Giant Global Graph. Well, it has been a long time since my last post here.
So many topics, so little time. Some talks, a couple of Design Issues articles, but no blog posts. To dissipate the worry of expectation of quality, I resolve to lower the bar. More about what I had for breakfast. So The Graph word has been creeping in. Maybe it is because Net and Web have been used. The Net we normally use as short for Internet, which is the International Information Infrastructure. Simpler, more powerful. Programmers could write at a more abstract level.
The word Web we normally use as short for World Wide Web. Also, it allowed unexpected re-use. So the Net and the Web may both be shaped as something mathematicians call a Graph, but they are at different levels. Now, people are making another mental move. Biologists are interested in proteins, drugs, genes. We can use the word Graph, now, to distinguish from Web. I called this graph the Semantic Web, but maybe it should have been Giant Global Graph!
Linked Data: Evolving the Web into a Global Data Space. Semweb4j. Hypergraph Winfo.
RDF - Semantic Web Standards. Overview RDF is a standard model for data interchange on the Web.
RDF has features that facilitate data merging even if the underlying schemas differ, and it specifically supports the evolution of schemas over time without requiring all the data consumers to be changed. RDF extends the linking structure of the Web to use URIs to name the relationship between things as well as the two ends of the link (this is usually referred to as a “triple”). Using this simple model, it allows structured and semi-structured data to be mixed, exposed, and shared across different applications.
This linking structure forms a directed, labeled graph, where the edges represent the named link between two resources, represented by the graph nodes. Recommended Reading The RDF 1.1 specification consists of a suite of W3C Recommendations and Working Group Notes, published in 2014. Virtuoso. Jena Semantic Web Framework. Sesame. DBpedia. DBpedia is a crowd-sourced community effort to extract structured information from Wikipedia and make this information available on the Web.
DBpedia allows you to ask sophisticated queries against Wikipedia, and to link the different data sets on the Web to Wikipedia data. We hope that this work will make it easier for the huge amount of information in Wikipedia to be used in some new interesting ways. 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.