data on the web. It is about making links, so that a person or machine can explore the web of data. With linked data, when you have some of it, you can find other, related, data. Like the web of hypertext, the web of data is constructed with documents on the web.

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]

Links to Infographic Sites, Visual Designers and C - Cool Infographics Randy's infographic design consultancy to Visualize Business Intelligence Jacob O'Neal's site focused on designing animated GIF infographics Company that helps visualize business data Rose Zgodzinski's site to help client find visual solutions Consulting, Design and Social + PR Brian Cragin is an infographic designer in San Diego A masterfully constructed infographic campaign can work wonders for your business Dashboard Design: Data Driven helps your clients better understand and act upon your information Dejure Design provides interactive and visual design services to social justice organizations seeking to make their legal work more accessible and engaging. One of the UK’s leading providers of infographics and data visualisation for bloggers and businesses of all sizes An interactive design industry We make important data beautiful and easy to understand We specialize in transmitting messages in a clear, simple and attractive way.

SPARQL 1.1 Update Graph update operations change existing graphs in the Graph Store but do not explicitly delete nor create them. Non-empty inserts into non-existing graphs will, however, implicitly create those graphs, i.e., an implementation fulfilling an update request SHOULD silently an automatically create graphs that do not exist before triples are inserted into them, and MUST return with failure if it fails to do so for any reason. (For example, the implementation may have insufficient resources, or an implementation may only provide an update service over a fixed set of graphs and the implicitly created graph is not within this fixed set).

Related: