Visualize RDF graph linked data as a connected diagram

How to visualize an RDF graph?

You can visualize RDF graph triples as a directed diagram, where subject and objects are depicted as nodes, and properties as edges, connecting subject and object nodes. Follow these steps:

• Enter web page address and submit, or if you have a code, enter it into the form and submit.
• Wait until graph is constructed and depicted, this will last depending on the size of the graph. You'll be notified, if the graph is too large to draw, so you can visualize data s triples only, without diagram
• isSemantic.net is also a RDF validator, so if your data has errors, you will be notified so you can fix them
• The RDF visualizer tool will also list triples in a subject-predicate-object table, as well as HTML tree visualization

How to visualize an RDF*/RDF-star graph?

You can visualize RDF-star graph embedded triples similary as an RDF graph: as a directed diagram, where subject and objects are depicted as nodes, and properties as edges. The difference is that edges in an RDF-star graph usually connect edges that connect subject and object nodes. Follow these steps:

• Enter web page address and submit, or if you have a code, enter it into the form and submit.
• Wait until graph is constructed and depicted, this will last depending on the size of the graph. You'll be notified, if the graph is too large to draw, so you can visualize data s triples only, without diagram
• isSemantic.net is also a RDF-star validator, so if your input data has errors, you will be notified so you can fix them
• The RDF-star visualizer tool will also list RDF-star embedded triples in a subject-predicate-object table, as well as HTML tree visualization
• Quoted or embedded triples which are not asserted, will be connected with dashed line, while asserted triples will have usual, full line. Read more about quoted and asserted triples .

What is linked data?

Linked data (also called structured data or schema markup) can be defined as data that describes data in a standardized way, or so-called metadata, and is usually information that is meant for machines to read them.
Its interoperable nature allows it to combine, i.e. link data from different domains. It's a part of a broad concept of the Semantic Web , created as well by Tim Berners-Lee; here you can read more about linked data .

For example, when we see a web page, meaning of the data comes to us by nature. However, computers do not have that ability; such web page is meaningless to the computers, and there is no way for a machine to find out what the web page is about, or to distinct one web page from another in that sense.

This is the main goal of structured data markup - to give meaning to the data that computers can read and understand.

One example of linked data in practice are rich snippets. You can explore rich snippets and their relations and hierarchy with isSemantic.net's schema markup generator tool

What is RDF?

For schema markup to be machine-readable and understandable, it itself must have a structure, which is called a data model. One of such models is RDF.

Resource Description Framework or short RDF is a standard for describing information on the Web in a machine-readable way, developed by The World Wide Web Consortium. One of its main functions is to allow information exchange from different domains and between different applications, independent of their technological environment. Its core concept is based on making statements about resources. This is achieved with using RDF data model which describes information as a subject-predicate-object model, or so-called triples.

RDF data model makes such information independent of serialization syntax so that you can use markup in any of RDF formats, it will always lead to exactly the same triples. This means that RDF formats are interchangeable: your markup in JSON-LD, Microdata, Turtle or RDFa will always contain the same information. Read more about RDF .

So, RDF is not a data format, it defines a standard way of expressing and describing relationships between things from different domains, or so-called statements. This data model can be serialized in a variety of standard formats, such as Turtle, Microdata, RDFa, JSON-LD etc. You can get more details about RDF serialization formats on our RDF converter.

What is an RDF graph?

RDF statements always have the same structure, regardless of the format:

subject predicate object

An RDF graph is a set of RDF statements (data model), which always have the same structure, regardless of the format, that consist of three parts:

subject predicate object

which is why they are called triples.

RDF triples

Subject (entity) is the first part of an RDF statement that refers to who or what the RDF statement is about.

Predicate (attribute) is the middle term (the linkage, or "verb") in an RDF statement which describes relationship between subject and object that always goes from subject to object.

Object (value) is the final part of an RDF statement that can be another entity or a plain value.

RDF graph is a a container that holds a group of statements. Triples allow creating linked data, which is more visible on an RDF graph visualization example below.

Since RDF is made for web, it uses globally unique URI (short for Uniform Resource Identifier), actually, IRI (short for International Resource Identifier, which supports international characters) as a way to name and identify web resources, so that everyone can access those resources.

URI/IRIs are usually shorten in a prefix:namespace format, also called compact URIs (or CURIEs). For example, we can declare that we are using schema.org like this: schema: "http://schema.org/". Let's say we then want to describe schema.org's WebSite, so now instead of writing down everywhere http//schema.org/WebSite, we can shorten it in schema:WebSite, which will then resolve to: http://schema.org/WebSite

These characteristics allow us to interlink different data from different domains, regardless of their format, language or system, and to find, share, reuse, combine and form new knowledge.

This is the core of linked data and the Semantic Web.

What is RDF*/RDF-star?

RDF* or RDF-star is an extension of RDF data model and syntax, that allows making statements about other statements. More specifically, this means that triples can have a role of a subject or an object in an RDF graph, the so called embedded triples. This is achieved by using (nesting) triples with annotations syntax. Typically for Turtle-star syntax would be double angle brackets: << >>, or {| |}. RDF-star embedded triples can graphically be represented as nodes that are connecting edges (properties), instead of other nodes (subjects and objects), and by that describing the nodes that are connected by that edge, i.e. that triple/statement. You can see it depicted on the following image, on which an embedded triple is a subject of multiple triples, which describe that triple as a whole. Along with diagram visualization, the image also contains triples visualization as an HTML nested tree hierarchy.

RDF-star is currently an unofficial draft of a standard, so the support for it is provisional, and will likely change according to its progress. Read more about it in RDF-star draft specification

Linked data and the Semantic Web

RDF allows us to combine different data from different domains of the world, regardless of their format, language or system. With this, we can find, share, reuse, combine and form a new knowledge.

We can use RDF to interlink different vocabularies, from different knowledge domains, by mapping and connecting the corresponding terms with same meaning in other vocabularies. This principle enables linking data to other data from other domains, which is the core of linked data and semantic web.

Linked data and semantic web allow us to inspect structured data and its relations, as well as to get a better picture of the meaning and semantics it conveys. This can help identify if structured data gives the data the exact meaning that you desire, as well as to form new information.

Here is an example of linking structured data on a web page, where we link Schema.org, Google rich snippets, Open Graph and Twitter Cards schema markup by using interlinked twitter:url, og:url and schema:url properties, which share the same value and meaning in their domains:

You can validate and analyze rich snippets with isSemantic.net's schema markup validator tool.

What is a controlled vocabulary?

As we know by nature, one term can have many meanings, for instance term name can mean anybody's or anything's name. For example, we know when some part of the web page represents a name of the company by nature, but how do search engines know that? To be able to know it, we would need a standardized context, a schema markup: this is where controlled vocabularies come in.

Controlled vocabularies (also called ontologies) are standardized sets of terms, usually arranged in a hierarchy, that are used to describe units of information about some part of the world (so-called domain of interest or the subject matter, for example, products, services, prices, companies and so on).

Controlled vocabularies usually describe specific industry or domain in standardized terms. Such vocabulary is Schema.org, that is used for describing content on the Web.