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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 datasets and makes these relationships interactively explorable. Highlighting and filtering features support analysis both on a global and detailed level. The RelFinder is based on the open source framework Adobe Flex, easy-to-use and works on any RDF dataset that provides standardized SPARQL access.

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. The term refers to a style of publishing and interlinking structured data on the Web. The basic assumption behind Linked Data is that the value and usefulness of data increases the more it is interlinked with other data. In summary, Linked Data is simply about using the Web to create typed links between data from different sources. The basic tenets of Linked Data are to: use the RDF data model to publish structured data on the Web use RDF links to interlink data from different data sources

The glue that holds together the traditional document Web is the hypertext links between HTML pages. The glue of the data web is RDF links. An RDF link simply states that one piece of data has some kind of relationship to another piece of data. These relationships can have different types. For instance, an RDF link that connects data about people can state that two people know each other; an RDF link that connects information about a person with information about publications in a bibliographic database might state that a person is the author of a specific paper.

In 'Dereferencing HTTP URIs' the W3C Technical Architecture Group (TAG) distinguish between two kinds of resources: information resources and non-information resources (also called 'other resources') . This distinction is quite important in a Linked Data context. All the resources we find on the traditional document Web, such as documents, images, and other media files, are information resources. But many of the things we want to share data about are not: People, physical products, places, proteins, scientific concepts, and so on. As a rule of thumb, all “real-world objects” that exist outside of the Web are non-information resources.

We are shifting from pushing information to pulling it. Media companies know that they will have to give their consumers full control to pull stories, news, music, television, movies, and all their content to them when they want it, where they want it, the way they want it. This shift is coming to all industries, from medicine to banking to cars and toys. 2.    The shift has already begun. The financial reporting industry has already embraced the semantic web and has built the largest commercial ecosystem of online, interoperable data so far. Many other industries are gearing up to follow. Your industry is no exception. 3.    Products will be pulled. As you take a product off the shelf, you’ll be pulling on the entire supply chain, causing a ripple effect back to the manufacturer. Your customers will start pulling your products from you, rather than you pushing them. Customers will be much more involved in product development; cycles will shorten dramatically. 4.    Big hint: This goes for marketing, too. Push marketing will become less and less relevant. Customers will say what they are looking for and you will have to respond on their terms, not yours. 5.    Services will be pulled as well. A building will order its own supplies and maintenance services. Your services may be combined with those of your competitor without you even knowing it. Customers will dictate the terms and you will have to go along. 6.    Most business processes will invert. The sales-oriented or solutions-oriented culture many companies have will be much less profitable, as market and customer-driven processes rise. Customers will soon be in a position to enter their desires in a way that can fit into your manufacturing or production processes directly. 7.    Customers will become ten times more powerful!They will keep the customer-relationship on their side. Projects like the VRM (Vendor Relationship Management) Project at Harvard and OpenID will put customers much more in charge. 8.    Pulling will have a profound impact on our entire economy. More than $3 trillion of our economy will be affected. Everything from retail to health care to the IRS will be streamlined by the principles of pull. 9.    Watch for the warning signs of push cancer. Push is about vendor lock-in and proprietary data strategies. Apple and Facebook are push companies—they will both face strong competition from the open web. They will both have to change their cultures to embrace pull or they will become much smaller. 10.   Watch for the signs of pull. Pull is the natural way businesses should work to put the customer first. When you hear about companies opening their data, giving customers account portability, and talking about interoperability with competitors, that’s the language of pull. Google embraces some of the principles of pull, but we’ll see how far they go. There is a lot at stake—learn now to open your corporate culture to the principles that will shape successful 21st century companies.

What is a Mashup? First of all, we need to agree on a basic definition of a mashup. There are many types of mashups—commercial, enterprise, data, and knowledge mashups to name a few categories. But basically, all types of mashups consist of two or more unrelated sources to create a new entity as a product, service, e-book, or online application. Mashups capture data and online applications from various points of origin and combine them to create a new functional entity specific to the needs of each corporation, reader, and customer. Mashups employ open APIs to create functional services that capture exposed data and application features from existing Web content and protocols to form a new type of online application.

What is the Semantic Web? The Semantic Web identifies content on the Web based on its meaning, providing intelligence from various data sources  or actionable features from online Web applications. This is in contrast to “syntactic” markup, which only identifies the look and layout of content. Tim Berners-Lee’s, the inventor of the World Wide Web, is one of many champions of semantic web interaction as a consistent medium for the exchange of data, information, and knowledge (see the Information Confluence for the distinction). The Semantic Web relies on the markup of separate information fields to be understood by computers in order perform much of the perfunctory background operations involved in finding, sharing, and combining information from the Web to render as usable knowledge. The Semantic Web continues to fall short of many of its highest ambitions to date, but is still supported by Tim Berners-Lee and World Wide Web Consortium (WWWC).  Criticism about its practical feasibility, lagging progress, security and privacy, and need for additional markup has yet to be resolved. Regardless, many still see the semantic content as Web 3.0, the next evolution Web. It promises to provide intelligence and interaction for semantic publishing in scientific research, exposing experimental data as structured information for real-time sharing of information by researchers. The Semantic Web is the only strategy proffered at this time to furnish intelligence and context across disparate Web information systems. Structured information based on context and meaning of information seems to be the only way to control Web data as it grows exponentially. Semantic publishing promises application interoperability and efficient, automated data integration. One of the more realistic components of the Semantic Web is Linked Data, an environment that sees all entities on the Web as individual objects. These objects can then be intelligently combined and repurposed to create a new service, product, or knowledge set.

What is Linked Data? Linked data simplifies much of the complexity of the Semantic Web. In contrast to the full Semantic Web, linked data publishes structured data using URI addresses rather than relying on a hierarchical (called ontological) cascading of parent/child relationships established by semantic markup. Using URIs, linked data handles everything on the Web as an object to be formed and presented as knowledge or actuated as new services and products. The following diagram represents the standard concept behind Linked Data. Disparate data sources from data stores, documents, Web sites, and other cloud and internal data repositories come together organically to grow a new, fully-functional knowledge set, service, or product. The main goals and concepts behind linked data includes these four principles: Use URIs to identify web objects. Use HTTP URIs to refer to and searched by readers and user agents from other applications. Provide useful information (e.g., a structured description or metadata) when the URI is referenced. Links to related URIs to expose data to improve searches of related information on the Web.

In this tutorial The purpose of this tutorial series is to create a mashup application so smart that users can literally add and remove services at will, and the system will know what to do with them. The series progresses as follows: Part 1: You learn about the concept of mashups and how they work. You then build a simple version of one and also discover serious performance problems involved in making potentially dozens of Web calls. Part 2: You solve some of that problem by using DB2's new pureXML capabilities to build an XML cache, which saves the results of previous requests and also enables you to retrieve specific information.Parts 3, 4, and 5: Ultimately, you will need to use ontologies, or vocabularies that define concepts and their relationships, so in Part 3 you started that process by learning about RDF and RDFs, two key ingredients in the Web Ontology Language (OWL), which is discussed here in Part 4. In Part 5, you will take the ontologies created in Part 4 and use them to enable users to change out information sources.Part 6: At this point, you have a working application and the framework in place so that the system can use semantic reasoning to understand the services at its disposal. In this part, you give the user control, enabling him or her to pick and choose the data that is used for a custom mashup.

The common domain implementation pattern when using Neo4j is to let the domain objects wrap a node, and store the state of the entity in the node properties. To relieve you from the boilerplate code needed for this, you can use a framework like jo4neo (intro, blog posts), where you use annotations to declare properties and relationships, but still have the full power of the graph database available for deep traversals and other graphy stuff. Here's a code sample showing jo4neo in action:view sourceprint?public class Person {  //used by jo4neo  transient Nodeid node;  //simple property  @neo String firstName;  //helps you store a java.util.Date to neo4j  @neo Date date;  // jo4neo will index for you  @neo(index=true) String email;  // many to many relation  @neo Collection<role> roles;    /* normal class oriented  * programming stuff goes here  */}</role>